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<!DOCTYPE html> <html lang="en" xmlns:mml="http://www.w3.org/1998/Math/MathML" data-vue-meta-server-rendered> <head>   <script id="Cookiebot" src="https://consent.cookiebot.com/uc.js" data-cbid="011c3436-7d64-4a27-ac89-ad262dbcfb8f" type="text/javascript"></script>   <script async src="https://www.googletagmanager.com/gtag/js?id=G-DTTE7J8M7F" data-cookieconsent="statistics"></script> <script data-cookieconsent="statistics"> window.gaDebug = false; window.dataLayer = window.dataLayer || []; function gtag() { if (window.gaDebug) { console.log("XXX gaDebug:", arguments); } dataLayer.push(arguments); } gtag('js', new Date()); (function () { try { var g = localStorage.getItem('ga_debug') || ''; window.gaDebug = (g == 'true'); } catch (e) { console.log("ga_debug error:", e); } gtag('config', 'G-DTTE7J8M7F', { 'debug_mode': window.gaDebug, 'send_page_view': false, // 'cookie_domain': 'none', }); })(); </script> <title>Emulsion Stabilization with Lignosulfonates | IntechOpen</title> <meta data-vue-meta="ssr" charset="utf-8"><meta data-vue-meta="ssr" http-equiv="X-UA-Compatible" content="IE=edge"><meta data-vue-meta="ssr" name="viewport" content="width=device-width, initial-scale=1"><meta data-vue-meta="ssr" name="description" content="Lignosulfonates are biobased surfactants and specialty chemicals. Due to their amphiphilic nature, they can be utilized in many technical applications, such as plasticizers, dispersants, stabilizers, and agrochemical formulations. Here, their ability to stabilize emulsions plays an important role. This chapter hence explains the fundamentals of emulsion stabilization with lignosulfonates. First, basic concepts are introduced along with the production and chemical make-up of lignosulfonates. Second, the interfacial activity is discussed. Parameters that affect interfacial activity and emulsion stabilization efficiency of lignosulfonates are furthermore treated. Such parameters may include salinity, pH, the presence of cosolvents and cosurfactants. Third, the underlying mechanisms of emulsion stabilization are outlined. The goal of this chapter is to introduce the reader to important fundamentals, and to draw the link between basic research and industrial practice."><meta data-vue-meta="ssr" name="title" content="Emulsion Stabilization with Lignosulfonates | IntechOpen"><meta data-vue-meta="ssr" name="authors" content="Jost Ruwoldt"><meta data-vue-meta="ssr" name="category" content="Chapter"><meta data-vue-meta="ssr" property="og:type" content="article"><meta data-vue-meta="ssr" property="og:url" content="https://www.intechopen.com/chapters/83868"><meta data-vue-meta="ssr" property="og:title" content="Emulsion Stabilization with Lignosulfonates"><meta data-vue-meta="ssr" property="og:description" content="Lignosulfonates are biobased surfactants and specialty chemicals. Due to their amphiphilic nature, they can be utilized in many technical applications, such as plasticizers, dispersants, stabilizers, and agrochemical formulations. Here, their ability to stabilize emulsions plays an important role. This chapter hence explains the fundamentals of emulsion stabilization with lignosulfonates. First, basic concepts are introduced along with the production and chemical make-up of lignosulfonates. Second, the interfacial activity is discussed. Parameters that affect interfacial activity and emulsion stabilization efficiency of lignosulfonates are furthermore treated. Such parameters may include salinity, pH, the presence of cosolvents and cosurfactants. Third, the underlying mechanisms of emulsion stabilization are outlined. The goal of this chapter is to introduce the reader to important fundamentals, and to draw the link between basic research and industrial practice."><meta data-vue-meta="ssr" name="twitter:card" content="summary"><meta data-vue-meta="ssr" name="DC.Format" content="text/html"><meta data-vue-meta="ssr" name="DC.Language" content="en"><meta data-vue-meta="ssr" name="DC.Title" content="Emulsion Stabilization with Lignosulfonates"><meta data-vue-meta="ssr" name="DC.Identifier" content="10.5772/intechopen.107336"><meta data-vue-meta="ssr" name="DC.Date" content="2022/09/30"><meta data-vue-meta="ssr" name="DC.Publisher" content="IntechOpen"><meta data-vue-meta="ssr" name="DC.AccessRights" content="open-access"><meta data-vue-meta="ssr" name="citation_fulltext_world_readable" content=""><meta data-vue-meta="ssr" name="citation_access" content="all"><meta data-vue-meta="ssr" name="citation_fulltext_html_url" content="https://www.intechopen.com/chapters/83868"><meta data-vue-meta="ssr" name="citation_publisher" content="IntechOpen"><meta data-vue-meta="ssr" name="citation_publication_date" content="2022/09/30"><meta data-vue-meta="ssr" name="citation_online_date" content="2022/09/30"><meta data-vue-meta="ssr" name="citation_title" content="Emulsion Stabilization with Lignosulfonates"><meta data-vue-meta="ssr" name="citation_doi" content="10.5772/intechopen.107336"><meta data-vue-meta="ssr" name="citation_pdf_url" content="https://www.intechopen.com/citation-pdf-url/83868"><meta data-vue-meta="ssr" name="citation_xml_url" content="https://www.intechopen.com/citation-xml-url/83868"><meta data-vue-meta="ssr" name="citation_public_url" content="https://www.intechopen.com/chapters/83868"><meta data-vue-meta="ssr" name="citation_isbn" content="978-1-83968-546-0"><meta data-vue-meta="ssr" name="DC.relation.ispartof" content="Lignin - Chemistry, Structure, and Application"><meta data-vue-meta="ssr" name="citation_inbook_title" content="Lignin - Chemistry, Structure, and Application"><meta data-vue-meta="ssr" property="og:image" content="https://cdnintech.com/books/11902/1718282379-1978756798/web-cover.jpg"><meta data-vue-meta="ssr" name="twitter:image" content="https://cdnintech.com/books/11902/1718282379-1978756798/web-cover.jpg"><meta data-vue-meta="ssr" name="thumbnail" content="https://cdnintech.com/books/11902/1718282379-1978756798/web-cover-300.jpg"><meta data-vue-meta="ssr" name="citation_author" content="Jost Ruwoldt"><meta data-vue-meta="ssr" name="DC.Contributor" content="Jost Ruwoldt"><meta data-vue-meta="ssr" name="citation_reference" content="Sixta H. 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50em){.cards__right{padding-top:5.5rem}}.card{position:relative;z-index:2;box-sizing:border-box;display:flex;flex-direction:column;justify-content:flex-start;align-items:flex-start;padding:2rem;width:18.7rem;height:18.7rem;background:#fffdea;border-radius:1.6rem}.card--light{background-color:#FFFDEA}.card--auto-height{height:auto !important}.card--outlined{border:1px solid #FBB2B2;width:22rem;height:22rem;padding:2rem}.card:not(:last-of-type){margin-bottom:3.2rem}@media screen and (max-width: 50em){.card:not(:last-of-type){margin-bottom:0.8rem}}@media screen and (max-width: 62.5em){.card{background-color:#FFFDEA;width:15.2rem;height:18rem}}.card__title{font-family:'Relative Bold', sans-serif;font-weight:400;font-style:normal;-webkit-font-smoothing:auto;-webkit-text-size-adjust:none;font-size:2.4rem;line-height:2.4rem;color:#e10000}@media screen and (max-width: 62.5em){.card__title{font-size:1.8rem}}.card__title>span{display:block;font-size:.7em}@media screen and (max-width: 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.section{font-size:1.8rem;line-height:2.4rem;margin-bottom:3rem;padding-bottom:2rem}.reader-body[data-v-37a3ac16] .section:last-child{border-bottom:0;padding-bottom:0;margin-bottom:6rem}.reader-body[data-v-37a3ac16] .section .section{padding:0;margin:0;border:0}.reader-body[data-v-37a3ac16] .caption{margin-bottom:3rem}.reader-body[data-v-37a3ac16] .caption h3{font-family:'FSBrabo', serif;font-weight:700;font-style:normal;-webkit-font-smoothing:auto;-webkit-text-size-adjust:none;font-size:1.8rem;line-height:1.5;display:inline;margin-right:1rem}.reader-body[data-v-37a3ac16] .caption p{font-size:1.8rem;line-height:1.5;display:inline}.reader-body[data-v-37a3ac16] .inline-formula .MathJax_Display{display:inline !important}@media screen and (max-width: 34.375em){.reader-body[data-v-37a3ac16] .media-panel .media{padding:1rem;margin-bottom:1rem}.reader-body[data-v-37a3ac16] .formula{font-size:1.2rem;margin:4rem 0;text-align:center}.reader-body[data-v-37a3ac16] .formula>strong{font-size:.8rem;display:block;text-align:right;margin-top:1rem}}@media screen and (min-width: 34.4375em){.reader-body[data-v-37a3ac16] .media-panel .media{padding:2rem;margin-bottom:2rem}.reader-body[data-v-37a3ac16] .formula{margin:5rem 0;text-align:center;position:relative}.reader-body[data-v-37a3ac16] .formula>strong{position:absolute;right:0;top:50%;margin-top:-.5rem;font-size:.6rem}}@media screen and (min-width: 34.4375em) and (max-width: 50em){.reader-body[data-v-37a3ac16] .formula{font-size:1.4rem}}@media screen and (min-width: 50.0625em){.reader-body[data-v-37a3ac16] .formula{font-size:1.6rem}}@media screen and (min-width: 62.5625em){.long-formula[data-v-37a3ac16] .section #df_EA\.4 .equ{left:3rem !important}} .figures[data-v-2b3aba72]{margin-top:7.2rem}.figures h2[data-v-2b3aba72]{font-size:2.4rem;line-height:3.2rem;margin-bottom:2.4rem;font-weight:bold}.figures .carousel-container[data-v-2b3aba72]{padding:2rem;border:1px solid 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sans-serif;font-weight:400;font-style:normal;-webkit-font-smoothing:auto;-webkit-text-size-adjust:none;color:#e10000;font-size:1.6rem;line-height:2.4rem;overflow:hidden}.ref-link[data-v-1797c9ee]{margin-top:1rem}.footnotes-link[data-v-1797c9ee]{margin-top:1rem;margin-bottom:3rem}.section-footer[data-v-1797c9ee]{margin-bottom:1.6rem}.section-footer p[data-v-1797c9ee],.section-footer a[data-v-1797c9ee]{font-family:'Relative Faux', sans-serif;font-weight:400;font-style:normal;-webkit-font-smoothing:auto;-webkit-text-size-adjust:none;font-size:1.6rem;line-height:2.4rem}.section-footer .intechopen-icon[data-v-1797c9ee]{width:2rem;height:2rem;margin-right:1rem;padding-bottom:0.3rem}.section-footer .chapter-caption[data-v-1797c9ee]{padding-top:4.8rem;border-top:1px solid #B3AF93;margin-top:5.6rem;text-transform:capitalize;margin-bottom:0.8rem}.section-footer .next-chapter[data-v-1797c9ee]{font-family:'FSBrabo', serif;font-weight:700;font-style:normal;-webkit-font-smoothing:auto;-webkit-text-size-adjust:none;font-size:1.8rem;line-height:2.4rem;color:#e10000}.section-footer .next-chapter[data-v-1797c9ee]:hover{color:#870000}.section-footer .chapter-stats[data-v-1797c9ee]{font-size:1.2rem;color:#060B13;letter-spacing:1px}.modal-active[data-v-1797c9ee]{z-index:1001}.ads-link[data-v-1797c9ee]{display:block;font-size:1.2rem;letter-spacing:1px;text-decoration:none;text-align:center;text-transform:uppercase;color:#777777}.ads-link[data-v-1797c9ee]:hover{color:#777777}.ads-link[data-v-1797c9ee]:after{content:none !important}.text--red[data-v-1797c9ee]{color:#e10000}.ctas[data-v-1797c9ee]{font-family:'Relative Book', sans-serif;font-weight:400;font-style:normal;-webkit-font-smoothing:auto;-webkit-text-size-adjust:none;font-size:1.6rem;line-height:2.4rem;padding-top:5.6rem;border-top:1px solid #B3AF93;margin-top:5.6rem}.ctas img[data-v-1797c9ee]{display:inline-block;width:2rem;height:auto;margin-right:1rem}.ctas button[data-v-1797c9ee]{color:#e10000;display:block;outline:0;padding:0;border:0;background:none}.ctas button[data-v-1797c9ee]:hover{color:#870000}.ctas a[data-v-1797c9ee]{color:#e10000;display:block;margin-top:2rem}.ctas a[data-v-1797c9ee]:hover{color:#870000}.shortcut[data-v-1797c9ee]{display:block;font-family:'Relative Book', sans-serif;font-weight:400;font-style:normal;-webkit-font-smoothing:auto;-webkit-text-size-adjust:none;color:#e10000;font-size:1.6rem;line-height:2.4rem;padding-left:1.7rem}.shortcut[data-v-1797c9ee]:hover{color:#870000}.shortcut[data-v-1797c9ee]:hover{color:#e10000}[data-v-1797c9ee] .share-and-download .share-module{left:0;width:57%}[data-v-1797c9ee] .share-and-download .share-module::before{right:6.4rem} @media screen and (min-width: 62.5625em){#app[data-scrolldir="up"] .sections-toggle .clip{height:calc(100vh - 85.5px - 70.8px - 90px)}} .unnumbered-section[data-v-be6610d8]{padding-left:1.7rem} .modal[data-v-faa01f88]{position:fixed;z-index:2000;top:0;bottom:0;left:0;right:0;display:flex;justify-content:center;align-items:center;overflow:hidden;background-color:#000;background-color:rgba(0,0,0,0.4)}.modal__content[data-v-faa01f88]{overflow:auto;width:100%;height:100%}@media screen and (min-width: 62.5625em){.modal__content[data-v-faa01f88]{display:flex;align-items:center}}.subtitle[data-v-faa01f88]{font-family:'Relative Bold', sans-serif;font-weight:400;font-style:normal;-webkit-font-smoothing:auto;-webkit-text-size-adjust:none;font-size:1.2rem;line-height:2.4rem;letter-spacing:0.5px;text-transform:uppercase;vertical-align:middle}.subtitle--desktop[data-v-faa01f88]{font-size:1.4rem;margin-bottom:0.8rem}.text[data-v-faa01f88]{font-family:'Relative Book', 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48em){.cta[data-v-cf751d1e]{font-size:1.6rem;line-height:2.4rem}} [data-v-51b9c4f3] .VueCarousel-slide{text-align:center}[data-v-51b9c4f3] .VueCarousel-navigation-button{z-index:10;top:9em !important;border:0;border-radius:4px;background-color:#ffffff !important;box-shadow:0px 2.4rem 8.8rem rgba(0,0,0,0.05)}@media screen and (min-width: 62.5625em){[data-v-51b9c4f3] .VueCarousel-navigation-button{top:13.2em !important;padding:2.4rem !important}}.smallSlider[data-v-51b9c4f3] .VueCarousel-navigation-button{top:5.5em !important}[data-v-51b9c4f3] .VueCarousel-navigation-button .icr{color:#e10000;font-size:2em;width:2.5rem;height:2.5rem}[data-v-51b9c4f3] .VueCarousel-navigation-button:hover .icr{color:#870000}[data-v-51b9c4f3] .VueCarousel-navigation-prev{transform:translateY(0) translateX(-10px) !important}[data-v-51b9c4f3] .VueCarousel-navigation-next{transform:translateY(0) translateX(10px) !important}[data-v-51b9c4f3] .VueCarousel-navigation-prev .icr{transform:rotate(180deg)}[data-v-51b9c4f3] .VueCarousel-navigation--disabled{display:none}[data-v-51b9c4f3] .VueCarousel-pagination{margin-top:1.6rem;text-align:left !important}@media screen and (min-width: 48em){[data-v-51b9c4f3] .VueCarousel-pagination{margin-top:4rem}}[data-v-51b9c4f3] .VueCarousel-dot-button{width:1rem !important;height:0.6rem !important;border-radius:0 !important} .book-item[data-v-69cc9686]{position:relative;display:inline-block;vertical-align:top;text-align:left}.book-item__downloads[data-v-69cc9686]{display:flex;align-items:center;position:absolute;top:0;right:0;z-index:10;transform:translate(0%, -50%);font-family:'Relative Bold', sans-serif;font-weight:400;font-style:normal;-webkit-font-smoothing:auto;-webkit-text-size-adjust:none;font-size:1rem;line-height:1.2rem;letter-spacing:1px;padding:1rem 0.3rem;background-color:#ffffff;box-shadow:0px 0.4rem 0.4rem rgba(0,0,0,0.15)}.book-item__downloads img[data-v-69cc9686]{display:inline-block;height:1.4rem;width:1.4rem;margin-right:0.5rem}@media screen and (min-width: 62.5625em){.book-item__downloads[data-v-69cc9686]{font-size:1.4rem;line-height:2rem;transform:translate(20%, -50%)}.book-item__downloads img[data-v-69cc9686]{height:2rem;width:2rem}}.cover-wrap[data-v-69cc9686]{max-width:21.4rem;margin-bottom:1.5rem}.title[data-v-69cc9686]{font-family:'Relative Bold', sans-serif;font-weight:400;font-style:normal;-webkit-font-smoothing:auto;-webkit-text-size-adjust:none;font-size:1.4rem;line-height:2rem;color:#e10000;text-align:left;margin-bottom:0.8rem}@media screen and (min-width: 62.5625em){.title[data-v-69cc9686]{font-size:1.6rem;line-height:2.4rem}}.edited[data-v-69cc9686]{font-family:'Relative Book', sans-serif;font-weight:400;font-style:normal;-webkit-font-smoothing:auto;-webkit-text-size-adjust:none;font-size:1.2rem;line-height:1.6rem;text-align:left}@media screen and (min-width: 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2.5rem}}.btn--large[data-v-4e735fe2]:hover,.btn--large[data-v-4e735fe2]:active{background:#BE0000}.btn--large[data-v-4e735fe2]:disabled{color:#FCE5E5;background:#FBB2BA;cursor:default !important}.btn--small[data-v-4e735fe2]{font-size:1.6rem;line-height:2.4rem;color:#fffdea;background:#e10000;width:12rem;padding:1.4rem 3.4rem}@media screen and (max-width: 62.5em){.btn--small[data-v-4e735fe2]{font-size:1.4rem;padding:1rem 2.5rem;width:9.6rem}}.btn--small[data-v-4e735fe2]:hover,.btn--small[data-v-4e735fe2]:active{background:#BE0000}.btn--small[data-v-4e735fe2]:disabled{color:#FCE5E5;background:#FBB2BA;cursor:default !important}.btn--outline[data-v-4e735fe2]{color:#e10000;background:#fffdea !important;border:1px solid #e10000}.btn--outline[data-v-4e735fe2]:hover,.btn--outline[data-v-4e735fe2]:active{color:#BE0000;border-color:#BE0000}.btn--outline[data-v-4e735fe2]:disabled{color:#F08080;background:#F08080;border-color:#F08080;cursor:default 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href="https://ehealthcaresolutions.com/contact-us/" target="_blank" class="ads-link" data-v-79b2068e>Advertisement</a> <div id="intechopen-intechopen-0" data-v-79b2068e></div>  </div>  <div class="main" data-v-79b2068e><aside class="left-col" data-v-79b2068e><div style="height: 100%;" data-v-79b2068e><div class="track" data-v-79b2068e><a href="https://ehealthcaresolutions.com/contact-us/" target="_blank" class="ads-link" style="margin-top: 3px;" data-v-79b2068e> Advertisement </a> <div id="intechopen-intechopen-5" class="ads-link" style="padding-bottom: 4.5rem;" data-v-79b2068e></div>  </div></div></aside> <div class="middle-col" data-v-79b2068e><div class="intro" data-v-46823712 data-v-79b2068e><h2 class="title" data-v-46823712>Abstract</h2> <div class="body" data-v-46823712><p data-v-46823712>Lignosulfonates are biobased surfactants and specialty chemicals. Due to their amphiphilic nature, they can be utilized in many technical applications, such as plasticizers, dispersants, stabilizers, and agrochemical formulations. Here, their ability to stabilize emulsions plays an important role. This chapter hence explains the fundamentals of emulsion stabilization with lignosulfonates. First, basic concepts are introduced along with the production and chemical make-up of lignosulfonates. Second, the interfacial activity is discussed. Parameters that affect interfacial activity and emulsion stabilization efficiency of lignosulfonates are furthermore treated. Such parameters may include salinity, pH, the presence of cosolvents and cosurfactants. Third, the underlying mechanisms of emulsion stabilization are outlined. The goal of this chapter is to introduce the reader to important fundamentals, and to draw the link between basic research and industrial practice.</p></div></div> <div class="keywords keywords-chapters" data-v-260fc791 data-v-79b2068e><h3 class="subTitle" data-v-260fc791>Keywords</h3> <ul data-v-260fc791><li class="item" data-v-260fc791>lignin</li><li class="item" data-v-260fc791> lignosulfonates</li><li class="item" data-v-260fc791> surfactant</li><li class="item" data-v-260fc791> emulsion</li><li class="item" data-v-260fc791> dispersion</li><li class="item" data-v-260fc791> stabilizer</li><li class="item" data-v-260fc791> interfacial activity</li><li class="item" data-v-260fc791> colloid chemistry</li></ul></div> <div id="section-chapter-and-author" class="info collapsed" data-v-5ab781cd data-v-79b2068e><div class="toggle-header" data-v-5ab781cd><h2 class="title" data-v-5ab781cd>Author Information</h2> <a class="title" data-v-5ab781cd>Show +</a></div> <div class="wrap" data-v-5ab781cd><ul data-v-5ab781cd><li class="authorsItem" data-v-5ab781cd><h4 class="author" data-v-5ab781cd>Jost Ruwoldt<span data-v-5ab781cd>*</span></h4> <span class="position" data-v-5ab781cd><ul class="list"><li>RISE PFI AS, Trondheim, Norway</li></ul></span></li></ul> <p class="title" data-v-5ab781cd>*Address all correspondence to: jostru.chemeng@gmail.com</p></div></div>  <div class="reader-body reader-body" data-v-37a3ac16 data-v-79b2068e><div class="section" id="sec_1" data-lvl="1"><h2 class="heading main-title">1. Introduction</h2><p id="p2">Lignosulfonates are biobased specialty chemicals, which are generated as a by-product during sulfite pulping of wood [<a href="#B1" class="ref-link" data-ref-style="bibr">1</a>]. They are water-soluble polyelectrolytes, as they contain ionizable moieties such as sulfonate and carboxylic acid groups. Having preserved the polyaromatic backbone of lignin, they are functional amphiphiles with surfactant-like behavior. Due to their rich chemistry, lignosulfonates are found in many industrial applications [<a href="#B2" class="ref-link" data-ref-style="bibr">2</a>]. This book chapter discusses the fundamentals of one of those applications, that is, emulsion stabilization. By explaining the working principles of interfacial adsorption and emulsion stabilization, the goal is to provide a reference for applied and fundamental research, as well as industry and potential end-users of lignosulfonates.</p><p id="p3">Next to cellulose, lignin is considered the second most abundant and important polymeric compound in plants [<a href="#B1" class="ref-link" data-ref-style="bibr">1</a>]. Here, it fulfills functions such as water-proofing the cell-walls and adding to the mechanical cohesion and strength. While wood may contain around 20–30% lignin, its abundance in aquatic and herbaceous angiosperms is generally less. In contrast to α-cellulose, lignin is an amorphous material with a randomly branched structure. This non-uniformity can make technical utilization challenging, as reactivity and availability of functional groups may vary [<a href="#B3" class="ref-link" data-ref-style="bibr">3</a>]. Still, some applications may benefit from polydispersity. For specialty chemicals such as surfactants, it is the function or the effect that counts. Salinity changes may induce precipitation of an ionic surfactant. If the surfactant is polydisperse, precipitation may be limited to only a fraction of it. The remaining surfactant can then still perform the desired function. Moreover, mixtures of dissimilar surfactants can form synergies, where the performance may be superior over its individual components [<a href="#B4" class="ref-link" data-ref-style="bibr">4</a>]. The application of lignin as specialty chemicals can thus benefit from its inherent characteristics, which includes its polydispersity. It is therefore not surprising that dispersants and surfactants are currently the dominant value-added applications of technical lignin.</p><p id="p4">It is frequently stated 50–70 million tons of technical lignin are produced per year, of which only 1–2% of are utilized for value-added products [<a href="#B5" class="ref-link" data-ref-style="bibr">5</a>]. The majority is burned for heat and chemicals recovery in Kraft mills [<a href="#B6" class="ref-link" data-ref-style="bibr">6</a>]. More than 1 million tons of lignosulfonates are produced annually [<a href="#B7" class="ref-link" data-ref-style="bibr">7</a>], hence dominating the market of technical lignin. In contrast to many other lignin products, lignosulfonates are readily water-soluble. Their most common application is dispersants [<a href="#B8" class="ref-link" data-ref-style="bibr">8</a>], for example as concrete plasticizers, drilling mud thinners, coal-slurry or dye dispersants [<a href="#B9" class="ref-link" data-ref-style="bibr">9</a>]. Roughly 50% of the annual production of lignosulfonates were used for concrete admixtures in 1999 [<a href="#B10" class="ref-link" data-ref-style="bibr">10</a>]. Other applications include dust binders, chelating and complexing agents, soil conditioning agents, floatation agents, and water-in-oil emulsion stabilizers [<a href="#B8" class="ref-link" data-ref-style="bibr">8</a>, <a href="#B9" class="ref-link" data-ref-style="bibr">9</a>, <a href="#B11" class="ref-link" data-ref-style="bibr">11</a>, <a href="#B12" class="ref-link" data-ref-style="bibr">12</a>]. As the effect on interfacial tension is limited, high shear is usually required during emulsification [<a href="#B13" class="ref-link" data-ref-style="bibr">13</a>]. Still, lignosulfonates can yield emulsions that are stable over months and longer, finding application for example in agrochemical formulations [<a href="#B8" class="ref-link" data-ref-style="bibr">8</a>]. Other potential areas with less commercial importance include corrosion and scale inhibitors, CO<sub>2</sub> flooding and enhanced oil recovery, as well as polymer precursors and additives [<a href="#B2" class="ref-link" data-ref-style="bibr">2</a>, <a href="#B14" class="ref-link" data-ref-style="bibr">14</a>, <a href="#B15" class="ref-link" data-ref-style="bibr">15</a>, <a href="#B16" class="ref-link" data-ref-style="bibr">16</a>, <a href="#B17" class="ref-link" data-ref-style="bibr">17</a>, <a href="#B18" class="ref-link" data-ref-style="bibr">18</a>, <a href="#B19" class="ref-link" data-ref-style="bibr">19</a>, <a href="#B20" class="ref-link" data-ref-style="bibr">20</a>].</p><p id="p5">Great importance is attributed to biopolymers these days, as they are inherently renewable and largely biodegradable. By substituting fossil-based polymers with biopolymers, the transition to more sustainable technologies is furthered. Expanding the use of lignosulfonates is therefore an important piece in the puzzle. Compared to the global production of surfactants or pulp and paper products, lignosulfonates are currently a niche application. There is hence a potential for growth, in particular for applications that involve liquid–liquid interfaces.</p></div><div class="section" id="sec_2" data-lvl="1"> <a href="https://ehealthcaresolutions.com/contact-us/" target="_blank" class="ads-link">Advertisement</a> <div id="video_ad_id_20000" class="ads"></div><h2 class="heading main-title">2. Fundamentals</h2><div class="section" id="sec_2_2" data-lvl="2"><h3 class="heading section-title">2.1 Definitions and distinctions</h3><p id="p6">The term <strong><bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">lignin</bold></strong> is used for the natural lignin as found in lignocellulosic biomass. It is also referred to as pristine lignin, as no treatment or modification has been done. Chemically speaking, lignin is a biopolymer consisting of the monolignol units sinapyl alcohol (S), coniferyl alcohol (G), and <em><italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">p</italic></em>-coumaryl alcohol (H) [<a href="#B21" class="ref-link" data-ref-style="bibr">21</a>], which are connected by various oxygen- and carbon–carbon linkages. Lignin has been described as a polyaromatic and randomly branched biopolymer.</p><p id="p7"><strong><bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">Technical lignin</bold></strong> refers to the lignin-rich product obtained from biomass separation processes. While pristine lignin is a virtually “infinite” network [<a href="#B22" class="ref-link" data-ref-style="bibr">22</a>], technical lignin is a fragmentated version thereof. The molecular weight, composition, and ratio of functional groups of technical lignin are hence different. Their abundance can be affected by parameters such as biomass feedstock, separation process, and purification steps. Technical lignin usually has a purity of at least 70% (Klason lignin + acid soluble lignin), with commercial products being closer to 85–100% of lignin per ash-free dry matter.</p><p id="p8"><strong><bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">Pulping</bold></strong> of lignocellulose biomass is conducted to obtain a fibrous material. Approximately 90% of the global pulp products are made from wood, whereas 10% originate from annual plants [<a href="#B1" class="ref-link" data-ref-style="bibr">1</a>]. Common end-products include paper, cardboard, molded pulp, and specialty cellulose. Mechanical pulping applies force in a refiner to defibrate the feedstock into fibers and fibrils. Chemical pulping dissolves the lignin and other substances to liberate the cellulose fibers. Industrial processes can also be based on a combination of mechanical and chemical treatments. Today, technical lignin most commonly originates from chemical pulping.</p><p id="p9">A <strong><bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">biorefinery</bold></strong> is defined as “the sustainable processing of biomass into a spectrum of marketable products (food, feed, materials, chemicals) and energy (fuels, power, heat)” [<a href="#B23" class="ref-link" data-ref-style="bibr">23</a>]. In other words, a biorefinery separates biomass into useful materials, chemicals, and energy. First generation biorefineries differ from second generation biorefineries by the choice of input material, i.e., food crops (first generation) instead of non-food crops (second generation) [<a href="#B24" class="ref-link" data-ref-style="bibr">24</a>]. Pulping of wood is thus defined as a lignocellulosic crop, second generation biorefinery.</p><p id="p10">An overview of existing <strong><bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">biomass separation processes</bold></strong> with the resulting lignin product is given in <a href="#F1" class="ref-link" data-ref-style="fig">Figure 1</a>. Technical lignin has traditionally been obtained by chemical pulping, i.e., Kraft, sulfite, or soda pulping. Organosolv pulping is a more recent invention, which utilizes organic solvents and often acid catalysis for delignification [<a href="#B26" class="ref-link" data-ref-style="bibr">26</a>]. The original goal of organosolv pulping was to obtain a fiber material. Still, this process has also attracted interest for biorefinery applications, which subsequently process the cellulose for chemical utilization [<a href="#B27" class="ref-link" data-ref-style="bibr">27</a>]. The production of technical lignin can hence be conducted as part of a pulping processes, but it is not limited to that. An example for a non-pulping type lignin would be hydrolysis lignin, which is produced in biorefinery sugar platforms. Here, the cellulose and hemicellulose are hydrolyzed to extract sugar monomers and oligomers. The sugar can further be converted to higher value products, for example ethanol or furfural. The residual solids are rich in lignin and therefore termed hydrolysis lignin. Residual cellulose and other impurities can impart poorer performance and hence lower value on this lignin type [<a href="#B3" class="ref-link" data-ref-style="bibr">3</a>, <a href="#B28" class="ref-link" data-ref-style="bibr">28</a>]. Still, recent developments have yielded increased purity and reactivity, e.g., the Cellunolix<sup>®</sup> lignin by St1 (Finnland) [<a href="#B29" class="ref-link" data-ref-style="bibr">29</a>] or the Lignova™ lignin by Fibenol (Estonia) [<a href="#B30" class="ref-link" data-ref-style="bibr">30</a>]. Because of these developments, it can be expected that hydrolysis lignin may play a larger role in the future. Steam explosion lignin is viewed as a separate category to hydrolysis lignin by some authors [<a href="#B3" class="ref-link" data-ref-style="bibr">3</a>, <a href="#B31" class="ref-link" data-ref-style="bibr">31</a>]. Yet, both lignin types are similar in composition and the treatments are sometimes even cascaded. Steam explosion treatment subjects the substrate to steam at elevated temperature (ca. 160–280°C) and pressure (ca. 7–48 bar) [<a href="#B32" class="ref-link" data-ref-style="bibr">32</a>]. This induces biomass disintegration and partial hydrolysis. Due to this, it will be considered as part of hydrolysis lignin, as shown in <a href="#F1" class="ref-link" data-ref-style="fig">Figure 1</a>. Hydrolysis lignins can further be subdivided into acid hydrolysis lignin and enzymatic hydrolysis lignin, with the latter being more reactive due to a lower degree of condensation [<a href="#B3" class="ref-link" data-ref-style="bibr">3</a>]. Recent advances have also yielded novel processes, which are still in an early stage of their development. Ionic liquids have been demonstrated to function as lignin solvents [<a href="#B33" class="ref-link" data-ref-style="bibr">33</a>]. Combined with other treatments, ionic liquids can yield new products and conversion routes with promising features; however, some economic and technical challenges still need to be addressed [<a href="#B34" class="ref-link" data-ref-style="bibr">34</a>]. Another recent invention is the use of supercritical solvents, e.g., supercritical water yielding products such as Aquasolv lignin [<a href="#B35" class="ref-link" data-ref-style="bibr">35</a>].</p><figure class="media-panel" id="F1"><div class="media"><img src="//cdnintech.com/media/chapter/83868/1680680847/media/F1.png" class="figure-link" alt=""></div><figcaption class="caption"><h4>Figure 1.</h4><p><p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" id="p11">Lignin extraction processes and their dominant products. Modified from Laurichesse and Avérous [<xref rid="B25" ref-type="bibr">25</xref>].</p></p></figcaption></figure><p id="p12"><strong><bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">Lignosulfonates</bold></strong> are traditionally extracted from sulfite spent liquors. Sulfite pulping is usually operated at low pH, but neutral or alkaline sulfite pulping have also been developed [<a href="#B1" class="ref-link" data-ref-style="bibr">1</a>]. Sulfite liquors typically contain about 50–80% lignosulfonates, 30% hemicellulose and 10% inorganics per dry matter content [<a href="#B5" class="ref-link" data-ref-style="bibr">5</a>]. Purification is often conducted by membrane filtration, removing low molecular weight components such as sugars. Commercial grade lignosulfonates are available in both purified and unpurified qualities. As a result of the pulping conditions, they also tend to exhibit a higher degree of condensation than, e.g., soda or organosolv lignin [<a href="#B3" class="ref-link" data-ref-style="bibr">3</a>].</p><p id="p13"><strong><bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">Sulfonated lignin</bold></strong> is produced by chemical modification of lignin separated by a process other than sulfite pulping [<a href="#B2" class="ref-link" data-ref-style="bibr">2</a>]. For example, MeadWestvaco produces Kraft lignin sulfonated with sulfite salts and an aldehyde, e.g., formaldehyde [<a href="#B5" class="ref-link" data-ref-style="bibr">5</a>]. A variety of modification processes exist and the differences between lignosulfonates and sulfonated lignin can be marginal.</p><p id="p14">The <strong><bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">counterion</bold></strong> is the ion accompanying a second ionic species to maintain charge neutrality. Lignosulfonates contain covalently bond anionic moieties, which most importantly include sulfonate and carboxyl groups. A counter ion with positive charge is hence necessary for charge neutrality. This counterion is frequently a remnant of the pulping process, i.e., pulping with sodium, calcium or magnesium bisulfite will yield sodium, calcium, or magnesium lignosulfonates, respectively. Ion-exchange may also be conducted to replace the counterion. Protonation is furthermore possible, i.e., hydrogen as the counter ion. However, lignosulfonate dispersants are usually the salt of lignosulfonic acid, as this yields a more moderate pH and improves water-solubility.</p><p id="p15">A <strong><bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">surfactant</bold></strong>, i.e., surface-active agent, is a compound that can lower the surface or interfacial tension of a liquid in contact with another phase [<a href="#B36" class="ref-link" data-ref-style="bibr">36</a>]. This effect is usually accompanied by adsorption at the surface or interface, i.e., enrichment at the phase boundary [<a href="#B37" class="ref-link" data-ref-style="bibr">37</a>]. Surfactants usually contain hydrophilic and lipophilic moieties, which facilitate interfacial adsorption. Lignosulfonates have been shown to reduce the surface tension of water [<a href="#B38" class="ref-link" data-ref-style="bibr">38</a>] and can hence be classified as surfactants.</p><p id="p16"><strong><bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">Surface tension</bold></strong> can be observed as the tendency of a liquid surface to assume the smallest possible surface area. It is linked to the intermolecular attraction forces within the liquid and is commonly denoted as force per unit length or energy per unit area. Dispersing a liquid with high surface tension hence requires more energy than dispersing a liquid with low surface tension. In this chapter, the surface tension will be used when discussing liquid–gas phase boundaries.</p><p id="p17">The <strong><bold xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">interfacial tension</bold></strong> is the equivalent to the surface tension at liquid–liquid interfaces. A system with low interfacial tension requires less work for emulsification than a system with high interfacial tension.</p></div><div class="section" id="sec_3_2" data-lvl="2"><h3 class="heading section-title">2.2 Production</h3><p id="p18">Lignosulfonates are produced as a by-product during sulfite pulping of wood [<a href="#B1" class="ref-link" data-ref-style="bibr">1</a>]. Sulfite pulping is a long-established method for producing cellulosic fibers [<a href="#B39" class="ref-link" data-ref-style="bibr">39</a>]. The process usually operates at low pH, utilizing sulfite or bisulfite salts to soften and remove the lignin. The lignin undergoes a number of reactions, which include [<a href="#B1" class="ref-link" data-ref-style="bibr">1</a>]:<ul><li><p id="p19">Hydrolysis</p></li><li><p id="p20">Sulfonation</p></li><li><p id="p21">Sulfitolysis</p></li><li><p id="p22">Dissolution</p></li><li><p id="p23">Degradation</p></li><li><p id="p24">Condensation</p></li></ul></p><p id="p25">During hydrolysis, the lignin-carbohydrate and, to a smaller extent, lignin-lignin linkages are broken down [<a href="#B1" class="ref-link" data-ref-style="bibr">1</a>]. Sulfonation introduces sulfonate groups onto the lignin. When present in sufficient amounts, the sulfonate groups render the lignin water-soluble, which facilitates dissolution in the cooking liquor. Sulfitolysis and degradation may further reduce the molecular weight, whereas condensation reactions increase it. Condensation counteracts delignification by forming new carbon–carbon bonds [<a href="#B1" class="ref-link" data-ref-style="bibr">1</a>].</p><p id="p26">Natural lignin is synthesized from the three monolignols, i.e., sinapyl alcohol (S), coniferyl alcohol (G), and p-coumaryl alcohol (H) units [<a href="#B21" class="ref-link" data-ref-style="bibr">21</a>]. Coniferous lignin (softwood lignin) is composed mainly of G-units, whereas lignin from broad-leaved trees (hardwood lignin) contains a mixture of G- and S-units [<a href="#B40" class="ref-link" data-ref-style="bibr">40</a>]. Lignin from annual plants also contains H-units in addition to G- and S-units [<a href="#B41" class="ref-link" data-ref-style="bibr">41</a>]. The feedstock therefore affects the composition of the resulting lignosulfonates, as the three monolignols vary in their methoxy content and potential branching. The feedstock can furthermore affect the pulping process, since sulfonation of hardwood lignin is slower than of softwood lignin [<a href="#B1" class="ref-link" data-ref-style="bibr">1</a>]. Moreover, softwood lignin is more prone to condensation reactions, resulting in higher molecular weight as compared to hardwood lignosulfonates [<a href="#B42" class="ref-link" data-ref-style="bibr">42</a>]. An overview of the monolignols and a schematic of softwood lignin is given in <a href="#F2" class="ref-link" data-ref-style="fig">Figure 2</a>.</p><figure class="media-panel" id="F2"><div class="media"><img src="//cdnintech.com/media/chapter/83868/1680680847/media/F2.png" class="figure-link" alt=""></div><figcaption class="caption"><h4>Figure 2.</h4><p><p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" id="p27">Primary lignin monomers and their corresponding units (left) [<xref rid="B25" ref-type="bibr">25</xref>]. Schematic structure of softwood lignin (right) [<xref rid="B43" ref-type="bibr">43</xref>].</p></p></figcaption></figure><p id="p28">While alkali lignin can be separated by acid precipitation, this approach is not feasible for lignosulfonates. Instead, membrane filtration (ultrafiltration) is often conducted to purify the sulfite liquor [<a href="#B5" class="ref-link" data-ref-style="bibr">5</a>]. Challenges can arise due to overlapping molecular weight of the lignosulfonates and dissolved hemicellulose. One approach is to cascade a series of membranes with different cut-off molecular weights [<a href="#B44" class="ref-link" data-ref-style="bibr">44</a>]. An alternative is given by the Howard process [<a href="#B5" class="ref-link" data-ref-style="bibr">5</a>], which uses lime (calcium oxide) to precipitate the lignosulfonate above pH 12 [<a href="#B45" class="ref-link" data-ref-style="bibr">45</a>]. The precipitated solids can be separated mechanically and washed to improve the purity. Other potential approaches include amine extraction, electrolysis, ion-exchange resins, the Pekilo process (fermentation and ultrafiltration), and reverse osmosis [<a href="#B5" class="ref-link" data-ref-style="bibr">5</a>].</p><p id="p29">Several factors affect the composition of lignosulfonates, which include but are not limited to:<ul><li><p id="p30">The choice of raw material, e.g., softwood or hardwood, affecting the monolignol composition</p></li><li><p id="p31">The choice of pulping chemicals</p></li><li><p id="p32">The pulping conditions</p></li><li><p id="p33">Recovery and purification</p></li><li><p id="p34">Post-treatment and chemical modification</p></li></ul></p><p id="p35">The composition of lignosulfonates is inherently linked to its characteristics and behavior, and hence to the performance in technical applications [<a href="#B2" class="ref-link" data-ref-style="bibr">2</a>].</p></div><div class="section" id="sec_4_2" data-lvl="2"><h3 class="heading section-title">2.3 Structure and composition</h3><p id="p36">As discussed in the previous chapter, the structure and composition of lignosulfonates is strongly dependent on their origin and production. Still, there are certain characteristics that are worth discussing.</p><p id="p37">Due to their structure and monomeric configuration, cellulose and hemicellulose contain a higher percentage of oxygen than lignin. Lignin furthermore has the highest carbon content of these three biopolymers. A unique feature of lignosulfonates is their elevated sulfur content, which arises from the pulping process. <a href="#tab1" class="ref-link" data-ref-style="table">Table 1</a> lists a range of elementary composition, as published in current literature. It should be mentioned that these values should only be taken as indicators, since individual samples may be different. In particular, the ash content may exhibit values up to 40 wt.%. Still, an elevated oxygen content and lower carbon content can in theory indicate lower purity, as the contributions from cellulose and hemicellulose would be greater.</p><div class="table-wrap" id="tab1"><div class="table-content"><table frame="hsides" rules="groups"><col><col><col><thead><tr><th>Parameter</th><th align="center">Approximate content in wt.%</th><th align="center">Reference</th></tr></thead><tbody><tr><td>Dry matter</td><td align="center">94–96</td><td align="center">[<a href="#B46" class="ref-link" data-ref-style="bibr">46</a>]</td></tr><tr><td>Ash</td><td align="center">4–10</td><td align="center">[<a href="#B3" class="ref-link" data-ref-style="bibr">3</a>, <a href="#B47" class="ref-link" data-ref-style="bibr">47</a>]</td></tr><tr><td>Carbon</td><td align="center">29–47</td><td align="center">[<a href="#B48" class="ref-link" data-ref-style="bibr">48</a>, <a href="#B49" class="ref-link" data-ref-style="bibr">49</a>, <a href="#B50" class="ref-link" data-ref-style="bibr">50</a>]</td></tr><tr><td>Hydrogen</td><td align="center">5</td><td align="center">[<a href="#B48" class="ref-link" data-ref-style="bibr">48</a>, <a href="#B50" class="ref-link" data-ref-style="bibr">50</a>]</td></tr><tr><td>Oxygen</td><td align="center">37–54</td><td align="center">[<a href="#B48" class="ref-link" data-ref-style="bibr">48</a>, <a href="#B49" class="ref-link" data-ref-style="bibr">49</a>, <a href="#B50" class="ref-link" data-ref-style="bibr">50</a>]</td></tr><tr><td>Sulfur</td><td align="center">2–10</td><td align="center">[<a href="#B46" class="ref-link" data-ref-style="bibr">46</a>]</td></tr><tr><td>Nitrogen</td><td align="center">0.02</td><td align="center">[<a href="#B3" class="ref-link" data-ref-style="bibr">3</a>]</td></tr></tbody></table></div><div class="table-caption"><h3 class="heading">Table 1.</h3><div class="text"><p id="p38">Approximate elementary composition of lignosulfonates.</p></div><div class="text"></div></div></div><p id="p39">The chemical structure of lignosulfonates mirrors that of both native lignin and the modifications done during sulfite pulping. As such, the skeletal configuration of lignin is preserved to some extent, while new carbon–carbon linkages have been formed. In addition, sulfonate and carboxylic acid groups were added, which are not found in native lignin to this extent. Generic structure models of lignosulfonates are shown in <a href="#F3" class="ref-link" data-ref-style="fig">Figure 3</a>. It is important to note that these are only approximate models, as lignosulfonates are a polydisperse mixture of many different macromolecules. The structure hence varies not only between different lignosulfonates, but also within a given sample. In other words, lignosulfonates should be considered statistical entities rather than classical chemical compounds [<a href="#B53" class="ref-link" data-ref-style="bibr">53</a>].</p><figure class="media-panel" id="F3"><div class="media"><img src="//cdnintech.com/media/chapter/83868/1680680847/media/F3.png" class="figure-link" alt=""></div><figcaption class="caption"><h4>Figure 3.</h4><p><p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" id="p40">Generic (simplified) structure of lignosulfonates according to Kun and Pukanszky [<xref rid="B51" ref-type="bibr">51</xref>] (left), and Fiorani et al. [<xref rid="B52" ref-type="bibr">52</xref>] (right).</p></p></figcaption></figure><p id="p41">The chemical moieties of lignosulfonates can be categorized into ionizable, polar and non-polar groups [<a href="#B2" class="ref-link" data-ref-style="bibr">2</a>]. Ionizable groups include sulfonate, carboxylic acid, and phenolic hydroxyl groups. At a neutral pH of 7, mainly the first two can be considered dissociated (ionized) and hence hydrophilic. Phenolic hydroxyl groups are usually ionized at around pH 9–10 [<a href="#B54" class="ref-link" data-ref-style="bibr">54</a>, <a href="#B55" class="ref-link" data-ref-style="bibr">55</a>], but values extending to pH 5–12 have been reported [<a href="#B56" class="ref-link" data-ref-style="bibr">56</a>]. Polar groups include various oxygen containing moieties due to the higher dipole moment of oxygen–carbon and oxygen-hydrogen linkages. These include ketones, aldehydes, and methoxy groups. Despite being polar, these groups are not considered operative hydrophilic groups [<a href="#B57" class="ref-link" data-ref-style="bibr">57</a>]. Aliphatic hydroxyl and ether groups are also present to a great extent in lignosulfonates. These can be intrinsically hydrophilic; however, their functionality is determined by the surrounding molecular structure [<a href="#B57" class="ref-link" data-ref-style="bibr">57</a>, <a href="#B58" class="ref-link" data-ref-style="bibr">58</a>, <a href="#B59" class="ref-link" data-ref-style="bibr">59</a>]. Because of this, the water-solubility of lignosulfonates arises from the presence of ionizable groups, i.e., sulfonate and carboxyl groups at neutral pH. Nonpolar groups include aromatic and aliphatic units, as found in the skeletal configuration of lignin. An overview of the common functional groups and linkages is given in <a href="#F4" class="ref-link" data-ref-style="fig">Figure 4</a>. This overview does not include additional functionalities, which may be grafted onto the lignosulfonates, e.g., by phosphorylation, alkylation, sulfobutylation or silylation [<a href="#B60" class="ref-link" data-ref-style="bibr">60</a>].</p><figure class="media-panel" id="F4"><div class="media"><img src="//cdnintech.com/media/chapter/83868/1680680847/media/F4.png" class="figure-link" alt=""></div><figcaption class="caption"><h4>Figure 4.</h4><p><p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" id="p42">Commonly encountered chemical bounds and functional groups in technical lignin. Image taken from [<xref rid="B2" ref-type="bibr">2</xref>].</p></p></figcaption></figure><p id="p43">The abundance of functional groups can be of interest for two reasons. Firstly, this is an important parameter for chemical modification, as specific functional groups may be targeted. Secondly, the physicochemical properties of lignosulfonates are highly dependent on their composition. Hydrophobic interaction chromatography (HIC) has played an important role in characterizing lignosulfonates recently [<a href="#B61" class="ref-link" data-ref-style="bibr">61</a>, <a href="#B62" class="ref-link" data-ref-style="bibr">62</a>, <a href="#B63" class="ref-link" data-ref-style="bibr">63</a>]. Based on this technique, the charge-to-size ratio was reportedly lower for more hydrophobic lignosulfonates [<a href="#B64" class="ref-link" data-ref-style="bibr">64</a>]. Better performance as suspension or emulsion stabilizer was furthermore seen for more hydrophobic lignosulfonates [<a href="#B13" class="ref-link" data-ref-style="bibr">13</a>, <a href="#B63" class="ref-link" data-ref-style="bibr">63</a>]. This example illustrates, how the abundance of functional groups may impact the performance in technical applications.</p><p id="p44">Compared to other technical lignins, lignosulfonates tend to exhibit a lower amount of phenolic hydroxyl groups [<a href="#B47" class="ref-link" data-ref-style="bibr">47</a>]. While the sulfonate group is a distinct feature of lignosulfonates, the abundance of carboxylic acid groups is comparable to that of other technical lignins. A recent study was performed aqueous carbon black dispersions stabilized by sodium lignosulfonate, which also listed the composition of six commercial samples [<a href="#B46" class="ref-link" data-ref-style="bibr">46</a>]. The values are summarized in <a href="#tab2" class="ref-link" data-ref-style="table">Table 2</a>. As all samples were of softwood origin, a higher methoxy content can be expected for hardwood lignosulfonates due to the monolignol composition.</p><div class="table-wrap" id="tab2"><div class="table-content"><table frame="hsides" rules="groups"><col><col><thead><tr><th>Parameter</th><th align="center">Approximate range</th></tr></thead><tbody><tr><td>M<sub>w</sub> in g/mol</td><td align="center">1800–4000</td></tr><tr><td>M<sub>n</sub> in g/mol</td><td align="center">6000–330,000</td></tr><tr><td>Polydispersity index</td><td align="center">3–83</td></tr><tr><td>Organic sulfur (wt.%)</td><td align="center">2.1–9.4</td></tr><tr><td>Carboxyl groups (wt.%)</td><td align="center">8.3–14.9</td></tr><tr><td>Phenolic hydroxyl groups (wt.%)</td><td align="center">1.3–2.0</td></tr><tr><td>Methoxy groups (wt.%)</td><td align="center">7.3–15.4</td></tr></tbody></table></div><div class="table-caption"><h3 class="heading">Table 2.</h3><div class="text"><p id="p45">Abundance of functional groups of softwood sodium lignosulfonates according to Subramanian et al. [<a href="#B46" class="ref-link" data-ref-style="bibr">46</a>].</p></div><div class="text"></div></div></div><p id="p46"><a href="#tab2" class="ref-link" data-ref-style="table">Table 2</a> also lists the number-average (M<sub>n</sub>) and mass-average molecular weight (M<sub>w</sub>). A polydispersity index of up to 83 accounts for a great variety in molecular mass, which is characteristic for lignin from sulfite pulping. The molecular weight can have several implications on the properties of lignosulfonates. It is naturally linked to the diffusion coefficient [<a href="#B65" class="ref-link" data-ref-style="bibr">65</a>], which will further affect interfacial adsorption and related phenomena [<a href="#B13" class="ref-link" data-ref-style="bibr">13</a>, <a href="#B66" class="ref-link" data-ref-style="bibr">66</a>]. Research has shown that the degree of sulfonation decreases with increasing molecular weight [<a href="#B67" class="ref-link" data-ref-style="bibr">67</a>]. Stearic screening can occur in lignosulfonates with high molecular weight [<a href="#B3" class="ref-link" data-ref-style="bibr">3</a>]. This effect was used to explain, e.g., the lower effect on zeta potential by shielding ionizable groups [<a href="#B68" class="ref-link" data-ref-style="bibr">68</a>] or the lower reactivity by screening of phenolic hydroxyl groups [<a href="#B3" class="ref-link" data-ref-style="bibr">3</a>]. Overall, the molecular weight of lignosulfonates may span from less than 1000 g/mol to more than 400,000 g/mol [<a href="#B42" class="ref-link" data-ref-style="bibr">42</a>, <a href="#B67" class="ref-link" data-ref-style="bibr">67</a>]. The molecular weight ranges are thus higher than for other technical lignins [<a href="#B2" class="ref-link" data-ref-style="bibr">2</a>]. In comparison, values of (1000–15,000 g/mol) have been reported for soda lignin, 1500–25,000 g/mol for Kraft lignin, and 500–5000 g/mol for organosolv lignin [<a href="#B3" class="ref-link" data-ref-style="bibr">3</a>]. Acid hydrolysis lignin is closer to lignosulfonates in terms of molecular weight, where values of 1500–50,000 g/mol have been reported [<a href="#B69" class="ref-link" data-ref-style="bibr">69</a>]. The molecular weight distribution of various lignosulfonates is illustrated in <a href="#F5" class="ref-link" data-ref-style="fig">Figure 5</a>. As can be seen, the molecular weight of the hardwood samples was consistently lower than that of softwood lignosulfonates. This difference is likely the result of the monolignol configuration, which can further affect the sulfite pulping process.</p><figure class="media-panel" id="F5"><div class="media"><img src="//cdnintech.com/media/chapter/83868/1680680847/media/F5.png" class="figure-link" alt=""></div><figcaption class="caption"><h4>Figure 5.</h4><p><p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" id="p47">Molecular weight distribution of lignosulfonates originating from spruce [LS1 (&diams;), LS2 (▀) and LS3 (+)], a spruce-birch blend [LS5 (▲)], aspen [LS6 (*)], and eucalyptus [LS7 (●) and LS8 (×)]. Image taken from [<xref rid="B42" ref-type="bibr">42</xref>].</p></p></figcaption></figure></div></div><div class="section" id="sec_6" data-lvl="1"> <a href="https://ehealthcaresolutions.com/contact-us/" target="_blank" class="ads-link">Advertisement</a> <div id="intechopen-intechopen-3" class="ads"></div><h2 class="heading main-title">3. Adsorption on surfaces and interfaces</h2><div class="section" id="sec_6_2" data-lvl="2"><h3 class="heading section-title">3.1 Adsorption</h3><p id="p48">It is generally agreed that adsorption of lignosulfonates follows the Langmuir isotherm [<a href="#B70" class="ref-link" data-ref-style="bibr">70</a>, <a href="#B71" class="ref-link" data-ref-style="bibr">71</a>, <a href="#B72" class="ref-link" data-ref-style="bibr">72</a>, <a href="#B73" class="ref-link" data-ref-style="bibr">73</a>]. The according framework was first published by Irving Langmuir in 1916, which described the adsorption of gasses on solids [<a href="#B74" class="ref-link" data-ref-style="bibr">74</a>]. A common expression of the Langmuir equation is given in <a href="#E1" class="ref-link" data-ref-style="disp-formula">Eq. (1)</a>, were <span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m1"><mml:mi mathvariant="normal">Γ</mml:mi></mml:math></span> corresponds to the amount of adsorbed species, <span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m2"><mml:msub><mml:mi mathvariant="normal">Γ</mml:mi><mml:mi>max</mml:mi></mml:msub></mml:math></span> is the maximum amount adsorbed, <span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m3"><mml:mi>c</mml:mi></mml:math></span> is the concentration of adsorbing species in bulk, and <span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m4"><mml:mi>K</mml:mi></mml:math></span> is the Langmuir equilibrium constant.</p><div id="df_E1" class="formula panel"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m5" specific-use="web-only"><mml:mi mathvariant="normal">Γ</mml:mi><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:msub><mml:mi mathvariant="normal">Γ</mml:mi><mml:mi>max</mml:mi></mml:msub><mml:mi mathvariant="italic">Kc</mml:mi></mml:mrow><mml:mrow><mml:mn>1</mml:mn><mml:mo>+</mml:mo><mml:mi mathvariant="italic">Kc</mml:mi></mml:mrow></mml:mfrac></mml:math><span class="equ">E1</span></div><p id="p49">The parameters <span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m6"><mml:msub><mml:mi mathvariant="normal">Γ</mml:mi><mml:mi>max</mml:mi></mml:msub></mml:math></span> and <span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m7"><mml:mi>K</mml:mi></mml:math></span> can be determined via mass-balancing, i.e., measuring the adsorbed amount in dependence of concentration. This approach is simple for adsorption on solid surfaces, as the amount of non-adsorbing surfactant is equivalent to the remaining bulk concentration. An example for the adsorption of lignosulfonates on carbon black is given in <a href="#F6" class="ref-link" data-ref-style="fig">Figure 6</a>. The characteristic behavior accompanying Langmuir adsorption isotherms is a sharp increase of adsorbed amount at low concentrations, whereas higher concentrations yield a plateau.</p><figure class="media-panel" id="F6"><div class="media"><img src="//cdnintech.com/media/chapter/83868/1680680847/media/F6.png" class="figure-link" alt=""></div><figcaption class="caption"><h4>Figure 6.</h4><p><p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" id="p50">Adsorption isotherm of lignosulfonate on 1 wt% carbon black along with Langmuir isotherm fitting. Image taken from [<xref rid="B46" ref-type="bibr">46</xref>].</p></p></figcaption></figure><p id="p51">Determination of the Langmuir equation parameters to liquid–liquid systems is less straight forward than for liquid–solid dispersions. Emulsification is accompanied by an increase in specific surface area, which can be difficult to quantify. The surface or interfacial tension can be used instead of mass-balancing. Langmuir type adsorption implies the applicability of the Szyszkowski equation, as given in <a href="#E2" class="ref-link" data-ref-style="disp-formula">Eq. (2)</a>. Here, the surface pressure <span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m8"><mml:mi mathvariant="normal">Π</mml:mi></mml:math></span> is calculated as the difference of surface or interfacial tension without surfactant (<span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m9"><mml:msub><mml:mi>γ</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:math></span>) and at concentration <span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m10"><mml:mi>c</mml:mi></mml:math></span> (<span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m11"><mml:mi>γ</mml:mi><mml:mfenced open="(" close=")"><mml:mi>c</mml:mi></mml:mfenced></mml:math></span>). The equation further involves the temperature <span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m12"><mml:mi>T</mml:mi></mml:math></span>, the ideal gas constant <span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m13"><mml:mi>R</mml:mi></mml:math></span>, and the constant <span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m14"><mml:mi>n</mml:mi></mml:math></span>.</p><div id="df_E2" class="formula panel"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m15" specific-use="web-only"><mml:mi mathvariant="normal">Π</mml:mi><mml:mo>=</mml:mo><mml:msub><mml:mi>γ</mml:mi><mml:mn>0</mml:mn></mml:msub><mml:mo>−</mml:mo><mml:mi>γ</mml:mi><mml:mfenced open="(" close=")"><mml:mi>c</mml:mi></mml:mfenced><mml:mo>=</mml:mo><mml:mi>n</mml:mi><mml:mi>RT</mml:mi><mml:msub><mml:mi mathvariant="normal">Γ</mml:mi><mml:mi>m</mml:mi></mml:msub><mml:mo>ln</mml:mo><mml:mfenced open="(" close=")"><mml:mrow><mml:mn>1</mml:mn><mml:mo>+</mml:mo><mml:mi mathvariant="italic">Kc</mml:mi></mml:mrow></mml:mfenced></mml:math><span class="equ">E2</span></div><p id="p52">The surface excess <span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m16"><mml:msub><mml:mi mathvariant="normal">Γ</mml:mi><mml:mi>m</mml:mi></mml:msub></mml:math></span> can further be determined using the Gibbs adsorption isotherm. As stated in <a href="#E3" class="ref-link" data-ref-style="disp-formula">Eq. (3)</a>, this framework relies on the linear-logarithmic progression of surface tension <span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m17"><mml:mi>γ</mml:mi></mml:math></span> with concentration <span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m18"><mml:mi>c</mml:mi></mml:math></span>. It is important to note that the linear-logarithmic regime does not span over the entire concentration range. At low surfactant concentrations, the surface or interfacial tension approaches the surfactant-free case <span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m19"><mml:msub><mml:mi>γ</mml:mi><mml:mn>0</mml:mn></mml:msub></mml:math></span> asymptotically. At high lignosulfonate concentrations, agglomeration and other effects will decrease the observed slope [<a href="#B38" class="ref-link" data-ref-style="bibr">38</a>, <a href="#B75" class="ref-link" data-ref-style="bibr">75</a>]. A more detailed discussion of the surface and interfacial tension of lignosulfonates is given in Section 3.2.</p><div id="df_E3" class="formula panel"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m20" specific-use="web-only"><mml:msub><mml:mi mathvariant="normal">Γ</mml:mi><mml:mi>m</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:mo>−</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mrow><mml:mi>n</mml:mi><mml:mi>RT</mml:mi></mml:mrow></mml:mfrac><mml:mfenced open="(" close=")"><mml:mfrac><mml:mrow><mml:mi>∂</mml:mi><mml:mi>γ</mml:mi></mml:mrow><mml:mrow><mml:mi>∂</mml:mi><mml:mo>ln</mml:mo><mml:mi>c</mml:mi></mml:mrow></mml:mfrac></mml:mfenced></mml:math><span class="equ">E3</span></div><p id="p53">Assumptions can furthermore be made to determine the constant <span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m21"><mml:mi>n</mml:mi></mml:math></span>. In case of strong surfactant electrolytes, such as <span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m22"><mml:mi>R</mml:mi><mml:mo>−</mml:mo><mml:mi>O</mml:mi><mml:mo>−</mml:mo><mml:mi>S</mml:mi><mml:msubsup><mml:mi>O</mml:mi><mml:mn>3</mml:mn><mml:mo>−</mml:mo></mml:msubsup><mml:msup><mml:mi mathvariant="italic">Na</mml:mi><mml:mo>+</mml:mo></mml:msup></mml:math></span>, both the surfactant ion and the counterion must absorb, yielding a value of <span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m23"><mml:mi>n</mml:mi><mml:mo>=</mml:mo><mml:mn>2</mml:mn></mml:math></span> [<a href="#B76" class="ref-link" data-ref-style="bibr">76</a>]. A value of <span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m24"><mml:mi>n</mml:mi><mml:mo>=</mml:mo><mml:mn>1</mml:mn></mml:math></span> corresponds to non-ionic surfactants or ionic surfactants in presence of high concentrations of an indifferent electrolyte, such as NaCl. Both assumptions have been applied to lignosulfonates and were found to yield conclusive results [<a href="#B13" class="ref-link" data-ref-style="bibr">13</a>, <a href="#B66" class="ref-link" data-ref-style="bibr">66</a>].</p><p id="p54">By applying the above framework, other information can also be extracted from surface and interfacial tension measurements. For example, the surface excess <span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m25"><mml:msub><mml:mi mathvariant="normal">Γ</mml:mi><mml:mi>m</mml:mi></mml:msub></mml:math></span> can be used to calculate the area per molecule, as stated in <a href="#E4" class="ref-link" data-ref-style="disp-formula">Eq. (4)</a> [<a href="#B76" class="ref-link" data-ref-style="bibr">76</a>]. Here, <span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m26"><mml:msub><mml:mi>N</mml:mi><mml:mi>av</mml:mi></mml:msub></mml:math></span> denotes the Avogadro’s constant <span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m27"><mml:mn>6.022</mml:mn><mml:mo>×</mml:mo><mml:msup><mml:mn>10</mml:mn><mml:mn>23</mml:mn></mml:msup><mml:mspace width="0.25em"></mml:mspace><mml:mi>mo</mml:mi><mml:msup><mml:mi mathvariant="normal">l</mml:mi><mml:mrow><mml:mo>−</mml:mo><mml:mn>1</mml:mn></mml:mrow></mml:msup></mml:math></span>.</p><div id="df_E4" class="formula panel"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m28" specific-use="web-only"><mml:msub><mml:mi mathvariant="normal">A</mml:mi><mml:mi mathvariant="normal">m</mml:mi></mml:msub><mml:mo>=</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mrow><mml:msub><mml:mi mathvariant="normal">Γ</mml:mi><mml:mi>m</mml:mi></mml:msub><mml:msub><mml:mi>N</mml:mi><mml:mi>av</mml:mi></mml:msub></mml:mrow></mml:mfrac></mml:math><span class="equ">E4</span></div><p id="p55">Several authors have studied the adsorption kinetics of lignosulfonates on solid surfaces [<a href="#B71" class="ref-link" data-ref-style="bibr">71</a>, <a href="#B72" class="ref-link" data-ref-style="bibr">72</a>, <a href="#B77" class="ref-link" data-ref-style="bibr">77</a>, <a href="#B78" class="ref-link" data-ref-style="bibr">78</a>, <a href="#B79" class="ref-link" data-ref-style="bibr">79</a>, <a href="#B80" class="ref-link" data-ref-style="bibr">80</a>]. The reports generally agree that pseudo second-order kinetics provided the best fit. Such kinetic can be expressed as written in <a href="#E5" class="ref-link" data-ref-style="disp-formula">Eq. (5)</a>, where <span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m29"><mml:msub><mml:mi>q</mml:mi><mml:mi>t</mml:mi></mml:msub></mml:math></span> is the adsorbed amount at time <span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m30"><mml:mi>t</mml:mi></mml:math></span>, <span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m31"><mml:msub><mml:mi>q</mml:mi><mml:mi>e</mml:mi></mml:msub></mml:math></span> is the amount adsorbed at equilibrium, and <span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m32"><mml:mi>k</mml:mi></mml:math></span> is the rate constant.</p><div id="df_E5" class="formula panel"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m33" specific-use="web-only"><mml:mfrac><mml:mi mathvariant="normal">t</mml:mi><mml:msub><mml:mi mathvariant="normal">q</mml:mi><mml:mi mathvariant="normal">t</mml:mi></mml:msub></mml:mfrac><mml:mo>=</mml:mo><mml:mfrac><mml:mn>1</mml:mn><mml:mrow><mml:mi>k</mml:mi><mml:msubsup><mml:mi>q</mml:mi><mml:mi>e</mml:mi><mml:mn>2</mml:mn></mml:msubsup></mml:mrow></mml:mfrac><mml:mo>+</mml:mo><mml:mfrac><mml:mi>t</mml:mi><mml:msub><mml:mi>q</mml:mi><mml:mi>e</mml:mi></mml:msub></mml:mfrac></mml:math><span class="equ">E5</span></div><p id="p56"><a href="#E5" class="ref-link" data-ref-style="disp-formula">Eq. (5)</a> can be fitted to experimental data by plotting <span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m34"><mml:mfrac><mml:mi>t</mml:mi><mml:msub><mml:mi>q</mml:mi><mml:mi>t</mml:mi></mml:msub></mml:mfrac></mml:math></span> against <span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m35"><mml:mi>t</mml:mi></mml:math></span>, yielding <span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m36"><mml:mfrac><mml:mn>1</mml:mn><mml:msub><mml:mi>q</mml:mi><mml:mi>e</mml:mi></mml:msub></mml:mfrac></mml:math></span> as the slope and <span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m37"><mml:mfrac><mml:mn>1</mml:mn><mml:mrow><mml:mi>k</mml:mi><mml:msubsup><mml:mi>q</mml:mi><mml:mi>e</mml:mi><mml:mn>2</mml:mn></mml:msubsup></mml:mrow></mml:mfrac></mml:math></span> as the intersection. This model is, however, limited to adsorption from liquid onto solid phase. Kinetic modeling of lignosulfonate adsorption at liquid–liquid interfaces has also been attempted; yet, the results indicated that water–oil adsorption was not diffusion-controlled [<a href="#B66" class="ref-link" data-ref-style="bibr">66</a>]. It usually takes hours or days to attain an equilibrium state at the liquid-air or liquid–liquid interface [<a href="#B66" class="ref-link" data-ref-style="bibr">66</a>, <a href="#B81" class="ref-link" data-ref-style="bibr">81</a>, <a href="#B82" class="ref-link" data-ref-style="bibr">82</a>]. This time span is greater than for simple monodisperse surfactants. Different explanations have been given for this behavior. The lignosulfonate can undergo diffusion exchange at the interface, replacing molecules with a lower diffusion coefficient but higher effect on interfacial tension. In addition, the individual macromolecules may be subject to rearrangement, both with respect to the interface and to each other [<a href="#B2" class="ref-link" data-ref-style="bibr">2</a>]. Such realignment of conformation has been described, e.g., for petroleum asphaltenes [<a href="#B83" class="ref-link" data-ref-style="bibr">83</a>, <a href="#B84" class="ref-link" data-ref-style="bibr">84</a>]. Both lignosulfonates and asphaltenes share common characteristics, e.g., both are polybranched, exhibit a tendency for self-association, and require overnight storage, as the emulsions would be less stable if processed immediately after emulsification [<a href="#B13" class="ref-link" data-ref-style="bibr">13</a>, <a href="#B85" class="ref-link" data-ref-style="bibr">85</a>]. Analogies have therefore been drawn between these two species in terms of their interfacial behavior [<a href="#B2" class="ref-link" data-ref-style="bibr">2</a>, <a href="#B66" class="ref-link" data-ref-style="bibr">66</a>].</p></div><div class="section" id="sec_7_2" data-lvl="2"><h3 class="heading section-title">3.2 Effect on surface and interfacial tension</h3><p id="p57">Measuring surface tension is a useful tool, e.g., for assessing the behavior of lignosulfonates in solution or their interactions with other components [<a href="#B38" class="ref-link" data-ref-style="bibr">38</a>, <a href="#B86" class="ref-link" data-ref-style="bibr">86</a>]. In addition, the interfacial tension provides a measure for the ease of emulsification [<a href="#B13" class="ref-link" data-ref-style="bibr">13</a>]. The effect on surface or interfacial tension is related to the amphiphilic property of lignosulfonates, containing both hydrophilic and hydrophobic moieties. From a molecular point of view, the lignosulfonate macromolecule can attain a lower state of energy by extending its hydrophilic moieties into the water, while facing the hydrophobic parts away from it. The decrease in surface tension at increasing surfactant concentration can be explained by different mechanisms. Firstly, adsorption and desorption are occurring simultaneously, where an equilibrium is attained if the adsorption rate is equal and opposite to the desorption rate. By increasing the surfactant concentration, it is statistically more likely for a surfactant molecule to be in the right position and conformation to undergo adsorption. This would hence drive the adsorption–desorption equilibrium towards a higher surface coverage. Secondly, lignosulfonates are polyelectrolytes. By increasing the lignosulfonate concentration, the electrolyte concentration is also increased. As has been shown by small-angle X-ray scattering (SAXS), the effective surface charge of lignosulfonates decreases at increasing concentration [<a href="#B87" class="ref-link" data-ref-style="bibr">87</a>]. Higher concentrations of a common ion indeed enhance effects such as counterion condensation, charge screening, and the dissociation equilibrium [<a href="#B88" class="ref-link" data-ref-style="bibr">88</a>]. Water-solubility is ensured by the ionic groups of lignosulfonates, so a lower effective charge would have destabilizing effect. At a lower water-solubility, the equilibrium would hence be shifted to increased surface or interface adsorption. This effect concurs with the observations that lignosulfonates can be precipitated by salt addition (salting-out) [<a href="#B89" class="ref-link" data-ref-style="bibr">89</a>] and that emulsion stabilization is highest, if the stabilizers are on the verge of precipitation [<a href="#B90" class="ref-link" data-ref-style="bibr">90</a>].</p><p id="p58">Lignosulfonate adsorption at aqueous surfaces is evidenced, among others, by a decrease in surface tension [<a href="#B13" class="ref-link" data-ref-style="bibr">13</a>, <a href="#B38" class="ref-link" data-ref-style="bibr">38</a>, <a href="#B91" class="ref-link" data-ref-style="bibr">91</a>]. Within a certain range, this decrease follows a linear-logarithmic progression with concentration [<a href="#B13" class="ref-link" data-ref-style="bibr">13</a>, <a href="#B38" class="ref-link" data-ref-style="bibr">38</a>]. Below this range, the surface tension of the pure liquid is approached asymptotically. At high lignosulfonate concentrations, the slope of the surface tension decreases. Some authors have explained this behavior with the onset of lignosulfonate aggregation [<a href="#B75" class="ref-link" data-ref-style="bibr">75</a>, <a href="#B92" class="ref-link" data-ref-style="bibr">92</a>], but other effects cannot be ruled out. Measurements of the surface tension with respect to concentration are shown in <a href="#F7" class="ref-link" data-ref-style="fig">Figure 7</a>.</p><figure class="media-panel" id="F7"><div class="media"><img src="//cdnintech.com/media/chapter/83868/1680680847/media/F7.png" class="figure-link" alt=""></div><figcaption class="caption"><h4>Figure 7.</h4><p><p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" id="p59">Equilibrium surface tension in dependence of surfactant concentration. Comparison of lignosulfonates (LS) with polyelectrolyte polymers (left) [<xref rid="B38" ref-type="bibr">38</xref>] or with the surfactants dodecyl benzenesulfonate (DBS), nonylphenyl polyoxyethylene glycol (PONP) and polysorbate 20 (PS20) (right) [<xref rid="B92" ref-type="bibr">92</xref>].</p></p></figcaption></figure><p id="p60">In comparison with commercial surfactants, the effect on surface or interfacial tension is often less at the same mass concentration [<a href="#B75" class="ref-link" data-ref-style="bibr">75</a>, <a href="#B82" class="ref-link" data-ref-style="bibr">82</a>, <a href="#B92" class="ref-link" data-ref-style="bibr">92</a>]. However, in comparison with other polyelectrolyte polymers, the effect on surface tension can be considerably higher [<a href="#B38" class="ref-link" data-ref-style="bibr">38</a>]. This circumstance is likely related to the chemical composition and structure, which define macroscopic properties such as solubility, hydrophilic–lipophilic balance (HLB), or surface coverage.</p></div><div class="section" id="sec_8_2" data-lvl="2"><h3 class="heading section-title">3.3 Parameters affecting the surface activity of lignosulfonates</h3><p id="p61">There are several external factors, which govern the surface activity of lignosulfonates, in addition to the intrinsic properties such as composition and abundance of functional groups. These factors include, but are not limited to:<ul><li><p id="p62">Salinity</p></li><li><p id="p63">pH</p></li><li><p id="p64">Temperature</p></li><li><p id="p65">Co-solvents in the aqueous phase</p></li><li><p id="p66">Oil phase composition</p></li></ul></p><p id="p67">It has been shown that increasing salinity with simple monovalent electrolytes, such as NaCl, can have the same effect as increasing lignosulfonate concentration [<a href="#B38" class="ref-link" data-ref-style="bibr">38</a>, <a href="#B66" class="ref-link" data-ref-style="bibr">66</a>]. The effect of NaCl concentration on surface or interfacial tension is illustrated in <a href="#F8" class="ref-link" data-ref-style="fig">Figure 8</a>, which is marked by same linear-logarithmic progression as in <a href="#F7" class="ref-link" data-ref-style="fig">Figure 7</a>. As discussed earlier, increasing the concentration of a common ion facilitates a lower effective surface charge, which further enhances surface or interface adsorption. The similarities in observed surface tension hence corroborate that the surface adsorption of lignosulfonates is also driven by salinity. It could further be argued that outside the tested concentration range in <a href="#F8" class="ref-link" data-ref-style="fig">Figure 8</a>, the same slope-decrease or plateau would be visible is in <a href="#F7" class="ref-link" data-ref-style="fig">Figure 7</a>. While this may be plausible, it has yet to be demonstrated experimentally.</p><figure class="media-panel" id="F8"><div class="media"><img src="//cdnintech.com/media/chapter/83868/1680680847/media/F8.png" class="figure-link" alt=""></div><figcaption class="caption"><h4>Figure 8.</h4><p><p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" id="p68">Effect of NaCl concentration on the surface tension of 0.01 wt.% lignosulfonate in water (left) [<xref rid="B38" ref-type="bibr">38</xref>]. Effect of NaCl or lignosulfonate concentration on the tension of the water-xylene interface (right) [<xref rid="B66" ref-type="bibr">66</xref>].</p></p></figcaption></figure><p id="p69">However, the data exhibited in <a href="#F7" class="ref-link" data-ref-style="fig">Figures 7</a> and <a href="#F8" class="ref-link" data-ref-style="fig">8</a> represents a simplified case. In both instances, the counterion was solely the monovalent sodium ion, as only sodium lignosulfonate and NaCl were used. In presence of multivalent cations, the surface phenomena of lignosulfonates are more complex. Di- or trivalent cations, for example, were shown to induce interface gelling [<a href="#B66" class="ref-link" data-ref-style="bibr">66</a>]. As illustrated in <a href="#F9" class="ref-link" data-ref-style="fig">Figure 9</a>, such interfaces behave inelastically, exhibiting wrinkles and cracks upon deformation. Pendant drop tensiometry relies on the applicability of the Young-Laplace equation. Since this is not the case for inelastic interfaces, the technique fails to predict accurate interfacial tension. Similar challenges are evident for other techniques, such as the Du Noüy ring method or spinning drop tensiometry.</p><figure class="media-panel" id="F9"><div class="media"><img src="//cdnintech.com/media/chapter/83868/1680680847/media/F9.png" class="figure-link" alt=""></div><figcaption class="caption"><h4>Figure 9.</h4><p><p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" id="p70">Droplet retraction in pendant drop video-tensiometry. In incompressible interface layer is visible as wrinkling of the droplet surface, which was formed by sodium lignosulfonate in presence of CaCl<sub>2</sub>. Image taken from [<xref rid="B66" ref-type="bibr">66</xref>].</p></p></figcaption></figure><p id="p71">Lowering the pH can further enhance the effect of lignosulfonates on surface tension [<a href="#B91" class="ref-link" data-ref-style="bibr">91</a>]. This circumstance is in analogy to the salting-out effect of simple electrolytes. Phenolic moieties are said to ionize at around pH 9–10, while the carboxylic acid groups ionize at pH 3–4 [<a href="#B54" class="ref-link" data-ref-style="bibr">54</a>, <a href="#B55" class="ref-link" data-ref-style="bibr">55</a>]. A lower pH can hence reduce the total charge of the lignosulfonate macromolecules. This would further reduce the water-solubility and thereby drive the equilibrium towards higher adsorption. However, the discussed effect is valid only if the lignosulfonates remain water-soluble. If precipitation is evident, then the bulk concentration would decrease, which would also reduce surface and interface adsorption.</p><p id="p72">As depicted in <a href="#F10" class="ref-link" data-ref-style="fig">Figure 10</a>, increasing the temperature can also increase the effect of lignosulfonates on surface tension. At higher temperature, the hydrodynamic radius of lignosulfonates decreases [<a href="#B93" class="ref-link" data-ref-style="bibr">93</a>]. Thermodynamically speaking, the entropy is higher at elevated temperatures. This can enable a larger number of possible conformations, thus reducing the average molecular dimensions [<a href="#B88" class="ref-link" data-ref-style="bibr">88</a>]. As a result, lignosulfonate aggregation and a reduction of zeta potential have been reported at elevated temperature [<a href="#B94" class="ref-link" data-ref-style="bibr">94</a>]. These two effects indicate solution-destabilization, which could further promote surface adsorption.</p><figure class="media-panel" id="F10"><div class="media"><img src="//cdnintech.com/media/chapter/83868/1680680847/media/F10.png" class="figure-link" alt=""></div><figcaption class="caption"><h4>Figure 10.</h4><p><p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" id="p73">Surface tension of water and 1 g/l lignosulfonate in water. Image taken from [<xref rid="B93" ref-type="bibr">93</xref>].</p></p></figcaption></figure><p id="p74">Co-solvents in the aqueous phase can alter characteristics such as the solution parameter and the dielectric constant. This will inevitably also affect the surface behavior of the lignosulfonates. The addition of low molecular weight alcohols yielded a decrease of surface charge and slight interparticle association [<a href="#B87" class="ref-link" data-ref-style="bibr">87</a>]. The effect was thereby similar as to increasing the ionic strength, implying solution destabilization of lignosulfonates by alcohol addition. On the other hand, hydrophobic interaction chromatography uses water/ethanol and water/2-propanol mixtures to eluate the more hydrophobic fractions [<a href="#B64" class="ref-link" data-ref-style="bibr">64</a>], which would suggest that water/alcohol mixtures are a better solvent for these. This is corroborated by the fact that the surface pressure decreased due to ethanol addition [<a href="#B81" class="ref-link" data-ref-style="bibr">81</a>], i.e. fewer lignosulfonate molecules would enter the interface. Corresponding measurements of interfacial tension are shown in <a href="#F10" class="ref-link" data-ref-style="fig">Figure 10</a>. Overall, the effects of adding alcohols are hence counteracting, i.e., reduction of effective charge (destabilizing) and solubility improvement (stabilizing). It is thus not surprising that the emulsion stability could be both improved and reduced after alcohol addition (<a href="#F11" class="ref-link" data-ref-style="fig">Figure 11</a>) [<a href="#B81" class="ref-link" data-ref-style="bibr">81</a>].</p><figure class="media-panel" id="F11"><div class="media"><img src="//cdnintech.com/media/chapter/83868/1680680847/media/F11.png" class="figure-link" alt=""></div><figcaption class="caption"><h4>Figure 11.</h4><p><p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" id="p75">Tension of the mineral oil–water interface in dependence of ethanol concentration. The samples contained 1 g/l lignosulfonate (LS) and 20 mM NaCl as background electrolyte. Figure taken from [<xref rid="B81" ref-type="bibr">81</xref>].</p></p></figcaption></figure><p id="p76">The addition of non-solvents to water will eventually lead to lignosulfonate precipitation [<a href="#B87" class="ref-link" data-ref-style="bibr">87</a>]. In this case, the interfacial activity would also decrease, as the bulk concentration is lower [<a href="#B66" class="ref-link" data-ref-style="bibr">66</a>]. Solvent shifting can be useful for the production of functional micro- and nanoparticles from lignin [<a href="#B95" class="ref-link" data-ref-style="bibr">95</a>]. However, the technology bears limited importance for this chapter, as the resulting Pickering-emulsions tend to be less stable [<a href="#B66" class="ref-link" data-ref-style="bibr">66</a>].</p><p id="p77">At last, the oil phase composition can also affect the interfacial activity of lignin. A simple explanation for this can be based on the concept of the hydrophilic–lipophilic balance (HLB). Surfactants can generally be classified according to their HLB, where lower HLB values account for more lipophilic surfactants and high values for more hydrophilic ones. It is generally agreed that an HLB of 3–6 is characteristic for water-in-oil (W/O) emulsifiers, whereas 8–18 are suited for oil-in-water (O/W) emulsifiers [<a href="#B76" class="ref-link" data-ref-style="bibr">76</a>]. According to the HLB model, optimum emulsion stability is given, when a surfactant-blend matches the HLB value of the emulsified liquids. In analogy to that, the interfacial tension is also said to exhibit a minimum at the optimal HLB of the surfactant mixture. The concept is illustrated in <a href="#F12" class="ref-link" data-ref-style="fig">Figure 12</a>.</p><figure class="media-panel" id="F12"><div class="media"><img src="//cdnintech.com/media/chapter/83868/1680680847/media/F12.png" class="figure-link" alt=""></div><figcaption class="caption"><h4>Figure 12.</h4><p><p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" id="p78">Variation of emulsion stability, droplet size, and interfacial tension with percentage of surfactant with high HLB. Figure reproduced from [<xref rid="B76" ref-type="bibr">76</xref>].</p></p></figcaption></figure><p id="p79">Oils with low polarity, such as paraffins and mineral oil, tend to have a required HLF for O/W emulsions of 9–11, whereas more polar oils are in the range of 12–17, e.g., oleic acid, chlorinated paraffins, and aromatics such as toluene [<a href="#B96" class="ref-link" data-ref-style="bibr">96</a>]. The HLB scale can hence also be an indicator for the compatibility or affinity of surfactants towards a certain oil phase. Lignosulfonates were reported to have an HLB of 11.6 based on their composition [<a href="#B97" class="ref-link" data-ref-style="bibr">97</a>], but the effective HLB is likely higher than this, as the cited value is a rough estimation based on the elementary composition. Among others, it does not consider stearic effects. In addition, the contribution of the sulfonate group to the effective HLB is generally high. There are few studies comparing the stability of different oils emulsified with lignosulfonates. Experience shows that aromatic solvents, e.g., toluene or xylene (HLB = 14–15), tend yield more stable than emulsions with mineral oil (HLB = 10) [<a href="#B13" class="ref-link" data-ref-style="bibr">13</a>]. Accordingly, it was demonstrated that the effect on interfacial tension of xylene was greater than on mineral oil, as plotted in <a href="#F12" class="ref-link" data-ref-style="fig">Figure 12</a>. It would only make sense that lignosulfonates, comprising a polyaromatic structure, also have a higher affinity to aromatic oils than to paraffinic ones. Based on their behavior, lignosulfonates can be classified as O/W emulsion stabilizers with an effective HLB of 10–18 (<a href="#F13" class="ref-link" data-ref-style="fig">Figure 13</a>).</p><figure class="media-panel" id="F13"><div class="media"><img src="//cdnintech.com/media/chapter/83868/1680680847/media/F13.png" class="figure-link" alt=""></div><figcaption class="caption"><h4>Figure 13.</h4><p><p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" id="p80">Effect of molecular weight and oil phase on interfacial tension. Figure taken from [<xref rid="B13" ref-type="bibr">13</xref>].</p></p></figcaption></figure></div><div class="section" id="sec_9_2" data-lvl="2"><h3 class="heading section-title">3.4 Interactions with other surfactants</h3><p id="p81">The presence of other surfactants can affect the surface activity of lignosulfonate. Surfactants can be distinguished based on their charge, i.e., non-ionic, anionic, cationic, and zwitterionic surfactants. Another classification would be based on the structure, that is, polymeric and non-polymeric surfactants. Electrostatic interactions with lignosulfonates are eminent, if the co-surfactant carries a charge. Surfactant interactions will hence be discussed for each individual type in this sub-chapter.</p><p id="p82">Interactions with non-ionic surfactants can be due to effects such as hydrogen bonding or hydrophobic interactions. Straight-chain alcohols can exhibit surfactant-like properties, if the chain length is at least four carbon atoms or more [<a href="#B98" class="ref-link" data-ref-style="bibr">98</a>]. The effect of these was studied by Qiu et al., who concluded that alcohols can improve the surface activity of lignosulfonate [<a href="#B86" class="ref-link" data-ref-style="bibr">86</a>]. The authors attributed the largest effect to alcohols with a chain-length of at least 10 carbon atoms, which was evidence by an increase in zeta potential of TiO<sub>2</sub> particles. Such behavior would suggest cooperative adsorption. Still, the author conducted experiments at a constant alcohol/lignosulfonate ratio, which makes delineating individual contributions difficult, as the lignosulfonate concentration would increase at increasing alcohol levels. Low molecular weight alcohols can indeed increase counterion condensation on lignosulfonates [<a href="#B87" class="ref-link" data-ref-style="bibr">87</a>], which could facilitate a higher surface coverage. Simon et al. further studied the interfacial tension of lignosulfonate solutions in presence of asphaltenes [<a href="#B82" class="ref-link" data-ref-style="bibr">82</a>]. The authors concluded that interfacial adsorption was competitive, which is a potential detriment for emulsion stability. At last, Askvik et al. concluded that lignosulfonates and non-ionic surfactants did not associate, due to the small contribution of hydrophobic interaction [<a href="#B38" class="ref-link" data-ref-style="bibr">38</a>]. Current literate hence disagrees, whether blending lignosulfonates with non-ionic surfactants has a positive effect. Yet, some cases may indeed benefit from such mixtures.</p><p id="p83">Anionic surfactants can interact with lignosulfonates by electrostatic repulsion, which would suggest competitive adsorption. Still, combining lignosulfonates with other anionic surfactants can be beneficial, as both species increase the ionic strength. As has been discussed previously, increasing salinity will also facilitate more interfacial adsorption [<a href="#B66" class="ref-link" data-ref-style="bibr">66</a>]. This perception is supported by a study on blending lignosulfonates and sodium dodecyl sulfate (SDS) [<a href="#B75" class="ref-link" data-ref-style="bibr">75</a>], which showed that the presence of lignosulfonates decreased the critical micelle concentration (CMC) of SDS. A beneficial effect was also found in the context of enhanced oil recovery (EOR) [<a href="#B99" class="ref-link" data-ref-style="bibr">99</a>, <a href="#B100" class="ref-link" data-ref-style="bibr">100</a>, <a href="#B101" class="ref-link" data-ref-style="bibr">101</a>]. By blending petroleum sulfonates, sodium chloride, 2-propanol, and lignosulfonates, interfacial tension values as low as <span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m38"><mml:mn>1</mml:mn><mml:mo>×</mml:mo><mml:msup><mml:mn>10</mml:mn><mml:mrow><mml:mo>−</mml:mo><mml:mn>3</mml:mn></mml:mrow></mml:msup><mml:mi>mN</mml:mi><mml:mo>/</mml:mo><mml:mi mathvariant="normal">m</mml:mi></mml:math></span> were obtained [<a href="#B100" class="ref-link" data-ref-style="bibr">100</a>]. Another implementation would be the use of lignosulfonates as sacrificial adsorbents [<a href="#B16" class="ref-link" data-ref-style="bibr">16</a>, <a href="#B102" class="ref-link" data-ref-style="bibr">102</a>]. Here, the rock formations are initially saturated with lignosulfonates, after which a second flood with a different surfactant mixture would be injected. While this application does not directly relate to emulsion stabilization, it shows that adsorption was also competitive.</p><p id="p84">Cationic surfactants interact with lignosulfonates electrostatically, which can yield the formation of lignosulfonate-cationic surfactant complexes [<a href="#B38" class="ref-link" data-ref-style="bibr">38</a>]. Improved solubility of such complexes in oil media has been reported [<a href="#B103" class="ref-link" data-ref-style="bibr">103</a>]. Still, a challenge with such systems is the formation of a water-insoluble complexes. In such cases, the surfactants precipitate and are no longer available for interfacial adsorption, hence yielding mixed effects on emulsion stabilization [<a href="#B38" class="ref-link" data-ref-style="bibr">38</a>].</p><p id="p85">It has long been established that lignosulfonates can associate with cationic polyelectrolytes, forming insoluble complexes, colloids, and macroscopic precipitates [<a href="#B104" class="ref-link" data-ref-style="bibr">104</a>]. Association of lignosulfonates with chitosan reportedly forms such complexes at a sulfonate/amine ratio close to 1.0, suggesting that all sulfonate groups are accessible for interactions [<a href="#B105" class="ref-link" data-ref-style="bibr">105</a>]. No complex formation was reported at pH 8, which entails that it was indeed electrostatic interactions governing the association of these two compounds. Another interesting application is the formation of multilayers via layer-by-layer association of lignosulfonates and cationic polyelectrolytes [<a href="#B106" class="ref-link" data-ref-style="bibr">106</a>, <a href="#B107" class="ref-link" data-ref-style="bibr">107</a>]. This self-assembly was reportedly governed by electrostatic interactions, hydrogen bonding, and cation-π interactions.</p><p id="p86">It can be concluded that strong interactions exist between lignosulfonates and cationic surfactants or polymers. Still, these interactions frequently yield precipitates, which would shift the emulsion stabilization mechanism from interfacial adsorption to that of a Pickering emulsion. Beneficial interactions can occur due to mixing lignosulfonates with anionic or non-ionic surfactants, but these may depend on the actual system and the application mode.</p></div></div><div class="section" id="sec_11" data-lvl="1"> <a href="https://ehealthcaresolutions.com/contact-us/" target="_blank" class="ads-link">Advertisement</a> <div id="intechopen-intechopen-4" class="ads"></div><h2 class="heading main-title">4. Emulsion stabilization mechanisms</h2><div class="section" id="sec_11_2" data-lvl="2"><h3 class="heading section-title">4.1 Basic concepts</h3><p id="p87">Emulsion stabilization entails the prevention or delay of the coalescence event. Coalescence is the fusing of two or more droplets to form one larger droplet. The limiting case for coalescence is complete phase separation, i.e., the oil and the water being separated into two distinct phases. Coalescence involves film drainage, during which the continuous phase is displaced between the coalescing droplets. Flocculation usually precedes coalescence, in which the dispersed droplets collect to form larger aggregates. Creaming or sedimentation occurs, if the flocculated droplets accumulate at the top (creaming) or the bottom (sedimentation) of the continuous phase. Centrifugation of emulsions stabilized with lignosulfonates can yield the formation of a dense packed layer (DPL) of droplets, which exhibit thixotropy and viscoelastic behavior [<a href="#B13" class="ref-link" data-ref-style="bibr">13</a>].</p><p id="p88">Fundamentally speaking, the use of a stabilizer (surfactant and/or polymer) introduces an energy barrier between the droplets [<a href="#B76" class="ref-link" data-ref-style="bibr">76</a>]. The lowest state of energy would be a system, which is completely phase separated. Yet, the transition from emulsion to complete phase separation may become noncontinuous in presence of a stabilizer. Emulsions stabilized with lignosulfonates are hence only kinetically stable. This entails that with time, the emulsions are expected to return to original state, i.e., a fully coalesced and phase separated system. Still, this transition is hindered to the extent that emulsion can remain in their emulsified state over a period of months or even years.</p><p id="p89">The interfacial tension is an important parameter, as low interfacial tension reduces the energy required for emulsification. In addition, this parameter can be used to study interfacial phenomena and interactions in the aqueous phase. A known stabilizer tends to be more effective at parameters, which yield a higher reduction of interfacial tension. Still, the reduction of interfacial tension in general is no guarantee for forming stable emulsions. There are examples of surfactants, which substantially decrease the interfacial tension, but do not produce stable emulsions or even destabilize existing systems. The latter are referred to as demulsifiers or emulsion breakers. The important point is that interfacial tension measurements can yield complementary information, but it should not be taken as a sole measure to probe emulsion stability. Interfacial adsorption is a prerequisite for an efficient stabilizer; however, emulsion stabilization involves several other mechanisms, which will be discussed in detail further on.</p></div><div class="section" id="sec_12_2" data-lvl="2"><h3 class="heading section-title">4.2 Stearic hindrance</h3><p id="p90">Stearic hindrance or stearic repulsion relies on the presence of the surfactant or polymer at the interface. By imposing spatial obstacles, the oil within the droplets is prevented from coalescing. Stearic repulsion is an important mechanism for non-ionic surfactants and polymers, as these lack the contribution from electrostatic repulsion.</p><p id="p91">Stearic repulsion is aided by a positive osmotic free energy of interaction, which states that the affinity of the adsorbed species to the continuous phase (water) is greater than to each other [<a href="#B76" class="ref-link" data-ref-style="bibr">76</a>]. As such, complete film drainage can be prevented, as the surfactant or polymer favors the retention of water between the oil droplets.</p><p id="p92">A second effect is of entropic nature, also referred to as volume restriction or elastic interaction [<a href="#B76" class="ref-link" data-ref-style="bibr">76</a>]. A significant overlap of the polymer chains can be favored by hydrophobic or van der Waals interactions. Separating these chains would require energy, which can act as a barrier to prevent coalescence. This phenomenon will be discussed in further detail during Section 4.5.</p></div><div class="section" id="sec_13_2" data-lvl="2"><h3 class="heading section-title">4.3 Marangoni effect</h3><p id="p93">The Marangoni effect, also referred to as Marangoni-Gibbs effect, is a common effect that facilitates emulsion stabilization with simple surfactants. It is related to the mass transfer along the interface between two fluids due to a concentration gradient. In analogy to Fick’s law of diffusion, mass transfer of surfactant molecules is directed towards areas with lower concentration. As the oil droplets approach, the surfactant layer between each droplet and the continuous phase can be displaced. This will in turn yield a concentration gradient. Surfactant molecules are hence drawn back into the contact area between the oil droplets, yielding a stabilizing effect. An illustration of the Marangoni effect is given in <a href="#F14" class="ref-link" data-ref-style="fig">Figure 14</a>.</p><figure class="media-panel" id="F14"><div class="media"><img src="//cdnintech.com/media/chapter/83868/1680680847/media/F14.png" class="figure-link" alt=""></div><figcaption class="caption"><h4>Figure 14.</h4><p><p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" id="p94">Illustration of the Marangoni effect during film drainage. Image taken from [<xref rid="B108" ref-type="bibr">108</xref>].</p></p></figcaption></figure><p id="p95">Attribution of the Marangoni effect to emulsion stabilization with lignosulfonates is given only implicitly, as the contribution of individual effects is often difficult to delineate. Still, the described effect is likely of importance, as lignosulfonates are subject to interfacial diffusion in the same manner as other surfactants.</p></div><div class="section" id="sec_14_2" data-lvl="2"><h3 class="heading section-title">4.4 Electrostatic repulsion</h3><p id="p96">In aqueous solution, lignosulfonates can attain a negative charge due to the dissociation of anionic groups. When adsorbed at the interface, these groups will contribute to an overall negative charge. Coulomb forces are then acting between the interfaces of different oil droplets, yielding electrostatic repulsion. This mechanism has been described for stabilization of both particles and emulsions with lignosulfonates [<a href="#B38" class="ref-link" data-ref-style="bibr">38</a>, <a href="#B46" class="ref-link" data-ref-style="bibr">46</a>, <a href="#B109" class="ref-link" data-ref-style="bibr">109</a>]. Related phenomena are frequently studied by measuring the electrophoretic mobility of the dispersed particles or droplets, i.e., the zeta potential [<a href="#B38" class="ref-link" data-ref-style="bibr">38</a>, <a href="#B70" class="ref-link" data-ref-style="bibr">70</a>].</p><p id="p97">Electrostatic repulsion is highly affected by the composition of the aqueous phase. Increasing electrolyte concentrations or the presence of less polar solvents will affect counterion condensation [<a href="#B87" class="ref-link" data-ref-style="bibr">87</a>]. Charge screening and a lower degree of dissociation can then lessen the repulsion between anionic groups [<a href="#B88" class="ref-link" data-ref-style="bibr">88</a>]. This could explain the destabilizing effect, which the presence of low molecular weight alcohols can have [<a href="#B81" class="ref-link" data-ref-style="bibr">81</a>]. Still, increasing the concentration of simple electrolytes tends to improve stability, if the lignosulfonate is not precipitated from solution [<a href="#B66" class="ref-link" data-ref-style="bibr">66</a>]. This effect is likely attributed to the fact that increasing salinity can enhance other effects, such as increased interfacial adsorption. The pH furthermore affects electrostatic repulsion. It has been reported that higher pH induces larger changes of the zeta potential, as the lignosulfonate macromolecules exhibit a higher degree of ionization [<a href="#B70" class="ref-link" data-ref-style="bibr">70</a>, <a href="#B110" class="ref-link" data-ref-style="bibr">110</a>].</p></div><div class="section" id="sec_15_2" data-lvl="2"><h3 class="heading section-title">4.5 Viscoelastic interface films</h3><p id="p98">It has long been established that droplet coalescence is affected by the stability of interfacial layers [<a href="#B111" class="ref-link" data-ref-style="bibr">111</a>]. From a purely mechanical point of view, an emulsion would naturally be more stable, if the dispersed droplets were coated by a rigid interface layer. The term rigid hereby refers to the inelastic behavior, as can also be observed for lignosulfonates [<a href="#B66" class="ref-link" data-ref-style="bibr">66</a>]. These systems are, however, not entirely rigid. Deformation may occur to some extent, bearing both elastic and viscose contributions, hence the terminology viscoelastic interface films.</p><p id="p99">Upon deformation, a purely elastic film will store the exerted work as potential energy. If the force is no longer acting, the system will return to the originate state or even oscillate, if the viscose contribution is small or negligible. Viscose forces can be viewed in analogy to friction, since energy is dissipated upon deformation, which cannot be retrieved during relaxation. Based on this, the complex modulus <span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m39"><mml:msup><mml:mi>E</mml:mi><mml:mo>&lowast;</mml:mo></mml:msup></mml:math></span> can be modeled as in <a href="#E6" class="ref-link" data-ref-style="disp-formula">Eq. (6)</a>, i.e., as the sum of the elastic contribution <span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m40"><mml:msup><mml:mi>E</mml:mi><mml:mo>′</mml:mo></mml:msup></mml:math></span> and the viscose contribution <span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m41"><mml:msup><mml:mi>E</mml:mi><mml:mrow><mml:mo>′</mml:mo><mml:mo>′</mml:mo></mml:mrow></mml:msup></mml:math></span>. These contributions are also referred to as the apparent elastic dilatational modulus and the apparent viscous dilatational modulus, respectively, as <a href="#E6" class="ref-link" data-ref-style="disp-formula">Eq. (6)</a> is based on the framework of dilatational interfacial rheology. During this measurement technique, a droplet is suspended in a continuous phase in presence of surfactants (see <a href="#F9" class="ref-link" data-ref-style="fig">Figure 9</a>), while undergoing volume expansion and contraction at the frequency <span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m42"><mml:mi>ω</mml:mi></mml:math></span>. This allows the complex modulus <span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m43"><mml:msup><mml:mi>E</mml:mi><mml:mo>&lowast;</mml:mo></mml:msup></mml:math></span> to be determined in terms of the change of interfacial tension <span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m44"><mml:mi mathvariant="italic">dσ</mml:mi><mml:mfenced open="(" close=")"><mml:mi>t</mml:mi></mml:mfenced></mml:math></span> divided by the change in interface area <span class="inline-formula"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m45"><mml:mi>d</mml:mi><mml:mo>ln</mml:mo><mml:mi>A</mml:mi><mml:mfenced open="(" close=")"><mml:mi>t</mml:mi></mml:mfenced></mml:math></span>.</p><div id="df_E6" class="formula panel"><mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" id="m46" specific-use="web-only"><mml:msup><mml:mi>E</mml:mi><mml:mo>&lowast;</mml:mo></mml:msup><mml:mfenced open="(" close=")"><mml:mi>ω</mml:mi></mml:mfenced><mml:mo>=</mml:mo><mml:msup><mml:mi>E</mml:mi><mml:mo>′</mml:mo></mml:msup><mml:mfenced open="(" close=")"><mml:mi>ω</mml:mi></mml:mfenced><mml:mo>+</mml:mo><mml:mi>i</mml:mi><mml:msup><mml:mi>E</mml:mi><mml:mrow><mml:mo>′</mml:mo><mml:mo>′</mml:mo></mml:mrow></mml:msup><mml:mfenced open="(" close=")"><mml:mi>ω</mml:mi></mml:mfenced><mml:mo>=</mml:mo><mml:mfrac><mml:mrow><mml:mi mathvariant="italic">dσ</mml:mi><mml:mfenced open="(" close=")"><mml:mi>t</mml:mi></mml:mfenced></mml:mrow><mml:mrow><mml:mi>d</mml:mi><mml:mo>ln</mml:mo><mml:mi>A</mml:mi><mml:mfenced open="(" close=")"><mml:mi>t</mml:mi></mml:mfenced></mml:mrow></mml:mfrac></mml:math><span class="equ">E6</span></div><p id="p100">Pendant drop tensiometry has the advantage of yielding information on both interfacial tension and interfacial rheology. The technique ceases to function, however, if droplet contraction and expansion is not entirely viscoelastic, as the Young Laplace equation is no longer valid. Other techniques to measure surface rheology include the oscillating barrier method, capillary waves, Langmuir trough, and surface rotational shear rheometry [<a href="#B112" class="ref-link" data-ref-style="bibr">112</a>]. The latter two have been successfully applied for studying the interfacial behavior of lignosulfonates.</p><p id="p101">Results from interfacial shear rheology of lignosulfonates are depicted in <a href="#F15" class="ref-link" data-ref-style="fig">Figure 15</a>. Frequency sweeps are of interest, as these can be used to characterize the interfacial properties. As can be seen, the elastic modulus <em><italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">E’</italic></em> and the viscose modulus <em><italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">E”</italic></em> are intersecting or approaching each other in cases, where only monovalent cations are present. The interfacial response is hence entirely viscoelastic. In presence of multivalent cations, i.e., Ca<sup>2+</sup> and Al<sup>3+</sup>, the elastic and viscose modulus are approximately parallel to each other. This behavior is characteristic for that of gelled interfaces. It appears that multivalent cations can function as connectors between the lignosulfonate molecules, imposing a stronger cohesion to the interface film. This gelling is a reasonable explanation for the observed rigidity in <a href="#F9" class="ref-link" data-ref-style="fig">Figure 9</a>.</p><figure class="media-panel" id="F15"><div class="media"><img src="//cdnintech.com/media/chapter/83868/1680680847/media/F15.png" class="figure-link" alt=""></div><figcaption class="caption"><h4>Figure 15.</h4><p><p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" id="p102">Frequency sweep of 1.8 g/l sodium lignosulfonate and in presence of different electrolytes at 0.2% strain. The oil phase is made of xylene isomer blend. Figure taken from [<xref rid="B66" ref-type="bibr">66</xref>].</p></p></figcaption></figure><p id="p103">Increasing the lignosulfonate concentration has shown to decrease the interfacial tension (see <a href="#F8" class="ref-link" data-ref-style="fig">Figure 8</a>). While the same could be expected for the interfacial modulus, experimental evidence shows that this is not the case. As depicted in <a href="#F16" class="ref-link" data-ref-style="fig">Figure 16</a>, the interfacial modulus will increase to a maximum, after which a decrease is noted. It appears that electrolytic effects govern this behavior, as the same maximum was observed for adding simple electrolytes. The maximum has indeed been correlated with a maximum in emulsion stability and the onset of lignosulfonate precipitation [<a href="#B66" class="ref-link" data-ref-style="bibr">66</a>]. The observed phenomena are hence in line with two long established principles: Emulsions can be stabilized by the formation of viscoelastic interface layers and the emulsion stability tends to be best, if the stabilizing agent is on the verge of precipitation [<a href="#B90" class="ref-link" data-ref-style="bibr">90</a>, <a href="#B111" class="ref-link" data-ref-style="bibr">111</a>]. If the solubility limit is exceeded, precipitation yields the formation of particles, hence shifting the stabilization mechanism to that of a Pickering emulsion. This type of mechanism will be discussed in the next sub-chapter.</p><figure class="media-panel" id="F16"><div class="media"><img src="//cdnintech.com/media/chapter/83868/1680680847/media/F16.png" class="figure-link" alt=""></div><figcaption class="caption"><h4>Figure 16.</h4><p><p xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" id="p104">Interfacial moduli in dependence of lignosulfonate or added salt concentration. Data was obtained using interfacial shear rheology and xylene isomer blend as the oil phase. Figures taken from [<xref rid="B66" ref-type="bibr">66</xref>].</p></p></figcaption></figure></div><div class="section" id="sec_16_2" data-lvl="2"><h3 class="heading section-title">4.6 Particle stabilization</h3><p id="p105">Particle stabilization of emulsions involves the presence of a third (solid) phase. The solid phase is usually present as a colloidal dispersion, exhibiting particle sizes of approximately 1 nm to 1 μm. These particles can adsorb at the oil–water interface, forming bilayers and bridging monolayers [<a href="#B113" class="ref-link" data-ref-style="bibr">113</a>]. The stabilizing mechanism is based on coherent particle layers around the dispersed liquid, preventing coalescence by acting as a steric (mechanical) barrier. A particle stabilized emulsion is also referred to as Pickering emulsion. Interest has currently shifted from using inorganic particles to adopting bio-based systems, which includes the use of cellulose, chitin, starch, proteins, and lignin [<a href="#B114" class="ref-link" data-ref-style="bibr">114</a>].</p><p id="p106">Particle stabilization is usually not the primary mechanism, with which lignosulfonates stabilize emulsions. In aqueous solution at low salinity, lignosulfonates are usually well-dissolved and hence act by molecular adsorption at the interface. Certain conditions, however, can induce lignosulfonate precipitation, which will shift the stabilization mechanism to that of a Pickering emulsion [<a href="#B66" class="ref-link" data-ref-style="bibr">66</a>]. In addition, lignosulfonate aggregation can occur at concentrations as low as 0.05 g/l [<a href="#B55" class="ref-link" data-ref-style="bibr">55</a>]. Aggregation is reportedly facilitated by π–π stacking, hydrogen bonding, and hydrophobic interactions [<a href="#B93" class="ref-link" data-ref-style="bibr">93</a>, <a href="#B115" class="ref-link" data-ref-style="bibr">115</a>, <a href="#B116" class="ref-link" data-ref-style="bibr">116</a>]. At the right conditions, aggregate dimensions can be in the range of colloidal dispersions. Based on the diffusion coefficient of lignosulfonates obtained from dilatational interfacial rheology, it was concluded that lignosulfonates undergo interfacial adsorption in the aggregated state [<a href="#B66" class="ref-link" data-ref-style="bibr">66</a>]. Interfacially adsorbed aggregates could furthermore act by particle stabilization. It is important to note that lignosulfonate aggregation occurs gradually over a broad concentration range. The contribution of aggregates to the overall emulsion stability would hence build up in increments. This contrasts with precipitation, where an immediate shift to particle stabilization is observed at the precipitation onset.</p></div></div><div class="section" id="sec_18" data-lvl="1"> <a href="https://ehealthcaresolutions.com/contact-us/" target="_blank" class="ads-link">Advertisement</a> <div id="intechopen-intechopen-6" class="ads"></div><h2 class="heading main-title">5. Summary and conclusion</h2><p id="p107">This chapter detailed the fundamentals of emulsion stabilization with lignosulfonates. First, basic concepts, the industrial production, as well as chemical make-up and structure of lignosulfonates were discussed. Second, the effect of lignosulfonates on surface and interfacial tension was described. Third, the fundamental mechanisms behind emulsion stabilization with lignosulfonates were explained.</p><p id="p108">Lignosulfonates are bio-based specialty chemicals and function as surfactants due to their amphiphilic property. Lignosulfonates are readily water-soluble as they comprise ionizable moieties, i.e., sulfonate and carboxylic acid groups at neutral pH. They can hence be utilized in a variety of technical applications, which includes the stabilization of oil-in-water emulsions. Surface and interface adsorption of lignosulfonates is evidenced by a reduction in surface and interfacial tension. Parameters that can enhance the effect on interfacial tension include increased salinity, a reduction in pH, and the presence of co-solvents or co-surfactants. A high reduction of interfacial tension is generally beneficial, as this suggests enhanced interfacial adsorption and reduces the energy required during emulsification. While interfacial adsorption is a prerequisite for an efficient emulsion stabilizer, the stabilization mechanism is related to other phenomena as well. For lignosulfonates, these mechanisms include stearic hindrance, electrostatic repulsion, the Marangoni-Gibbs effect, the formation of viscoelastic interface layers, and particle stabilization. The stabilization mechanisms are furthermore affected by the composition of the lignosulfonates as well as the aqueous and oil phase. Parameters that increase the interfacial activity and yield the formation of more cohesive interface layers are beneficial, as both effects tend to promote emulsion stability.</p><p id="p109">There has been an increased interest in biopolymers recently, as these are inherently more sustainable than petroleum-derived polymers. Lignosulfonates are no exception to that trend, which is also mirrored by the large variety of lignosulfonate products on the market today. Emulsion stabilization is one of the application areas, which still has the potential for growth. This chapter was hence dedicated to the fundamentals of emulsion stabilization with lignosulfonates, in the hope that this may aid their utilization in new areas and products.</p></div><div class="section" id="sec_22" data-lvl="1"> <a href="https://ehealthcaresolutions.com/contact-us/" target="_blank" class="ads-link">Advertisement</a> <div id="intechopen-intechopen-7" class="ads"></div><h2 class="heading main-title">Conflict of interest</h2><p id="p110">The author declares no conflict of interest.</p></div> </div> <div id="adx_native_ad_110741" class="ads" style="margin-top: -15px; margin-bottom: 7rem;" data-v-79b2068e></div> <div id="references" class="ref-list" data-v-79b2068e><h2 data-v-79b2068e>References</h2> <ol data-v-79b2068e><li data-v-79b2068e><span class="order" data-v-79b2068e>1.</span> <span data-v-79b2068e><ref id="B1"><mixed-citation publication-type="book">Sixta H. Handbook of Pulp. 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Langmuir. 2008;<bold>24</bold>(15):7735-7743</mixed-citation></ref></span></li></ol></div>  </div> <aside class="right-col" data-v-79b2068e><div class="track-container" data-v-79b2068e><div class="track" data-v-79b2068e><section class="sections-toggle" data-v-1797c9ee data-v-79b2068e><h3 class="title" data-v-1797c9ee>Sections</h3> <div class="clip" data-v-1797c9ee><a class="shortcut capitalize" data-v-1797c9ee>Author information</a> <ul class="list" data-v-1797c9ee><li class="item" data-v-be6610d8 data-v-1797c9ee><span class="item-order" data-v-be6610d8>1.</span><a class="item-link" data-v-be6610d8>Introduction</a></li><li class="item" data-v-be6610d8 data-v-1797c9ee><span class="item-order" data-v-be6610d8>2.</span><a class="item-link" data-v-be6610d8>Fundamentals</a></li><li class="item" data-v-be6610d8 data-v-1797c9ee><span class="item-order" data-v-be6610d8>3.</span><a class="item-link" data-v-be6610d8>Adsorption on surfaces and interfaces</a></li><li class="item" data-v-be6610d8 data-v-1797c9ee><span class="item-order" data-v-be6610d8>4.</span><a class="item-link" data-v-be6610d8>Emulsion stabilization mechanisms</a></li><li class="item" data-v-be6610d8 data-v-1797c9ee><span class="item-order" data-v-be6610d8>5.</span><a class="item-link" data-v-be6610d8>Summary and conclusion</a></li><li class="item unnumbered-section" data-v-be6610d8 data-v-1797c9ee><span class="item-order" data-v-be6610d8></span><a class="item-link" data-v-be6610d8>Conflict of interest</a></li></ul> <a class="shortcut capitalize ref-link" data-v-1797c9ee>References</a> <span class="shortcut capitalize footnotes-link" data-v-1797c9ee></span> <div class="section-footer" data-v-1797c9ee><div class="share-and-download cf" data-v-cec94ee8 data-v-1797c9ee><a rel="" href="#" class="btn btn-download" data-v-cec94ee8><svg width="24" height="24" viewBox="0 0 24 24" fill="none" xmlns="http://www.w3.org/2000/svg" data-v-cec94ee8><path fill-rule="evenodd" clip-rule="evenodd" d="M13 2C13 1.44772 12.5523 1 12 1C11.4477 1 11 1.44772 11 2V13.5858L8.70711 11.2929C8.31658 10.9024 7.68342 10.9024 7.29289 11.2929C6.90237 11.6834 6.90237 12.3166 7.29289 12.7071L11.2922 16.7064C11.2946 16.7088 11.297 16.7112 11.2995 16.7136C11.3938 16.8063 11.502 16.8764 11.6172 16.9241C11.7343 16.9727 11.8625 16.9996 11.997 17C11.998 17 11.999 17 12 17C12.001 17 12.002 17 12.003 17C12.2746 16.9992 12.5208 16.8901 12.7005 16.7136C12.703 16.7112 12.7054 16.7088 12.7078 16.7064L16.7071 12.7071C17.0976 12.3166 17.0976 11.6834 16.7071 11.2929C16.3166 10.9024 15.6834 10.9024 15.2929 11.2929L13 13.5858V2ZM3 16C3.55228 16 4 16.4477 4 17V20C4 20.5523 4.44772 21 5 21H19C19.5523 21 20 20.5523 20 20V17C20 16.4477 20.4477 16 21 16C21.5523 16 22 16.4477 22 17V20C22 21.6569 20.6569 23 19 23H5C3.34315 23 2 21.6569 2 20V17C2 16.4477 2.44772 16 3 16Z" fill="#FFFDEA" data-v-cec94ee8></path></svg> <span data-v-cec94ee8>DOWNLOAD FOR FREE</span></a> <div class="share-and-cite cf" data-v-cec94ee8><button class="btn btn-share" data-v-cec94ee8><img src="//cdnintech.com/web/frontend/www/assets/45.123/series/icons/ic-share.svg" alt data-v-cec94ee8> <span data-v-cec94ee8>Share</span></button> <div class="modal-container" data-v-cec94ee8><div data-v-44e2a4e0 data-v-cec94ee8><button class="activator-btn" data-v-44e2a4e0><img src="//cdnintech.com/web/frontend/www/assets/45.123/series/icons/ic-copy.svg" data-v-44e2a4e0> <span data-v-44e2a4e0>Cite</span></button> <div class="modal-overlay" style="display:none;" data-v-44e2a4e0 data-v-44e2a4e0><div class="modal-content" data-v-44e2a4e0><button class="close-btn" data-v-44e2a4e0><svg width="32" height="32" viewBox="0 0 32 32" fill="none" xmlns="http://www.w3.org/2000/svg" data-v-44e2a4e0><path fill-rule="evenodd" clip-rule="evenodd" d="M25.0607 9.06066C25.6464 8.47487 25.6464 7.52513 25.0607 6.93934C24.4749 6.35355 23.5251 6.35355 22.9393 6.93934L16 13.8787L9.06066 6.93934C8.47487 6.35355 7.52513 6.35355 6.93934 6.93934C6.35355 7.52513 6.35355 8.47487 6.93934 9.06066L13.8787 16L6.93934 22.9393C6.35355 23.5251 6.35355 24.4749 6.93934 25.0607C7.52513 25.6464 8.47487 25.6464 9.06066 25.0607L16 18.1213L22.9393 25.0607C23.5251 25.6464 24.4749 25.6464 25.0607 25.0607C25.6464 24.4749 25.6464 23.5251 25.0607 22.9393L18.1213 16L25.0607 9.06066Z" fill="#000000" data-v-44e2a4e0></path></svg></button> <div class="citation-header" data-v-44e2a4e0><p class="title" data-v-44e2a4e0>Cite this chapter</p> <p class="additonal-info" data-v-44e2a4e0>There are two ways to cite this chapter:</p></div> <div class="citation-body" data-v-44e2a4e0><div class="citation-card citation-card-cite" data-v-44e2a4e0><label for="citation-styles" data-v-44e2a4e0>1. 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20.5000817,16.7141761 C21.1293176,16.6008204 21.6765993,17.0811585 21.6765993,17.6893451 L21.6765993,22.2984507 L21.6821204,22.287581 C21.6821204,22.2912042 21.6817754,22.2948275 21.6817754,22.2984507 C21.6817754,30.752331 28.5590289,37.6295845 37.0127366,37.6295845 C37.7863845,37.6295845 38.5527859,37.5676444 39.3076275,37.4532535 L39.3076275,47.5686479 C39.3076275,48.3079613 39.9071873,48.9076937 40.6466732,48.9076937 C41.3859866,48.9076937 41.9853739,48.3079613 41.9853739,47.5686479 L41.9853739,36.796757 C44.484719,35.9396021 46.7488986,34.4454472 48.5267014,32.4212641 L48.5669021,32.3755423 C49.1533493,31.7199085 48.9746028,30.6460493 48.0927754,30.247493" data-v-eb7322e6></path></g></g></svg> <div class="text text-style-d743" style="font-size:150em;" data-v-eb7322e6> <span class="title" data-v-eb7322e6>Lignin</span> <span class="sub-title" data-v-eb7322e6>Chemistry, Structure, and Application</span>  <span class="editors" data-v-eb7322e6>Edited by Arpit Sand</span></div></a></figure> <h4 class="title" data-v-69cc9686><a href="/books/11902" data-v-69cc9686> <span data-v-69cc9686>Lignin</span></a></h4> <p class="edited" data-v-69cc9686> Edited by <span data-v-69cc9686><a href="/profiles/287032" data-v-69cc9686>Arpit Sand</a> </span></p> <p class="published-date" data-v-69cc9686><span data-v-69cc9686>Published:</span> 05 April 2023</p> </div> </div><div style="display:inline;" data-v-12a4d3b7 data-v-cf751d1e> <div class="chapter-item" data-v-3de91768 data-v-cf751d1e><div class="book-cover" style="background-image:url(https://cdn.intechopen.com/books/images_new/11902.jpg);" data-v-3de91768></div> <div class="inner" data-v-3de91768><span class="label" data-v-3de91768>Chapter 1</span> <a href="/chapters/86050" class="title" data-v-3de91768>Introductory Chapter: Introduction to Structure Pr...</a> <p class="authors" data-v-3de91768>By Jaya Tuteja and Arpit Sand</p> <p class="label" data-v-3de91768>280 downloads</p></div></div></div><div style="display:inline;" data-v-12a4d3b7 data-v-cf751d1e> <div class="chapter-item" data-v-3de91768 data-v-cf751d1e><div class="book-cover" style="background-image:url(https://cdn.intechopen.com/books/images_new/11902.jpg);" data-v-3de91768></div> <div class="inner" data-v-3de91768><span class="label" data-v-3de91768>Chapter 2</span> <a href="/chapters/83779" class="title" data-v-3de91768>Composition and Role of Lignin in Biochemicals</a> <p class="authors" data-v-3de91768>By Tawaf Ali Shah, Li Zhihe, Li Zhiyu and Zhang Andon...</p> <p class="label" data-v-3de91768>344 downloads</p></div></div></div><div style="display:inline;" data-v-12a4d3b7 data-v-cf751d1e> <div class="chapter-item" data-v-3de91768 data-v-cf751d1e><div class="book-cover" style="background-image:url(https://cdn.intechopen.com/books/images_new/11902.jpg);" data-v-3de91768></div> <div class="inner" data-v-3de91768><span class="label" data-v-3de91768>Chapter 3</span> <a href="/chapters/85056" class="title" data-v-3de91768>Perspective Chapter: Potential of Lignin Valorizat...</a> <p class="authors" data-v-3de91768>By Mohamed H. El-Moayed, Justin Kühn, Sea-Hyun Lee, M...</p> <p class="label" data-v-3de91768>227 downloads</p></div></div></div></div></div></div> </section> <footer data-v-e6aca418 data-v-49840897> <div class="footer" data-v-e6aca418><div class="inner" data-v-e6aca418><div class="footer-nav cf" data-v-e6aca418><div class="nav-box" data-v-e6aca418><a href="/" class="title router-link-active" data-v-e6aca418>Home</a> <a href="/news" class="title" data-v-e6aca418>News</a> <a href="/contact-us" class="title" data-v-e6aca418>Contact</a> <a href="/page/careers-at-intechopen" class="title" data-v-e6aca418>Careers</a> <a href="/sdg-hub" class="title" data-v-e6aca418>SDG Hub</a></div> <div class="nav-box" data-v-e6aca418> <a href="/about-intechopen" class="title" data-v-e6aca418>About</a> <a href="/authors-and-editors" class="link" data-v-e6aca418>Our Authors and Editors</a> <a href="/page/scientific-advisors" class="link" data-v-e6aca418>Scientific Advisors</a> <a href="/page/team" class="link" data-v-e6aca418>Team</a> <a href="/page/events" class="link" data-v-e6aca418>Events</a> <a href="/advertising" class="link" data-v-e6aca418>Advertising</a> <a href="/page/partnerships" class="link" data-v-e6aca418>Memberships and Partnerships</a></div> <div class="nav-box" data-v-e6aca418><a href="/publish" class="title" data-v-e6aca418>Publish</a> <a href="/page/about-open-access" class="link" data-v-e6aca418>About Open Access</a> <a href="/how-open-access-publishing-with-intechopen-works" class="link" data-v-e6aca418>How it Works</a> <a href="/page/OA-publishing-fees" class="link" data-v-e6aca418>OA Publishing Fees</a> <a href="/open-access-funding" class="link" data-v-e6aca418>Open Access Funding</a> <a href="/peer-reviewing" class="link" data-v-e6aca418>Peer Review</a> <a href="/page/editorial-policies" class="title" data-v-e6aca418>Editorial Policies</a></div> <div class="nav-box" data-v-e6aca418><div class="social-wrap" data-v-e6aca418><a href="https://twitter.com/intechopen" target="_blank" class="icr" data-v-e6aca418><img src="//cdnintech.com/web/frontend/www/assets/45.123/svg/x.svg" alt="Twitter" data-v-e6aca418></a> <a href="https://www.facebook.com/IntechOpen" target="_blank" class="icr" data-v-e6aca418><img src="//cdnintech.com/web/frontend/www/assets/45.123/svg/facebook.svg" alt="Facebook" data-v-e6aca418></a> <a href="https://www.linkedin.com/company/intechopen" target="_blank" class="icr" data-v-e6aca418><img src="//cdnintech.com/web/frontend/www/assets/45.123/svg/linkedin.svg" alt="LinkedIn" data-v-e6aca418></a> <a href="https://www.instagram.com/intechopen/" target="_blank" class="icr" data-v-e6aca418><img src="//cdnintech.com/web/frontend/www/assets/45.123/svg/instagram.svg" alt="Instagram" data-v-e6aca418></a></div> <div class="company-info-wrap cf" data-v-e6aca418><p class="address" data-v-e6aca418> IntechOpen Limited<br data-v-e6aca418> 167-169 Great Portland Street,<br data-v-e6aca418> London, W1W 5PF,<br data-v-e6aca418> UNITED KINGDOM </p> <div class="meta-wrap" data-v-e6aca418><p class="meta" data-v-e6aca418>Phone: +44 20 8089 5702</p></div></div></div></div> <div class="search-wrap cf" data-v-e6aca418><form class="search-term" data-v-6047d25e data-v-e6aca418><input placeholder="Search" required="required" value="" data-v-6047d25e> <button type="submit" class="icr iconSearch" data-v-6047d25e>Submit</button></form> <a href="https://auth.intechopen.com/?referer=sf&env=https%3A%2F%2Fpublish.intechopen.com" target="_blank" class="cta button-type-1" data-v-e6aca418>Author Panel Sign in</a></div> <div class="legal-wrap" data-v-e6aca418><ul class="legal-nav" data-v-e6aca418><li data-v-e6aca418><a href="/page/terms-and-conditions" data-v-e6aca418>Terms and Conditions</a></li> <li data-v-e6aca418><a href="/privacy-policy" data-v-e6aca418>Privacy Policy</a></li> <li data-v-e6aca418><a href="/page/customer-complaints" data-v-e6aca418>Customer Complaints</a></li></ul> <p class="copyright" data-v-e6aca418>© 2024 IntechOpen. 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Marshall, this book offers insightful research and novel approaches, contributing to the continuous discourse on Helicobacter pylori-related research.","metaKeywords":null,"publishedDatetime":"May 22, 2024","endDate":null,"newsType":"1","contentRaw":"[{\"type\":\"htmlEditorComponent\",\"content\":\"\u003Cp\u003EIntechOpen has achieved a significant milestone in its mission to democratise scientific knowledge by announcing the publication of its 7,000th open access book, \u003Ca href=\\\"https:\u002F\u002Fwww.intechopen.com\u002Fbooks\u002F1003597\\\"\u003E'Towards the Eradication of \u003Cem\u003EHelicobacter pylori\u003C\u002Fem\u003E Infection - Rapid Diagnosis and Precision Treatment.' \u003C\u002Fa\u003E\u003C\u002Fp\u003E\\n\\n\u003Cp\u003EGuided by the expertise of Dr Liang Wang, Dr Alfred Chin Yen Tay, and 2005 Nobel Prize Laureate Prof. Barry J. Marshall, this book offers insightful research and novel approaches, contributing to the continuous discourse on \u003Cem\u003EHelicobacter pylori\u003C\u002Fem\u003E-related research.\u003C\u002Fp\u003E\\n\\n\u003Cp\u003EThe editors agree that, despite extensive research and medical advances over many years, completely eliminating the bacterium remains a challenge in numerous cases. The pressing need to address this issue has prompted a multidisciplinary approach that combines rapid diagnosis and precise treatment methods, as showcased in this book. \u003C\u002Fp\u003E\\n\\n\u003Cp\u003EDr. Wang further elaborates, "In this volume, experts from various disciplines have joined forces to present the latest research, clinical insights, and practical applications of diagnosing and treating \u003Cem\u003EH. pylori\u003C\u002Fem\u003E infection. The chapters present in this volume cover diagnostic modalities in detecting \u003Cem\u003EH. pylori \u003C\u002Fem\u003Einfection, from rapid noninvasive techniques for detecting antibiotic resistance to the utility of linked color imaging in endoscopic diagnosis. The book also presents innovative treatment strategies, including the role of cytokines in inflammation, the impact of antibiotic resistance patterns, and the potential of immunotherapeutic approaches."\u003C\u002Fp\u003E\\n\\n\u003Cp\u003EThis year holds special significance as it marks the 40th anniversary of the groundbreaking and daring self-demonstration of Koch's postulates by Prof.Marshall, which confirmed the link between \u003Cem\u003EHelicobacter pylori\u003C\u002Fem\u003E and gastritis. This pivotal research, conducted with his colleague Robin Warren, ultimately earned them the Nobel Prize for their discovery of the bacterium \u003Cem\u003EHelicobacter pylori\u003C\u002Fem\u003E and its role in gastritis and peptic ulcer disease.\u003C\u002Fp\u003E\\n\\n\u003Cp\u003E \u003C\u002Fp\u003E\\n\\n\u003Cp\u003EAs a publisher of scientific works that brings together researchers from all over the world to contribute their knowledge to advance their fields of research, we are delighted that this year's milestone publication addresses this crucial public health issue and explores novel strategies in diagnosis and therapeutic approaches to combat \u003Cem\u003EHelicobacter pylori \u003C\u002Fem\u003Einfection.\u003C\u002Fp\u003E\\n\\n\u003Cp\u003EJelena Marusic, Head of Book Publishing at IntechOpen, reflects on this significant moment: "We extend our sincere thanks to all the authors for their invaluable contributions and to the editors whose dedication and expertise have been crucial in shaping this milestone publication. We take great pride in achieving this accomplishment, which was also made possible by the outstanding collaborative efforts of our dedicated teams."\u003C\u002Fp\u003E\\n\\n\u003Cp\u003ESara Uhac, IntechOpen CEO, adds: ”On this celebratory occasion, our deepest gratitude goes to all the members of our community who have contributed to our 7000 books over the years. Thank you for helping us achieve this important milestone, for sharing our values, for opening up science and for celebrating its contribution to the progress of society. The commitment to work by the principles of our driving idea, every day, brought this achievement to life.”\u003C\u002Fp\u003E\\n\\n\u003Cp\u003EOur innovative open access book publishing model, developed over the past two decades, was crafted with the purpose of promoting open access principles. As we celebrate this achievement, we remain committed to advancing scholarly communication in the years to come.\u003C\u002Fp\u003E\\n\\n\u003Cp\u003EAccess the book \u003Ca href=\\\"https:\u002F\u002Fwww.intechopen.com\u002Fbooks\u002F1003597\\\"\u003Ehere\u003C\u002Fa\u003E.\u003C\u002Fp\u003E\\n\"}]","published":true,"mainMedia":{"caption":"","originalUrl":"\u002Fmedia\u002Foriginal\u002F406"}},"components":[{"type":"htmlEditorComponent","content":"\u003Cp\u003EIntechOpen has achieved a significant milestone in its mission to democratise scientific knowledge by announcing the publication of its 7,000th open access book, \u003Ca href=\"https:\u002F\u002Fwww.intechopen.com\u002Fbooks\u002F1003597\"\u003E'Towards the Eradication of \u003Cem\u003EHelicobacter pylori\u003C\u002Fem\u003E Infection - Rapid Diagnosis and Precision Treatment.' \u003C\u002Fa\u003E\u003C\u002Fp\u003E\n\n\u003Cp\u003EGuided by the expertise of Dr Liang Wang, Dr Alfred Chin Yen Tay, and 2005 Nobel Prize Laureate Prof. Barry J. 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We take great pride in achieving this accomplishment, which was also made possible by the outstanding collaborative efforts of our dedicated teams."\u003C\u002Fp\u003E\n\n\u003Cp\u003ESara Uhac, IntechOpen CEO, adds: ”On this celebratory occasion, our deepest gratitude goes to all the members of our community who have contributed to our 7000 books over the years. Thank you for helping us achieve this important milestone, for sharing our values, for opening up science and for celebrating its contribution to the progress of society. The commitment to work by the principles of our driving idea, every day, brought this achievement to life.”\u003C\u002Fp\u003E\n\n\u003Cp\u003EOur innovative open access book publishing model, developed over the past two decades, was crafted with the purpose of promoting open access principles. As we celebrate this achievement, we remain committed to advancing scholarly communication in the years to come.\u003C\u002Fp\u003E\n\n\u003Cp\u003EAccess the book \u003Ca href=\"https:\u002F\u002Fwww.intechopen.com\u002Fbooks\u002F1003597\"\u003Ehere\u003C\u002Fa\u003E.\u003C\u002Fp\u003E\n"}],"latestNews":[{"slug":"green-energy-and-environmental-technology-journal-supporting-the-un-sustainable-development-goals-20241105","title":"Green Energy and Environmental Technology Journal: Supporting the UN Sustainable Development Goals"},{"slug":"intechopen-signs-research4life-publishers-recommitment-20241029","title":"IntechOpen Signs Research4Life Publishers Recommitment"},{"slug":"intechopen-launches-open-science-hub-20241028","title":"IntechOpen Launches Open Science Hub"},{"slug":"2024-best-paper-award-from-the-ai-computer-science-and-robotics-technology-journal-20241004","title":"2024 Best Paper Award From the AI, Computer Science, and Robotics Technology Journal"},{"slug":"peer-review-week-2024-spotlight-an-interview-with-global-campus-co-founder-paul-tuinenburg-20240927","title":"Peer Review Week Spotlight: An Interview with Global Campus Co-Founder Paul Tuinenburg"},{"slug":"new-open-access-books-from-the-knowledge-unlatched-select-programme-2024-20240819","title":"New Open Access Books from the Knowledge Unlatched Select Programme 2024"},{"slug":"intechopen-presents-interviews-for-young-scientists-with-science-s-leading-minds-20240708","title":"IntechOpen Presents Interviews for Young Scientists with Science's Leading Minds"},{"slug":"recent-intechopen-book-series-launches-20240705","title":"Recent IntechOpen Book Series Launches"}]},"book":{"item":{"type":"book","id":"1003595","leadTitle":null,"fullTitle":"Reducing Carbon Footprint in Different Sectors for Sustainability","title":"Reducing Carbon Footprint in Different Sectors for Sustainability","subtitle":null,"reviewType":"peer-reviewed","abstract":"Discover practical strategies and innovative solutions to combat climate change with \u003Ci\u003EReducing Carbon Footprint in Different Sectors for Sustainability\u003C\u002Fi\u003E. This comprehensive guide explores how diverse industries—including energy, transportation, cement production, agriculture, and architecture—are adopting sustainable practices to reduce their environmental impact. Highlighting the critical roles of education and research in driving this transformation, the book offers invaluable insights into the integration of sustainability across various sectors. Whether you are a policymaker, industry leader, researcher, or educator, this volume equips you with the knowledge and tools needed to make meaningful contributions toward a low-carbon future. Embrace the opportunity to be part of the global effort to mitigate climate change and promote sustainability with this essential resource.","isbn":"978-0-85466-859-5","printIsbn":"978-0-85466-860-1","pdfIsbn":"978-0-85466-861-8","doi":"10.5772\u002Fintechopen.1001813","price":119,"priceEur":null,"priceUsd":null,"priceCbs":null,"slug":null,"numberOfPages":184,"isOpenForSubmission":false,"isInWos":null,"isInBkci":false,"hash":"df9b7607912d9b3bec7b6a1474b8dd01","bookSignature":"Taha Selim Ustun","publishedDate":"September 25th 2024","coverURL":"https:\u002F\u002Fintech-files.s3.amazonaws.com\u002Fa043Y000010JzBIQA0\u002F0015499_TrikoderCover%20%282023-04-28%2008%3A13%3A03%29.jpg","cdnWebCoverURL":"https:\u002F\u002Fcdnintech.com\u002Fbooks\u002F1003595\u002F1724996256-2076780210\u002Fweb-cover.jpg","cdnWebCoverURL300":"https:\u002F\u002Fcdnintech.com\u002Fbooks\u002F1003595\u002F1724996256-2076780210\u002Fweb-cover-300.jpg","numberOfDownloads":380,"numberOfViews":null,"numberOfWosCitations":null,"numberOfCrossrefCitations":3,"numberOfCrossrefCitationsByBook":0,"numberOfDimensionsCitations":2,"numberOfDimensionsCitationsByBook":null,"hasAltmetrics":0,"totalAltmetricsMentions":0,"numberOfTotalCitations":5,"isAvailableForWebshopOrdering":true,"dateEndFirstStepPublish":"November 2nd 2023","dateEndSecondStepPublish":"December 28th 2023","dateEndThirdStepPublish":"February 1st 2024","dateEndFourthStepPublish":"April 21st 2024","dateEndFifthStepPublish":"June 20th 2024","currentStepOfPublishingProcess":5,"indexedIn":"1,2,3,4,5,6","editedByType":null,"kuFlag":false,"sdgRelated":true,"featuredMarkup":null,"isPublished":true,"isPublisherCbs":false,"noAds":0,"editors":[{"id":"197609","title":"Dr.","name":"Taha Selim","middleName":null,"surname":"Ustun","slug":"taha-selim-ustun","fullName":"Taha Selim Ustun","cdnProfilePictureURL":"https:\u002F\u002Fcdnintech.com\u002Fmedia\u002Fauthor\u002F197609\u002F1726218818\u002Fprofile\u002Fimage1.jpg","biography":"Taha Selim Ustun received his Ph.D. in electrical engineering from Victoria University, Melbourne, VIC, Australia. He is currently a senior researcher with the Fukushima Renewable Energy Institute (FREA), National Institute of Advanced Industrial Science and Technology (AIST), where he leads the Smart Grid Cybersecurity Laboratory. Before that, he was a faculty member with the School of Electrical and Computer Engineering, Carnegie Mellon University, Pittsburgh, PA, USA. He has been invited to run specialist courses in Africa, India, and China. His research has attracted funding from prestigious programs in Japan, Australia, Europe, and North America. His current research interests include power systems protection, communication in power networks, distributed generation, microgrids, electric vehicle integration, and cybersecurity in smart grids.","institutionString":"Fukushima Renewable Energy Institute","position":null,"outsideEditionCount":null,"totalCites":0,"totalAuthoredChapters":"2","totalChapterViews":"0","totalEditedBooks":"4","institution":null,"countryString":"Japan"}],"equalEditorOne":null,"equalEditorTwo":null,"equalEditorThree":null,"coeditorOne":null,"coeditorTwo":null,"coeditorThree":null,"coeditorFour":null,"coeditorFive":null,"topics":[{"id":"136","title":"Environmental Sustainability","slug":"environmental-sciences-environmental-sustainability"}],"productType":{"id":"1","title":"Edited Volume","chapterContentType":"chapter","authoredCaption":"Edited by"},"subseries":{"id":"94","series":{"id":"24","title":"Sustainable Development","issn":"2753-6580","editor":{"id":"262440","title":"Prof.","name":"Usha","middleName":null,"surname":"Iyer-Raniga","slug":"usha-iyer-raniga","fullName":"Usha Iyer-Raniga","cdnProfilePictureURL":"https:\u002F\u002Fcdnintech.com\u002Fmedia\u002Fauthor\u002F262440\u002F1604448294\u002Fprofile\u002Fimage1.jpeg","biography":"Usha Iyer-Raniga is a professor in the School of Property and Construction Management at RMIT University. Usha co-leads the One Planet Network’s Sustainable Buildings and Construction Programme (SBC), a United Nations 10 Year Framework of Programmes on Sustainable Consumption and Production (UN 10FYP SCP) aligned with Sustainable Development Goal 12. The work also directly impacts SDG 11 on Sustainable Cities and Communities. She completed her undergraduate degree as an architect before obtaining her Masters degree from Canada and her Doctorate in Australia. Usha has been a keynote speaker as well as an invited speaker at national and international conferences, seminars and workshops. Her teaching experience includes teaching in Asian countries. She has advised Austrade, APEC, national, state and local governments. She serves as a reviewer and a member of the scientific committee for national and international refereed journals and refereed conferences. She is on the editorial board for refereed journals and has worked on Special Issues. Usha has served and continues to serve on the Boards of several not-for-profit organisations and she has also served as panel judge for a number of awards including the Premiers Sustainability Award in Victoria and the International Green Gown Awards. Usha has published over 100 publications, including research and consulting reports. Her publications cover a wide range of scientific and technical research publications that include edited books, book chapters, refereed journals, refereed conference papers and reports for local, state and federal government clients. She has also produced podcasts for various organisations and participated in media interviews. She has received state, national and international funding worth over USD $25 million. Usha has been awarded the Quarterly Franklin Membership by London Journals Press (UK). Her biography has been included in the Marquis Who's Who in the World® 2018, 2016 (33rd Edition), along with approximately 55,000 of the most accomplished men and women from around the world, including luminaries as U.N. Secretary-General Ban Ki-moon. In 2017, Usha was awarded the Marquis Who’s Who Lifetime Achiever Award.","institutionString":null,"position":null,"outsideEditionCount":0,"totalCites":0,"totalAuthoredChapters":"2","totalChapterViews":"0","totalEditedBooks":"0","institution":{"name":"RMIT University","institutionURL":null,"country":{"name":"Australia"}}}}},"tags":null,"_preview":0,"chapters":[{"id":"1186553","title":"Carbon Footprint Reduction in Energy Sector with Higher Penetration of Renewable Energy Resources","doi":"10.5772\u002Fintechopen.1005769","slug":null,"totalDownloads":69,"totalCrossrefCites":0,"totalDimensionsCites":0,"hasAltmetrics":0,"orderNumber":1,"abstract":"\u003Cp id=\"p1\"\u003EEnergy sector is a big source of carbon emissions. Traditionally, it is built, almost entirely, on fossil fuels with the exception of hydro and nuclear power plants. In line with the global mobilization toward tackling global warming by reducing carbon emissions, energy sector is trying to transition its generation portfolio to clean and sustainable energy sources. Renewable energy sources such as solar, wind, and wave provide energy without carbon emissions and provide a good alternative to traditional fossil fuels such as coal or natural gas. Another opportunity lies at the intersection of energy with transportation sector, another big contributor to carbon emissions. When electrified with renewables, transportation sector can both reduce its carbon emissions and provide support to electrical grid \u003Cem\u003E\u003Citalic xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" xmlns:xlink=\"http:\u002F\u002Fwww.w3.org\u002F1999\u002Fxlink\" xmlns:xsi=\"http:\u002F\u002Fwww.w3.org\u002F2001\u002FXMLSchema-instance\"\u003Evia\u003C\u002Fitalic\u003E\u003C\u002Fem\u003E novel solutions such as smart charging. However, these benefits come at a price. Non-dispatchable nature of renewable energy sources and their low inertia create operational and planning issues that make it hard to ensure demand is always met and the system operates in a healthy way. This chapter covers how renewable penetration can be increased while mitigating these issues with novel solutions. These include novel optimization ideas based on nature and new devices such as smart inverters.\u003C\u002Fp\u003E\n","signatures":"Taha Selim Ustun","downloadPdfUrl":"\u002Fchapter\u002Fpdf-download\u002F1186553","previewPdfUrl":"\u002Fchapter\u002Fpdf-preview\u002F1186553","isPublished":true,"isOnlineFirst":false,"isDeactivated":0,"authors":[{"id":"197609","title":"Dr.","name":"Taha Selim","surname":"Ustun","slug":"taha-selim-ustun","fullName":"Taha Selim Ustun"}],"corrections":null,"_preview":0},{"id":"1176380","title":"Post-Combustion Carbon dioxide (CO\u003Csub\u003E2\u003C\u002Fsub\u003E) Capture Technologies for Light Vehicle Internal Combustion Engines: A Technical Review of Present Trends, Challenges, and Prospects towards Reducing Global Carbon Footprint","doi":"10.5772\u002Fintechopen.1005062","slug":null,"totalDownloads":57,"totalCrossrefCites":0,"totalDimensionsCites":0,"hasAltmetrics":0,"orderNumber":2,"abstract":"\u003Cp id=\"p1\"\u003EIn the past decade, global attention has focused on global warming and the resultant climate change occasioned by the massive release of anthropogenic greenhouse emissions, mainly carbon dioxide (CO\u003Csub\u003E2\u003C\u002Fsub\u003E) into the atmosphere. To achieve net-zero targets by 2050, it is necessary to decarbonize high carbon-polluting sectors such as road transportation. According to several reports, internal combustion (IC) engine-driven road vehicles are among the biggest CO\u003Csub\u003E2\u003C\u002Fsub\u003E emitters globally; hence, the deployment of novel carbon capture and storage (CCS) technologies in the sector is considered as a significant measure for scaling down carbon footprint. This review discusses various carbon capture technologies, with emphasis on post-combustion capture techniques. It further highlights on solid adsorbent materials that hold promising potentials for adsorption-based CO\u003Csub\u003E2\u003C\u002Fsub\u003E capture and scholarly works that focus on their synthesis, modification, and use. The present trends in the development of solid adsorbent-based mobile post-combustion CO\u003Csub\u003E2\u003C\u002Fsub\u003E capture devices for IC engine-driven road vehicles are discussed. The review also elucidates the current barriers to the economic-scale implementation of the current technologies. Future prospects and suggestions for advancements are presented, with particular emphasis on the synthesis of low cost, nano-sized materials. The chapter concludes with key findings and the overall impacts of implementing CCS technologies.\u003C\u002Fp\u003E\n","signatures":"Promise C. Anyanwu","downloadPdfUrl":"\u002Fchapter\u002Fpdf-download\u002F1176380","previewPdfUrl":"\u002Fchapter\u002Fpdf-preview\u002F1176380","isPublished":true,"isOnlineFirst":false,"isDeactivated":0,"authors":[{"id":"571851","title":"Mr.","name":"Promise","surname":"Anyanwu","slug":"promise-anyanwu","fullName":"Promise Anyanwu"}],"corrections":null,"_preview":0},{"id":"1177941","title":"Carbon Reduction through Building Matrix Design for Sustainable Development","doi":"10.5772\u002Fintechopen.1004867","slug":null,"totalDownloads":49,"totalCrossrefCites":0,"totalDimensionsCites":0,"hasAltmetrics":0,"orderNumber":3,"abstract":"\u003Cp id=\"p1\"\u003EUnder the influence of planet problems such as global warming and the energy crisis, carbon reduction has become one of the goals for sustainable development. This chapter focuses on residential buildings as research objects for achieving carbon reduction based on architectural design. After analyzing three design principles from the life cycle of the building, macro, medium and micro design scales, and passive-active design, the authors initially established an open-source matrix design method. Then, an architectural competition plan that won only first prize from 92 proposals was taken to explain further the connotation of carbon reduction to achieve sustainable development through the matrix design method. The results show that the vicious circle exists between global warming and the energy crisis. Residential buildings contain more potential than other buildings for solving these problems. The matrix design method is established based on the three design principles. From a qualitative perspective, according to the case application, this research helps achieve carbon reduction for sustainable development.\u003C\u002Fp\u003E\n","signatures":"Bin Li, Luca Caneparo, Yuqing Zhang and Weihong Guo","downloadPdfUrl":"\u002Fchapter\u002Fpdf-download\u002F1177941","previewPdfUrl":"\u002Fchapter\u002Fpdf-preview\u002F1177941","isPublished":true,"isOnlineFirst":false,"isDeactivated":0,"authors":[{"id":"573659","title":"Ph.D. Student","name":"Bin","surname":"Li","slug":"bin-li","fullName":"Bin Li"},{"id":"573695","title":"Associate Prof.","name":"Luca","surname":"Caneparo","slug":"luca-caneparo","fullName":"Luca Caneparo"},{"id":"573880","title":"Ph.D. Student","name":"Yuqing","surname":"Zhang","slug":"yuqing-zhang","fullName":"Yuqing Zhang"},{"id":"573882","title":"Prof.","name":"Weihong","surname":"Guo","slug":"weihong-guo","fullName":"Weihong Guo"}],"corrections":null,"_preview":0},{"id":"1180488","title":"Impact of Rice Husk Biochar on Soil Carbon Sequestration, Methane Emission, and Rice Yield in Wetland Soil (Ultisol)","doi":"10.5772\u002Fintechopen.1005103","slug":null,"totalDownloads":47,"totalCrossrefCites":0,"totalDimensionsCites":0,"hasAltmetrics":0,"orderNumber":4,"abstract":"\u003Cp id=\"p1\"\u003EThe integration of physical, chemical, and biological indicators of soil quality that have an impact on environmental factors and farmer profitability is the focus of soil health. Applying biochar is an effective technique to promote soil carbon sequestration, which is a component of soil quality. Rice husk biochar (RHB), produced from the pyrolysis of rice husk (RH), has a higher nutritious value than biochar made from wood. A field research was conducted to evaluate the short-term implications of RHB-derived nutrient translocation and distribution in rice crop, as well as their effects on soil nutrients, rice productivity, and methane (CH\u003Csub\u003E4\u003C\u002Fsub\u003E) emissions in wetland Ultisol. The treatments included applying four organic fertilizers: rice husk biochar, daincha (\u003Cem\u003E\u003Citalic xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" xmlns:xlink=\"http:\u002F\u002Fwww.w3.org\u002F1999\u002Fxlink\" xmlns:xsi=\"http:\u002F\u002Fwww.w3.org\u002F2001\u002FXMLSchema-instance\"\u003ESesbania aculeata\u003C\u002Fitalic\u003E\u003C\u002Fem\u003E), jack tree (\u003Cem\u003E\u003Citalic xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" xmlns:xlink=\"http:\u002F\u002Fwww.w3.org\u002F1999\u002Fxlink\" xmlns:xsi=\"http:\u002F\u002Fwww.w3.org\u002F2001\u002FXMLSchema-instance\"\u003EArtocarpus heterophyllus\u003C\u002Fitalic\u003E\u003C\u002Fem\u003E) leaves, and farm yard manure (FYM) at rates of 35 (N1), 70 (N2), and 105 (N3) kg N ha\u003Csup\u003E−1\u003C\u002Fsup\u003E. The results showed that the application of RHB enhanced the uptake of soil organic carbon (SOC) as well as the production of rice grains and straw. The yield of brown rice increased with higher rates of N treatment. The RHB contributed a significant amount of carbon to the refractory paddy soil, which increased its carbon content in the crop as well. Consequently, there was a significant 50–60% drop in CH\u003Csub\u003E4\u003C\u002Fsub\u003E emissions from soil as compared to FYM.\u003C\u002Fp\u003E\n","signatures":"Kamala Rajalekshmi, Betty Bastin and Sandeep Sasidharan","downloadPdfUrl":"\u002Fchapter\u002Fpdf-download\u002F1180488","previewPdfUrl":"\u002Fchapter\u002Fpdf-preview\u002F1180488","isPublished":true,"isOnlineFirst":false,"isDeactivated":0,"authors":[{"id":"487270","title":"Dr.","name":"Sandeep","surname":"Sasidharan","slug":"sandeep-sasidharan","fullName":"Sandeep Sasidharan"},{"id":"526583","title":"Dr.","name":"Rajalekshmi","surname":"Kamala","slug":"rajalekshmi-kamala","fullName":"Rajalekshmi Kamala"},{"id":"1211048","title":"Prof.","name":"Betty","surname":"bastin","slug":"betty-bastin","fullName":"Betty bastin"}],"corrections":null,"_preview":0},{"id":"1182128","title":"A Review of Strategies to Achieve Net Zero Targets in the Cement and Concrete Sectors","doi":"10.5772\u002Fintechopen.1005051","slug":null,"totalDownloads":98,"totalCrossrefCites":3,"totalDimensionsCites":2,"hasAltmetrics":0,"orderNumber":5,"abstract":"\u003Cp id=\"p1\"\u003EThe cement and concrete industries face significant challenges in decarbonization due to escalating demand driven by rapid urbanization, population growth, and infrastructure restoration needs. Cement production alone accounts for 8% of global anthropogenic CO\u003Csub\u003E2\u003C\u002Fsub\u003E emissions, underscoring the urgency of exploring pathways to achieve net-zero emissions in these sectors. With over 120 nations committing to net-zero targets by 2050, a comprehensive examination of emerging carbon-saving technologies is imperative. While several promising innovations are in nascent stages, rigorous life cycle assessments are essential to determine their potential for carbon reduction. Practical strategies for achieving net-zero objectives and UN sustainability goals involve embracing circular economy principles, harnessing diverse by-product sources, fostering stakeholder engagement, and fostering technological innovation. An efficiency approach that integrates advancements in materials science, alternative fuels, and sector-wide efficiencies is crucial for success. This assessment identifies promising technologies, highlights knowledge gaps, underscores the importance of further research, and offers recommendations for implementing best practices on the path to net zero.\u003C\u002Fp\u003E\n","signatures":"Kwaku Boakye, Dahl Winters, Olurotimi Oguntola, Kevin Fenton and Steve Simske","downloadPdfUrl":"\u002Fchapter\u002Fpdf-download\u002F1182128","previewPdfUrl":"\u002Fchapter\u002Fpdf-preview\u002F1182128","isPublished":true,"isOnlineFirst":false,"isDeactivated":0,"authors":[{"id":"576473","title":"Ph.D. Student","name":"Kwaku","surname":"Boakye","slug":"kwaku-boakye","fullName":"Kwaku Boakye"},{"id":"579963","title":"Prof.","name":"Steven","surname":"Simske","slug":"steven-simske","fullName":"Steven Simske"},{"id":"579965","title":"Dr.","name":"Kevin","surname":"Fenton","slug":"kevin-fenton","fullName":"Kevin Fenton"},{"id":"579966","title":"Ph.D. Student","name":"Dahl","surname":"Winters","slug":"dahl-winters","fullName":"Dahl Winters"},{"id":"579967","title":"Ph.D. Student","name":"Olurotimi","surname":"Oguntola","slug":"olurotimi-oguntola","fullName":"Olurotimi Oguntola"}],"corrections":null,"_preview":0},{"id":"1180246","title":"Perspective Chapter: Educational Technology under Scrutiny in Higher Education – A Framework for Balancing Environmental, Economic and Social Aspects in a Blended Design","doi":"10.5772\u002Fintechopen.1005117","slug":null,"totalDownloads":51,"totalCrossrefCites":0,"totalDimensionsCites":0,"hasAltmetrics":0,"orderNumber":6,"abstract":"\u003Cp id=\"p1\"\u003EFollowing COVID-19, higher education (HE) has recognised the importance of educational technology (EdTech). With its growing influence on educational design, awareness of its role and impact on the sustainability transition in HE from an economic, environmental and social perspective is needed. Taking a holistic view, this chapter shows the opportunities and drawbacks of using EdTech in HE aiming at developing suggestions for responsible application. Economically, there are concerns because the earnings models of for-profit EdTech companies are focused on obtaining user data and benefit from a lack of transparency in data use, privacy and intellectual property. Environmentally, the use of EdTech can reduce the carbon footprint of HE institutions by opening a virtual space where students can learn and faculty can attend international conferences without commuting or travelling (by plane). However, device disposal and the energy consumption of hardware and data storage must be considered. Socially, using EdTech can foster the development of sustainability competencies if thoughtfully designed by applying pedagogical design principles for sustainability-oriented blended learning. Higher education can take control of a balanced use of EdTech in educational practice by focusing on ethical and human values and adopting a whole-institution approach to sustainability as included in the proposed framework.\u003C\u002Fp\u003E\n","signatures":"Marieke Versteijlen and Marleen Janssen Groesbeek","downloadPdfUrl":"\u002Fchapter\u002Fpdf-download\u002F1180246","previewPdfUrl":"\u002Fchapter\u002Fpdf-preview\u002F1180246","isPublished":true,"isOnlineFirst":false,"isDeactivated":0,"authors":[{"id":"577181","title":"Prof.","name":"Marleen","surname":"Janssen Groesbeek","slug":"marleen-janssen-groesbeek","fullName":"Marleen Janssen Groesbeek"},{"id":"592230","title":"Dr.","name":"Marieke","surname":"Versteijlen","slug":"marieke-versteijlen","fullName":"Marieke Versteijlen"}],"corrections":null,"_preview":0},{"id":"1180056","title":"Perspective Chapter: Unlocking Energy and Natural Resources for Sustainable Development in Nigeria – The Role of Energy Research Centers","doi":"10.5772\u002Fintechopen.1005050","slug":null,"totalDownloads":9,"totalCrossrefCites":0,"totalDimensionsCites":0,"hasAltmetrics":0,"orderNumber":7,"abstract":"\u003Cp id=\"p1\"\u003EAmid global challenges like climate change and resource depletion, Nigeria’s pursuit of low-carbon energy resources teeters on the brink. Nigeria grapples with the delicate balance between economic growth, environmental stewardship, and energy security. Energy and natural resources are crucial to modern society, playing a pivotal role in economic development, environmental sustainability, and overall human well-being. In response to these challenges, the national energy research centers have emerged as vital institutions that can contribute to the development of sustainable innovations that would catalyze the transition to a low-carbon economy. Unlocking these potential hinges on cutting-edge research tailored to drive innovation, influence policy, and promote responsible resource management. Investing in research holds the potential to facilitate Nigeria’s transition to a low-carbon economy. These research centers can act as catalysts for unleashing the full potential of Nigeria’s energy and natural resources contributing to global efforts to combat climate change while ensuring economic growth and energy security for the populations. Achieving these objectives requires an increased investment in avant-garde research, which would propel Nigeria toward a future characterized by sustainability and prosperity and paving the way for a resilient and environmentally conscious path to long-term development.\u003C\u002Fp\u003E\n","signatures":"Emmanuel Ogbomida, Abdullahi Mustapha, Chukwudi Emeribe, Lawrence Ezemonye and Mike Ajieh","downloadPdfUrl":"\u002Fchapter\u002Fpdf-download\u002F1180056","previewPdfUrl":"\u002Fchapter\u002Fpdf-preview\u002F1180056","isPublished":true,"isOnlineFirst":false,"isDeactivated":0,"authors":[{"id":"278258","title":"Dr.","name":"Emmanuel","surname":"Ogbomida","slug":"emmanuel-ogbomida","fullName":"Emmanuel Ogbomida"},{"id":"1210559","title":"Ph.D.","name":"Abdullahi","surname":"Mustapha","slug":"abdullahi-mustapha","fullName":"Abdullahi Mustapha"},{"id":"1210560","title":"Ph.D.","name":"Chukwudi","surname":"Emeribe","slug":"chukwudi-emeribe","fullName":"Chukwudi Emeribe"},{"id":"1210561","title":"Ph.D.","name":"Mike","surname":"Ajieh","slug":"mike-ajieh","fullName":"Mike Ajieh"},{"id":"1210562","title":"Prof.","name":"Lawrence","surname":"Ezemonye","slug":"lawrence-ezemonye","fullName":"Lawrence Ezemonye"}],"corrections":null,"_preview":0}]},"relatedBooks":[{"type":"book","id":"8839","title":"Advanced Communication and Control Methods for Future Smartgrids","subtitle":null,"isOpenForSubmission":false,"isPublished":true,"hash":"272b87662ec87f859b72930758bce663","slug":"advanced-communication-and-control-methods-for-future-smartgrids","bookSignature":"Taha Selim Ustun","coverURL":"https:\u002F\u002Fcdn.intechopen.com\u002Fbooks\u002Fimages_new\u002F8839.jpg","editedByType":"Edited by","editors":[{"id":"197609","title":"Dr.","name":"Taha Selim","surname":"Ustun","slug":"taha-selim-ustun","fullName":"Taha Selim 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For instance, different schools of thinkers and observers are constrained by significantly different values of the Hubble constant, differing rates of Universe expansion, and hence Universe age. Concurrence through the collection of more data seems unlikely. There is also disagreement over the best objects to use for distance calibration of the many supernovae type Ia (SNe Ia) signals. Some prefer to reference the classical Cepheid variable stars and others the signals from the tip of the red-giant branch (TRGB). This situation is complicated further by recent observations of the James Webb Space Telescope (JWST) of very old, but large, mature galaxies the existence which cannot easily be explained by the current standard model of cosmology. Another basket of unanswered questions is the nature of dark matter (DM). Why do we find evidence for DM in some galaxies but not others and why haven't we been able to detect atomic or subatomic-sized DM particles despite the diligent labors of many people in underground observatories over the past decade? This lack of advancement is mirrored by the search for the nature of dark energy, which has stagnated for nearly three decades. In addition, researchers cannot agree whether space geometry is better described as Euclidean or elliptical. This disagreement has been termed a crisis. We will be collecting and publishing recent insights and the unhindered thoughts of many free-thinkers of cosmology to help physicists and astronomers reevaluate the evidence along new lines. One hopes this will lead to a better understanding of some topics of cosmology.","isbn":"978-1-83634-808-5","printIsbn":"978-1-83634-809-2","pdfIsbn":"978-1-83634-810-8","doi":"10.5772\u002Fintechopen.1005695","price":0,"priceEur":null,"priceUsd":null,"oapfPrice":1400,"slug":null,"numberOfPages":0,"isOpenForSubmission":true,"isSalesforceBook":true,"isNomenclature":false,"hash":"17392491b07028d1d6b5bbbee89d8289","bookSignature":"Dr. Michael L. Smith and Dr. Ahmet M. 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Dr. Smith has over four decades of experience with data analysis of non-linear systems and noisy data, having received his Ph.D. from Colorado State University and studied biophysics at Johns Hopkins University. He has studied theoretical variants of the Einstein equation, QM, and spectroscopy and was affiliated with Umea University, Sweden, prior to his retirement.","equalEditorOneBiosketch":null,"equalEditorTwoBiosketch":null,"equalEditorThreeBiosketch":null,"coeditorOneBiosketch":"Prof. Öztaş received his Ph.D. in 1991 from Hacettepe University, Turkey, in the field of string theory. Between 2000 and 2001, he studied at Luleå University of Technology in Sweden, focusing on astrophysics, particularly neutron stars. Since 2006, he has been working in the field of cosmology and continues to publish in this area.","coeditorTwoBiosketch":null,"coeditorThreeBiosketch":null,"coeditorFourBiosketch":null,"coeditorFiveBiosketch":null,"isPublished":false,"isDeactivated":false,"editors":[{"id":"59479","title":"Dr.","name":"Michael","middleName":"L.","surname":"Smith","slug":"michael-smith","fullName":"Michael Smith","cdnProfilePictureURL":"https:\u002F\u002Fcdnintech.com\u002Fmedia\u002Fauthor\u002F59479\u002F1719387430\u002Fprofile\u002Fimage1.jpg","biography":"Michael Smith received his Ph.D. from Colorado State University and then studied biophysics and computerized data handling of non-linear systems at Johns Hopkins University. Before retirement, he was affiliated with Umea University, Sweden since 1982. He has published on the topic of the proper interpretation of supernovae type Ia (SNe Ia) observations since 2006. Several of his publications deal with dark energy, dark matter, and Hubble constant determinations. Lately, he has been investigating the basis for the current Hubble tension as stemming from improper handling of the SNe Ia data and differing interpretations of the Friedmann (FLRW) model. He has also published new fundamental relations over the relations between matter, energy, spacetime, and gravity. In biophysics, he has recently published several articles on the roles of lactoperoxidase and iodine in the prevention of airborne infections including COVID-19. He has pointed out remarkable differences in death rates from the SARS-CoV-2 virus between Japan, \u003C20% death rate, and other modern societies (US, UK, Sweden). Dr. Smith has published more than fifty articles in peer-reviewed journals, edited two books on cosmology, and produced six short videos for public education.","institutionString":"Independent Researcher","countryString":"Sweden","position":null,"outsideEditionCount":null,"totalCites":0,"totalAuthoredChapters":"4","totalChapterViews":"0","totalEditedBooks":"2","institution":null}],"equalEditorOne":null,"equalEditorTwo":null,"equalEditorThree":null,"coeditorOne":{"id":"59581","title":"Dr.","name":"Ahmet M.","middleName":"Mecit","surname":"Öztaș","slug":"ahmet-m.-oztas","fullName":"Ahmet M. Öztaș","cdnProfilePictureURL":"https:\u002F\u002Fcdnintech.com\u002Fmedia\u002Fauthor\u002F59581\u002F1725349254\u002Fprofile\u002Fimage1.jpg","biography":"Prof. Dr. Ahmet Mecit Öztaş received his Ph.D. in 1991 from Hacettepe University (Ankara, Turkey) in the field of string theory. He has conducted extensive research in theoretical physics. Between 2000 and 2001, he studied at Luleå University of Technology in Sweden, focusing on astrophysics, particularly neutron stars, and published papers in this area. Since 2006, he has been working in the field of cosmology and continues to publish in this area. Currently, Dr. Öztaş is teaching at Hacettepe University, where, through theoretical courses, he also offers introductory courses in cosmology and astrophysics.","institutionString":null,"countryString":null,"position":null,"outsideEditionCount":null,"totalCites":0,"totalAuthoredChapters":"2","totalChapterViews":"0","totalEditedBooks":"0","institution":{"name":"Hacettepe University","institutionURL":null,"country":{"name":"Turkey"}}},"coeditorTwo":null,"coeditorThree":null,"coeditorFour":null,"coeditorFive":null,"assistantEditorOne":null,"assistantEditorTwo":null,"assistantEditorThree":null,"assistantEditorFour":null,"assistantEditorFive":null,"topics":[{"id":"98","title":"Astronomy and Astrophysics","slug":"astronomy-and-astrophysics"}],"chapters":null,"productType":{"id":"1","title":"Edited Volume","chapterContentType":"chapter","authoredCaption":"Edited by"},"subseries":null,"personalPublishingAssistant":{"id":"301331","firstName":"Mia","lastName":"Vulovic","middleName":null,"title":"Mrs.","imageUrl":"https:\u002F\u002Fmts.intechopen.com\u002Fstorage\u002Fusers\u002F301331\u002Fimages\u002F8498_n.jpg","email":"mia.v@intechopen.com","biography":"As an Author Service Manager, my responsibilities include monitoring and facilitating all publishing activities for authors and editors. From chapter submission and review to approval and revision, copyediting and design, until final publication, I work closely with authors and editors to ensure a simple and easy publishing process. I maintain constant and effective communication with authors, editors and reviewers, which allows for a level of personal support that enables contributors to fully commit and concentrate on the chapters they are writing, editing, or reviewing. I assist authors in the preparation of their full chapter submissions and track important deadlines and ensure they are met. I help to coordinate internal processes such as linguistic review, and monitor the technical aspects of the process. As an ASM I am also involved in the acquisition of editors. Whether that be identifying an exceptional author and proposing an editorship collaboration, or contacting researchers who would like the opportunity to work with IntechOpen, I establish and help manage author and editor acquisition and contact."},"_preview":0},"regionStatistics":[{"id":"1","name":"Southern Europe","contributorCount":21370},{"id":"2","name":"Northern Europe","contributorCount":6960},{"id":"3","name":"Western Europe","contributorCount":10652},{"id":"4","name":"Northern America","contributorCount":17996},{"id":"5","name":"Eastern Asia","contributorCount":20252},{"id":"6","name":"Australia and New Zealand","contributorCount":2718}],"intechStatistics":{"openAccessBooks":"7,200","internationalAuthorsAndEditors":"192,000","downloads":"210M","deliversInCountries":"154","authorsAmongMostCitedScientists":"TOP 1%","authorsAndEditorsFromTopUniversities":"14%"}},"ofsBook_old1":{"item":{},"relatedBooks":[]},"chapter":{"item":{"type":"chapter","id":"83868","title":"Emulsion Stabilization with Lignosulfonates","doi":"10.5772\u002Fintechopen.107336","slug":"emulsion-stabilization-with-lignosulfonates","body":"\u003Cdiv class=\"section\" id=\"sec_1\" data-lvl=\"1\"\u003E\u003Ch2 class=\"heading main-title\"\u003E1. Introduction\u003C\u002Fh2\u003E\u003Cp id=\"p2\"\u003ELignosulfonates are biobased specialty chemicals, which are generated as a by-product during sulfite pulping of wood [\u003Ca href=\"#B1\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E1\u003C\u002Fa\u003E]. They are water-soluble polyelectrolytes, as they contain ionizable moieties such as sulfonate and carboxylic acid groups. Having preserved the polyaromatic backbone of lignin, they are functional amphiphiles with surfactant-like behavior. Due to their rich chemistry, lignosulfonates are found in many industrial applications [\u003Ca href=\"#B2\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E2\u003C\u002Fa\u003E]. This book chapter discusses the fundamentals of one of those applications, that is, emulsion stabilization. By explaining the working principles of interfacial adsorption and emulsion stabilization, the goal is to provide a reference for applied and fundamental research, as well as industry and potential end-users of lignosulfonates.\u003C\u002Fp\u003E\u003Cp id=\"p3\"\u003ENext to cellulose, lignin is considered the second most abundant and important polymeric compound in plants [\u003Ca href=\"#B1\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E1\u003C\u002Fa\u003E]. Here, it fulfills functions such as water-proofing the cell-walls and adding to the mechanical cohesion and strength. While wood may contain around 20–30% lignin, its abundance in aquatic and herbaceous angiosperms is generally less. In contrast to α-cellulose, lignin is an amorphous material with a randomly branched structure. This non-uniformity can make technical utilization challenging, as reactivity and availability of functional groups may vary [\u003Ca href=\"#B3\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E3\u003C\u002Fa\u003E]. Still, some applications may benefit from polydispersity. For specialty chemicals such as surfactants, it is the function or the effect that counts. Salinity changes may induce precipitation of an ionic surfactant. If the surfactant is polydisperse, precipitation may be limited to only a fraction of it. The remaining surfactant can then still perform the desired function. Moreover, mixtures of dissimilar surfactants can form synergies, where the performance may be superior over its individual components [\u003Ca href=\"#B4\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E4\u003C\u002Fa\u003E]. The application of lignin as specialty chemicals can thus benefit from its inherent characteristics, which includes its polydispersity. It is therefore not surprising that dispersants and surfactants are currently the dominant value-added applications of technical lignin.\u003C\u002Fp\u003E\u003Cp id=\"p4\"\u003EIt is frequently stated 50–70 million tons of technical lignin are produced per year, of which only 1–2% of are utilized for value-added products [\u003Ca href=\"#B5\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E5\u003C\u002Fa\u003E]. The majority is burned for heat and chemicals recovery in Kraft mills [\u003Ca href=\"#B6\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E6\u003C\u002Fa\u003E]. More than 1 million tons of lignosulfonates are produced annually [\u003Ca href=\"#B7\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E7\u003C\u002Fa\u003E], hence dominating the market of technical lignin. In contrast to many other lignin products, lignosulfonates are readily water-soluble. Their most common application is dispersants [\u003Ca href=\"#B8\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E8\u003C\u002Fa\u003E], for example as concrete plasticizers, drilling mud thinners, coal-slurry or dye dispersants [\u003Ca href=\"#B9\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E9\u003C\u002Fa\u003E]. Roughly 50% of the annual production of lignosulfonates were used for concrete admixtures in 1999 [\u003Ca href=\"#B10\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E10\u003C\u002Fa\u003E]. Other applications include dust binders, chelating and complexing agents, soil conditioning agents, floatation agents, and water-in-oil emulsion stabilizers [\u003Ca href=\"#B8\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E8\u003C\u002Fa\u003E, \u003Ca href=\"#B9\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E9\u003C\u002Fa\u003E, \u003Ca href=\"#B11\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E11\u003C\u002Fa\u003E, \u003Ca href=\"#B12\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E12\u003C\u002Fa\u003E]. As the effect on interfacial tension is limited, high shear is usually required during emulsification [\u003Ca href=\"#B13\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E13\u003C\u002Fa\u003E]. Still, lignosulfonates can yield emulsions that are stable over months and longer, finding application for example in agrochemical formulations [\u003Ca href=\"#B8\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E8\u003C\u002Fa\u003E]. Other potential areas with less commercial importance include corrosion and scale inhibitors, CO\u003Csub\u003E2\u003C\u002Fsub\u003E flooding and enhanced oil recovery, as well as polymer precursors and additives [\u003Ca href=\"#B2\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E2\u003C\u002Fa\u003E, \u003Ca href=\"#B14\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E14\u003C\u002Fa\u003E, \u003Ca href=\"#B15\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E15\u003C\u002Fa\u003E, \u003Ca href=\"#B16\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E16\u003C\u002Fa\u003E, \u003Ca href=\"#B17\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E17\u003C\u002Fa\u003E, \u003Ca href=\"#B18\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E18\u003C\u002Fa\u003E, \u003Ca href=\"#B19\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E19\u003C\u002Fa\u003E, \u003Ca href=\"#B20\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E20\u003C\u002Fa\u003E].\u003C\u002Fp\u003E\u003Cp id=\"p5\"\u003EGreat importance is attributed to biopolymers these days, as they are inherently renewable and largely biodegradable. By substituting fossil-based polymers with biopolymers, the transition to more sustainable technologies is furthered. Expanding the use of lignosulfonates is therefore an important piece in the puzzle. Compared to the global production of surfactants or pulp and paper products, lignosulfonates are currently a niche application. There is hence a potential for growth, in particular for applications that involve liquid–liquid interfaces.\u003C\u002Fp\u003E\u003C\u002Fdiv\u003E\u003Cdiv class=\"section\" id=\"sec_2\" data-lvl=\"1\"\u003E\u003Ch2 class=\"heading main-title\"\u003E2. Fundamentals\u003C\u002Fh2\u003E\u003Cdiv class=\"section\" id=\"sec_2_2\" data-lvl=\"2\"\u003E\u003Ch3 class=\"heading section-title\"\u003E2.1 Definitions and distinctions\u003C\u002Fh3\u003E\u003Cp id=\"p6\"\u003EThe term \u003Cstrong\u003E\u003Cbold xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" xmlns:xlink=\"http:\u002F\u002Fwww.w3.org\u002F1999\u002Fxlink\" xmlns:xsi=\"http:\u002F\u002Fwww.w3.org\u002F2001\u002FXMLSchema-instance\"\u003Elignin\u003C\u002Fbold\u003E\u003C\u002Fstrong\u003E is used for the natural lignin as found in lignocellulosic biomass. It is also referred to as pristine lignin, as no treatment or modification has been done. Chemically speaking, lignin is a biopolymer consisting of the monolignol units sinapyl alcohol (S), coniferyl alcohol (G), and \u003Cem\u003E\u003Citalic xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" xmlns:xlink=\"http:\u002F\u002Fwww.w3.org\u002F1999\u002Fxlink\" xmlns:xsi=\"http:\u002F\u002Fwww.w3.org\u002F2001\u002FXMLSchema-instance\"\u003Ep\u003C\u002Fitalic\u003E\u003C\u002Fem\u003E-coumaryl alcohol (H) [\u003Ca href=\"#B21\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E21\u003C\u002Fa\u003E], which are connected by various oxygen- and carbon–carbon linkages. Lignin has been described as a polyaromatic and randomly branched biopolymer.\u003C\u002Fp\u003E\u003Cp id=\"p7\"\u003E\u003Cstrong\u003E\u003Cbold xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" xmlns:xlink=\"http:\u002F\u002Fwww.w3.org\u002F1999\u002Fxlink\" xmlns:xsi=\"http:\u002F\u002Fwww.w3.org\u002F2001\u002FXMLSchema-instance\"\u003ETechnical lignin\u003C\u002Fbold\u003E\u003C\u002Fstrong\u003E refers to the lignin-rich product obtained from biomass separation processes. While pristine lignin is a virtually “infinite” network [\u003Ca href=\"#B22\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E22\u003C\u002Fa\u003E], technical lignin is a fragmentated version thereof. The molecular weight, composition, and ratio of functional groups of technical lignin are hence different. Their abundance can be affected by parameters such as biomass feedstock, separation process, and purification steps. Technical lignin usually has a purity of at least 70% (Klason lignin + acid soluble lignin), with commercial products being closer to 85–100% of lignin per ash-free dry matter.\u003C\u002Fp\u003E\u003Cp id=\"p8\"\u003E\u003Cstrong\u003E\u003Cbold xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" xmlns:xlink=\"http:\u002F\u002Fwww.w3.org\u002F1999\u002Fxlink\" xmlns:xsi=\"http:\u002F\u002Fwww.w3.org\u002F2001\u002FXMLSchema-instance\"\u003EPulping\u003C\u002Fbold\u003E\u003C\u002Fstrong\u003E of lignocellulose biomass is conducted to obtain a fibrous material. Approximately 90% of the global pulp products are made from wood, whereas 10% originate from annual plants [\u003Ca href=\"#B1\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E1\u003C\u002Fa\u003E]. Common end-products include paper, cardboard, molded pulp, and specialty cellulose. Mechanical pulping applies force in a refiner to defibrate the feedstock into fibers and fibrils. Chemical pulping dissolves the lignin and other substances to liberate the cellulose fibers. Industrial processes can also be based on a combination of mechanical and chemical treatments. Today, technical lignin most commonly originates from chemical pulping.\u003C\u002Fp\u003E\u003Cp id=\"p9\"\u003EA \u003Cstrong\u003E\u003Cbold xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" xmlns:xlink=\"http:\u002F\u002Fwww.w3.org\u002F1999\u002Fxlink\" xmlns:xsi=\"http:\u002F\u002Fwww.w3.org\u002F2001\u002FXMLSchema-instance\"\u003Ebiorefinery\u003C\u002Fbold\u003E\u003C\u002Fstrong\u003E is defined as “the sustainable processing of biomass into a spectrum of marketable products (food, feed, materials, chemicals) and energy (fuels, power, heat)” [\u003Ca href=\"#B23\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E23\u003C\u002Fa\u003E]. In other words, a biorefinery separates biomass into useful materials, chemicals, and energy. First generation biorefineries differ from second generation biorefineries by the choice of input material, i.e., food crops (first generation) instead of non-food crops (second generation) [\u003Ca href=\"#B24\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E24\u003C\u002Fa\u003E]. Pulping of wood is thus defined as a lignocellulosic crop, second generation biorefinery.\u003C\u002Fp\u003E\u003Cp id=\"p10\"\u003EAn overview of existing \u003Cstrong\u003E\u003Cbold xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" xmlns:xlink=\"http:\u002F\u002Fwww.w3.org\u002F1999\u002Fxlink\" xmlns:xsi=\"http:\u002F\u002Fwww.w3.org\u002F2001\u002FXMLSchema-instance\"\u003Ebiomass separation processes\u003C\u002Fbold\u003E\u003C\u002Fstrong\u003E with the resulting lignin product is given in \u003Ca href=\"#F1\" class=\"ref-link\" data-ref-style=\"fig\"\u003EFigure 1\u003C\u002Fa\u003E. Technical lignin has traditionally been obtained by chemical pulping, i.e., Kraft, sulfite, or soda pulping. Organosolv pulping is a more recent invention, which utilizes organic solvents and often acid catalysis for delignification [\u003Ca href=\"#B26\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E26\u003C\u002Fa\u003E]. The original goal of organosolv pulping was to obtain a fiber material. Still, this process has also attracted interest for biorefinery applications, which subsequently process the cellulose for chemical utilization [\u003Ca href=\"#B27\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E27\u003C\u002Fa\u003E]. The production of technical lignin can hence be conducted as part of a pulping processes, but it is not limited to that. An example for a non-pulping type lignin would be hydrolysis lignin, which is produced in biorefinery sugar platforms. Here, the cellulose and hemicellulose are hydrolyzed to extract sugar monomers and oligomers. The sugar can further be converted to higher value products, for example ethanol or furfural. The residual solids are rich in lignin and therefore termed hydrolysis lignin. Residual cellulose and other impurities can impart poorer performance and hence lower value on this lignin type [\u003Ca href=\"#B3\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E3\u003C\u002Fa\u003E, \u003Ca href=\"#B28\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E28\u003C\u002Fa\u003E]. Still, recent developments have yielded increased purity and reactivity, e.g., the Cellunolix\u003Csup\u003E®\u003C\u002Fsup\u003E lignin by St1 (Finnland) [\u003Ca href=\"#B29\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E29\u003C\u002Fa\u003E] or the Lignova™ lignin by Fibenol (Estonia) [\u003Ca href=\"#B30\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E30\u003C\u002Fa\u003E]. Because of these developments, it can be expected that hydrolysis lignin may play a larger role in the future. Steam explosion lignin is viewed as a separate category to hydrolysis lignin by some authors [\u003Ca href=\"#B3\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E3\u003C\u002Fa\u003E, \u003Ca href=\"#B31\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E31\u003C\u002Fa\u003E]. Yet, both lignin types are similar in composition and the treatments are sometimes even cascaded. Steam explosion treatment subjects the substrate to steam at elevated temperature (ca. 160–280°C) and pressure (ca. 7–48 bar) [\u003Ca href=\"#B32\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E32\u003C\u002Fa\u003E]. This induces biomass disintegration and partial hydrolysis. Due to this, it will be considered as part of hydrolysis lignin, as shown in \u003Ca href=\"#F1\" class=\"ref-link\" data-ref-style=\"fig\"\u003EFigure 1\u003C\u002Fa\u003E. Hydrolysis lignins can further be subdivided into acid hydrolysis lignin and enzymatic hydrolysis lignin, with the latter being more reactive due to a lower degree of condensation [\u003Ca href=\"#B3\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E3\u003C\u002Fa\u003E]. Recent advances have also yielded novel processes, which are still in an early stage of their development. Ionic liquids have been demonstrated to function as lignin solvents [\u003Ca href=\"#B33\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E33\u003C\u002Fa\u003E]. Combined with other treatments, ionic liquids can yield new products and conversion routes with promising features; however, some economic and technical challenges still need to be addressed [\u003Ca href=\"#B34\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E34\u003C\u002Fa\u003E]. Another recent invention is the use of supercritical solvents, e.g., supercritical water yielding products such as Aquasolv lignin [\u003Ca href=\"#B35\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E35\u003C\u002Fa\u003E].\u003C\u002Fp\u003E\u003Cfigure class=\"media-panel\" id=\"F1\"\u003E\u003Cdiv class=\"media\"\u003E\u003Cimg src=\"\u002F\u002Fcdnintech.com\u002Fmedia\u002Fchapter\u002F83868\u002F1680680847\u002Fmedia\u002FF1.png\" class=\"figure-link\" alt=\"\"\u003E\u003C\u002Fdiv\u003E\u003Cfigcaption class=\"caption\"\u003E\u003Ch4\u003EFigure 1.\u003C\u002Fh4\u003E\u003Cp\u003E\u003Cp xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" xmlns:xlink=\"http:\u002F\u002Fwww.w3.org\u002F1999\u002Fxlink\" xmlns:xsi=\"http:\u002F\u002Fwww.w3.org\u002F2001\u002FXMLSchema-instance\" id=\"p11\"\u003ELignin extraction processes and their dominant products. Modified from Laurichesse and Avérous [\u003Cxref rid=\"B25\" ref-type=\"bibr\"\u003E25\u003C\u002Fxref\u003E].\u003C\u002Fp\u003E\u003C\u002Fp\u003E\u003C\u002Ffigcaption\u003E\u003C\u002Ffigure\u003E\u003Cp id=\"p12\"\u003E\u003Cstrong\u003E\u003Cbold xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" xmlns:xlink=\"http:\u002F\u002Fwww.w3.org\u002F1999\u002Fxlink\" xmlns:xsi=\"http:\u002F\u002Fwww.w3.org\u002F2001\u002FXMLSchema-instance\"\u003ELignosulfonates\u003C\u002Fbold\u003E\u003C\u002Fstrong\u003E are traditionally extracted from sulfite spent liquors. Sulfite pulping is usually operated at low pH, but neutral or alkaline sulfite pulping have also been developed [\u003Ca href=\"#B1\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E1\u003C\u002Fa\u003E]. Sulfite liquors typically contain about 50–80% lignosulfonates, 30% hemicellulose and 10% inorganics per dry matter content [\u003Ca href=\"#B5\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E5\u003C\u002Fa\u003E]. Purification is often conducted by membrane filtration, removing low molecular weight components such as sugars. Commercial grade lignosulfonates are available in both purified and unpurified qualities. As a result of the pulping conditions, they also tend to exhibit a higher degree of condensation than, e.g., soda or organosolv lignin [\u003Ca href=\"#B3\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E3\u003C\u002Fa\u003E].\u003C\u002Fp\u003E\u003Cp id=\"p13\"\u003E\u003Cstrong\u003E\u003Cbold xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" xmlns:xlink=\"http:\u002F\u002Fwww.w3.org\u002F1999\u002Fxlink\" xmlns:xsi=\"http:\u002F\u002Fwww.w3.org\u002F2001\u002FXMLSchema-instance\"\u003ESulfonated lignin\u003C\u002Fbold\u003E\u003C\u002Fstrong\u003E is produced by chemical modification of lignin separated by a process other than sulfite pulping [\u003Ca href=\"#B2\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E2\u003C\u002Fa\u003E]. For example, MeadWestvaco produces Kraft lignin sulfonated with sulfite salts and an aldehyde, e.g., formaldehyde [\u003Ca href=\"#B5\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E5\u003C\u002Fa\u003E]. A variety of modification processes exist and the differences between lignosulfonates and sulfonated lignin can be marginal.\u003C\u002Fp\u003E\u003Cp id=\"p14\"\u003EThe \u003Cstrong\u003E\u003Cbold xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" xmlns:xlink=\"http:\u002F\u002Fwww.w3.org\u002F1999\u002Fxlink\" xmlns:xsi=\"http:\u002F\u002Fwww.w3.org\u002F2001\u002FXMLSchema-instance\"\u003Ecounterion\u003C\u002Fbold\u003E\u003C\u002Fstrong\u003E is the ion accompanying a second ionic species to maintain charge neutrality. Lignosulfonates contain covalently bond anionic moieties, which most importantly include sulfonate and carboxyl groups. A counter ion with positive charge is hence necessary for charge neutrality. This counterion is frequently a remnant of the pulping process, i.e., pulping with sodium, calcium or magnesium bisulfite will yield sodium, calcium, or magnesium lignosulfonates, respectively. Ion-exchange may also be conducted to replace the counterion. Protonation is furthermore possible, i.e., hydrogen as the counter ion. However, lignosulfonate dispersants are usually the salt of lignosulfonic acid, as this yields a more moderate pH and improves water-solubility.\u003C\u002Fp\u003E\u003Cp id=\"p15\"\u003EA \u003Cstrong\u003E\u003Cbold xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" xmlns:xlink=\"http:\u002F\u002Fwww.w3.org\u002F1999\u002Fxlink\" xmlns:xsi=\"http:\u002F\u002Fwww.w3.org\u002F2001\u002FXMLSchema-instance\"\u003Esurfactant\u003C\u002Fbold\u003E\u003C\u002Fstrong\u003E, i.e., surface-active agent, is a compound that can lower the surface or interfacial tension of a liquid in contact with another phase [\u003Ca href=\"#B36\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E36\u003C\u002Fa\u003E]. This effect is usually accompanied by adsorption at the surface or interface, i.e., enrichment at the phase boundary [\u003Ca href=\"#B37\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E37\u003C\u002Fa\u003E]. Surfactants usually contain hydrophilic and lipophilic moieties, which facilitate interfacial adsorption. Lignosulfonates have been shown to reduce the surface tension of water [\u003Ca href=\"#B38\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E38\u003C\u002Fa\u003E] and can hence be classified as surfactants.\u003C\u002Fp\u003E\u003Cp id=\"p16\"\u003E\u003Cstrong\u003E\u003Cbold xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" xmlns:xlink=\"http:\u002F\u002Fwww.w3.org\u002F1999\u002Fxlink\" xmlns:xsi=\"http:\u002F\u002Fwww.w3.org\u002F2001\u002FXMLSchema-instance\"\u003ESurface tension\u003C\u002Fbold\u003E\u003C\u002Fstrong\u003E can be observed as the tendency of a liquid surface to assume the smallest possible surface area. It is linked to the intermolecular attraction forces within the liquid and is commonly denoted as force per unit length or energy per unit area. Dispersing a liquid with high surface tension hence requires more energy than dispersing a liquid with low surface tension. In this chapter, the surface tension will be used when discussing liquid–gas phase boundaries.\u003C\u002Fp\u003E\u003Cp id=\"p17\"\u003EThe \u003Cstrong\u003E\u003Cbold xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" xmlns:xlink=\"http:\u002F\u002Fwww.w3.org\u002F1999\u002Fxlink\" xmlns:xsi=\"http:\u002F\u002Fwww.w3.org\u002F2001\u002FXMLSchema-instance\"\u003Einterfacial tension\u003C\u002Fbold\u003E\u003C\u002Fstrong\u003E is the equivalent to the surface tension at liquid–liquid interfaces. A system with low interfacial tension requires less work for emulsification than a system with high interfacial tension.\u003C\u002Fp\u003E\u003C\u002Fdiv\u003E\u003Cdiv class=\"section\" id=\"sec_3_2\" data-lvl=\"2\"\u003E\u003Ch3 class=\"heading section-title\"\u003E2.2 Production\u003C\u002Fh3\u003E\u003Cp id=\"p18\"\u003ELignosulfonates are produced as a by-product during sulfite pulping of wood [\u003Ca href=\"#B1\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E1\u003C\u002Fa\u003E]. Sulfite pulping is a long-established method for producing cellulosic fibers [\u003Ca href=\"#B39\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E39\u003C\u002Fa\u003E]. The process usually operates at low pH, utilizing sulfite or bisulfite salts to soften and remove the lignin. The lignin undergoes a number of reactions, which include [\u003Ca href=\"#B1\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E1\u003C\u002Fa\u003E]:\u003Cul\u003E\u003Cli\u003E\u003Cp id=\"p19\"\u003EHydrolysis\u003C\u002Fp\u003E\u003C\u002Fli\u003E\u003Cli\u003E\u003Cp id=\"p20\"\u003ESulfonation\u003C\u002Fp\u003E\u003C\u002Fli\u003E\u003Cli\u003E\u003Cp id=\"p21\"\u003ESulfitolysis\u003C\u002Fp\u003E\u003C\u002Fli\u003E\u003Cli\u003E\u003Cp id=\"p22\"\u003EDissolution\u003C\u002Fp\u003E\u003C\u002Fli\u003E\u003Cli\u003E\u003Cp id=\"p23\"\u003EDegradation\u003C\u002Fp\u003E\u003C\u002Fli\u003E\u003Cli\u003E\u003Cp id=\"p24\"\u003ECondensation\u003C\u002Fp\u003E\u003C\u002Fli\u003E\u003C\u002Ful\u003E\u003C\u002Fp\u003E\u003Cp id=\"p25\"\u003EDuring hydrolysis, the lignin-carbohydrate and, to a smaller extent, lignin-lignin linkages are broken down [\u003Ca href=\"#B1\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E1\u003C\u002Fa\u003E]. Sulfonation introduces sulfonate groups onto the lignin. When present in sufficient amounts, the sulfonate groups render the lignin water-soluble, which facilitates dissolution in the cooking liquor. Sulfitolysis and degradation may further reduce the molecular weight, whereas condensation reactions increase it. Condensation counteracts delignification by forming new carbon–carbon bonds [\u003Ca href=\"#B1\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E1\u003C\u002Fa\u003E].\u003C\u002Fp\u003E\u003Cp id=\"p26\"\u003ENatural lignin is synthesized from the three monolignols, i.e., sinapyl alcohol (S), coniferyl alcohol (G), and p-coumaryl alcohol (H) units [\u003Ca href=\"#B21\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E21\u003C\u002Fa\u003E]. Coniferous lignin (softwood lignin) is composed mainly of G-units, whereas lignin from broad-leaved trees (hardwood lignin) contains a mixture of G- and S-units [\u003Ca href=\"#B40\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E40\u003C\u002Fa\u003E]. Lignin from annual plants also contains H-units in addition to G- and S-units [\u003Ca href=\"#B41\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E41\u003C\u002Fa\u003E]. The feedstock therefore affects the composition of the resulting lignosulfonates, as the three monolignols vary in their methoxy content and potential branching. The feedstock can furthermore affect the pulping process, since sulfonation of hardwood lignin is slower than of softwood lignin [\u003Ca href=\"#B1\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E1\u003C\u002Fa\u003E]. Moreover, softwood lignin is more prone to condensation reactions, resulting in higher molecular weight as compared to hardwood lignosulfonates [\u003Ca href=\"#B42\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E42\u003C\u002Fa\u003E]. An overview of the monolignols and a schematic of softwood lignin is given in \u003Ca href=\"#F2\" class=\"ref-link\" data-ref-style=\"fig\"\u003EFigure 2\u003C\u002Fa\u003E.\u003C\u002Fp\u003E\u003Cfigure class=\"media-panel\" id=\"F2\"\u003E\u003Cdiv class=\"media\"\u003E\u003Cimg src=\"\u002F\u002Fcdnintech.com\u002Fmedia\u002Fchapter\u002F83868\u002F1680680847\u002Fmedia\u002FF2.png\" class=\"figure-link\" alt=\"\"\u003E\u003C\u002Fdiv\u003E\u003Cfigcaption class=\"caption\"\u003E\u003Ch4\u003EFigure 2.\u003C\u002Fh4\u003E\u003Cp\u003E\u003Cp xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" xmlns:xlink=\"http:\u002F\u002Fwww.w3.org\u002F1999\u002Fxlink\" xmlns:xsi=\"http:\u002F\u002Fwww.w3.org\u002F2001\u002FXMLSchema-instance\" id=\"p27\"\u003EPrimary lignin monomers and their corresponding units (left) [\u003Cxref rid=\"B25\" ref-type=\"bibr\"\u003E25\u003C\u002Fxref\u003E]. Schematic structure of softwood lignin (right) [\u003Cxref rid=\"B43\" ref-type=\"bibr\"\u003E43\u003C\u002Fxref\u003E].\u003C\u002Fp\u003E\u003C\u002Fp\u003E\u003C\u002Ffigcaption\u003E\u003C\u002Ffigure\u003E\u003Cp id=\"p28\"\u003EWhile alkali lignin can be separated by acid precipitation, this approach is not feasible for lignosulfonates. Instead, membrane filtration (ultrafiltration) is often conducted to purify the sulfite liquor [\u003Ca href=\"#B5\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E5\u003C\u002Fa\u003E]. Challenges can arise due to overlapping molecular weight of the lignosulfonates and dissolved hemicellulose. One approach is to cascade a series of membranes with different cut-off molecular weights [\u003Ca href=\"#B44\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E44\u003C\u002Fa\u003E]. An alternative is given by the Howard process [\u003Ca href=\"#B5\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E5\u003C\u002Fa\u003E], which uses lime (calcium oxide) to precipitate the lignosulfonate above pH 12 [\u003Ca href=\"#B45\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E45\u003C\u002Fa\u003E]. The precipitated solids can be separated mechanically and washed to improve the purity. Other potential approaches include amine extraction, electrolysis, ion-exchange resins, the Pekilo process (fermentation and ultrafiltration), and reverse osmosis [\u003Ca href=\"#B5\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E5\u003C\u002Fa\u003E].\u003C\u002Fp\u003E\u003Cp id=\"p29\"\u003ESeveral factors affect the composition of lignosulfonates, which include but are not limited to:\u003Cul\u003E\u003Cli\u003E\u003Cp id=\"p30\"\u003EThe choice of raw material, e.g., softwood or hardwood, affecting the monolignol composition\u003C\u002Fp\u003E\u003C\u002Fli\u003E\u003Cli\u003E\u003Cp id=\"p31\"\u003EThe choice of pulping chemicals\u003C\u002Fp\u003E\u003C\u002Fli\u003E\u003Cli\u003E\u003Cp id=\"p32\"\u003EThe pulping conditions\u003C\u002Fp\u003E\u003C\u002Fli\u003E\u003Cli\u003E\u003Cp id=\"p33\"\u003ERecovery and purification\u003C\u002Fp\u003E\u003C\u002Fli\u003E\u003Cli\u003E\u003Cp id=\"p34\"\u003EPost-treatment and chemical modification\u003C\u002Fp\u003E\u003C\u002Fli\u003E\u003C\u002Ful\u003E\u003C\u002Fp\u003E\u003Cp id=\"p35\"\u003EThe composition of lignosulfonates is inherently linked to its characteristics and behavior, and hence to the performance in technical applications [\u003Ca href=\"#B2\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E2\u003C\u002Fa\u003E].\u003C\u002Fp\u003E\u003C\u002Fdiv\u003E\u003Cdiv class=\"section\" id=\"sec_4_2\" data-lvl=\"2\"\u003E\u003Ch3 class=\"heading section-title\"\u003E2.3 Structure and composition\u003C\u002Fh3\u003E\u003Cp id=\"p36\"\u003EAs discussed in the previous chapter, the structure and composition of lignosulfonates is strongly dependent on their origin and production. Still, there are certain characteristics that are worth discussing.\u003C\u002Fp\u003E\u003Cp id=\"p37\"\u003EDue to their structure and monomeric configuration, cellulose and hemicellulose contain a higher percentage of oxygen than lignin. Lignin furthermore has the highest carbon content of these three biopolymers. A unique feature of lignosulfonates is their elevated sulfur content, which arises from the pulping process. \u003Ca href=\"#tab1\" class=\"ref-link\" data-ref-style=\"table\"\u003ETable 1\u003C\u002Fa\u003E lists a range of elementary composition, as published in current literature. It should be mentioned that these values should only be taken as indicators, since individual samples may be different. In particular, the ash content may exhibit values up to 40 wt.%. Still, an elevated oxygen content and lower carbon content can in theory indicate lower purity, as the contributions from cellulose and hemicellulose would be greater.\u003C\u002Fp\u003E\u003Cdiv class=\"table-wrap\" id=\"tab1\"\u003E\u003Cdiv class=\"table-content\"\u003E\u003Ctable frame=\"hsides\" rules=\"groups\"\u003E\u003Ccol\u003E\u003Ccol\u003E\u003Ccol\u003E\u003Cthead\u003E\u003Ctr\u003E\u003Cth\u003EParameter\u003C\u002Fth\u003E\u003Cth align=\"center\"\u003EApproximate content in wt.%\u003C\u002Fth\u003E\u003Cth align=\"center\"\u003EReference\u003C\u002Fth\u003E\u003C\u002Ftr\u003E\u003C\u002Fthead\u003E\u003Ctbody\u003E\u003Ctr\u003E\u003Ctd\u003EDry matter\u003C\u002Ftd\u003E\u003Ctd align=\"center\"\u003E94–96\u003C\u002Ftd\u003E\u003Ctd align=\"center\"\u003E[\u003Ca href=\"#B46\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E46\u003C\u002Fa\u003E]\u003C\u002Ftd\u003E\u003C\u002Ftr\u003E\u003Ctr\u003E\u003Ctd\u003EAsh\u003C\u002Ftd\u003E\u003Ctd align=\"center\"\u003E4–10\u003C\u002Ftd\u003E\u003Ctd align=\"center\"\u003E[\u003Ca href=\"#B3\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E3\u003C\u002Fa\u003E, \u003Ca href=\"#B47\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E47\u003C\u002Fa\u003E]\u003C\u002Ftd\u003E\u003C\u002Ftr\u003E\u003Ctr\u003E\u003Ctd\u003ECarbon\u003C\u002Ftd\u003E\u003Ctd align=\"center\"\u003E29–47\u003C\u002Ftd\u003E\u003Ctd align=\"center\"\u003E[\u003Ca href=\"#B48\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E48\u003C\u002Fa\u003E, \u003Ca href=\"#B49\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E49\u003C\u002Fa\u003E, \u003Ca href=\"#B50\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E50\u003C\u002Fa\u003E]\u003C\u002Ftd\u003E\u003C\u002Ftr\u003E\u003Ctr\u003E\u003Ctd\u003EHydrogen\u003C\u002Ftd\u003E\u003Ctd align=\"center\"\u003E5\u003C\u002Ftd\u003E\u003Ctd align=\"center\"\u003E[\u003Ca href=\"#B48\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E48\u003C\u002Fa\u003E, \u003Ca href=\"#B50\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E50\u003C\u002Fa\u003E]\u003C\u002Ftd\u003E\u003C\u002Ftr\u003E\u003Ctr\u003E\u003Ctd\u003EOxygen\u003C\u002Ftd\u003E\u003Ctd align=\"center\"\u003E37–54\u003C\u002Ftd\u003E\u003Ctd align=\"center\"\u003E[\u003Ca href=\"#B48\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E48\u003C\u002Fa\u003E, \u003Ca href=\"#B49\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E49\u003C\u002Fa\u003E, \u003Ca href=\"#B50\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E50\u003C\u002Fa\u003E]\u003C\u002Ftd\u003E\u003C\u002Ftr\u003E\u003Ctr\u003E\u003Ctd\u003ESulfur\u003C\u002Ftd\u003E\u003Ctd align=\"center\"\u003E2–10\u003C\u002Ftd\u003E\u003Ctd align=\"center\"\u003E[\u003Ca href=\"#B46\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E46\u003C\u002Fa\u003E]\u003C\u002Ftd\u003E\u003C\u002Ftr\u003E\u003Ctr\u003E\u003Ctd\u003ENitrogen\u003C\u002Ftd\u003E\u003Ctd align=\"center\"\u003E0.02\u003C\u002Ftd\u003E\u003Ctd align=\"center\"\u003E[\u003Ca href=\"#B3\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E3\u003C\u002Fa\u003E]\u003C\u002Ftd\u003E\u003C\u002Ftr\u003E\u003C\u002Ftbody\u003E\u003C\u002Ftable\u003E\u003C\u002Fdiv\u003E\u003Cdiv class=\"table-caption\"\u003E\u003Ch3 class=\"heading\"\u003ETable 1.\u003C\u002Fh3\u003E\u003Cdiv class=\"text\"\u003E\u003Cp id=\"p38\"\u003EApproximate elementary composition of lignosulfonates.\u003C\u002Fp\u003E\u003C\u002Fdiv\u003E\u003Cdiv class=\"text\"\u003E\u003C\u002Fdiv\u003E\u003C\u002Fdiv\u003E\u003C\u002Fdiv\u003E\u003Cp id=\"p39\"\u003EThe chemical structure of lignosulfonates mirrors that of both native lignin and the modifications done during sulfite pulping. As such, the skeletal configuration of lignin is preserved to some extent, while new carbon–carbon linkages have been formed. In addition, sulfonate and carboxylic acid groups were added, which are not found in native lignin to this extent. Generic structure models of lignosulfonates are shown in \u003Ca href=\"#F3\" class=\"ref-link\" data-ref-style=\"fig\"\u003EFigure 3\u003C\u002Fa\u003E. It is important to note that these are only approximate models, as lignosulfonates are a polydisperse mixture of many different macromolecules. The structure hence varies not only between different lignosulfonates, but also within a given sample. In other words, lignosulfonates should be considered statistical entities rather than classical chemical compounds [\u003Ca href=\"#B53\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E53\u003C\u002Fa\u003E].\u003C\u002Fp\u003E\u003Cfigure class=\"media-panel\" id=\"F3\"\u003E\u003Cdiv class=\"media\"\u003E\u003Cimg src=\"\u002F\u002Fcdnintech.com\u002Fmedia\u002Fchapter\u002F83868\u002F1680680847\u002Fmedia\u002FF3.png\" class=\"figure-link\" alt=\"\"\u003E\u003C\u002Fdiv\u003E\u003Cfigcaption class=\"caption\"\u003E\u003Ch4\u003EFigure 3.\u003C\u002Fh4\u003E\u003Cp\u003E\u003Cp xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" xmlns:xlink=\"http:\u002F\u002Fwww.w3.org\u002F1999\u002Fxlink\" xmlns:xsi=\"http:\u002F\u002Fwww.w3.org\u002F2001\u002FXMLSchema-instance\" id=\"p40\"\u003EGeneric (simplified) structure of lignosulfonates according to Kun and Pukanszky [\u003Cxref rid=\"B51\" ref-type=\"bibr\"\u003E51\u003C\u002Fxref\u003E] (left), and Fiorani et al. [\u003Cxref rid=\"B52\" ref-type=\"bibr\"\u003E52\u003C\u002Fxref\u003E] (right).\u003C\u002Fp\u003E\u003C\u002Fp\u003E\u003C\u002Ffigcaption\u003E\u003C\u002Ffigure\u003E\u003Cp id=\"p41\"\u003EThe chemical moieties of lignosulfonates can be categorized into ionizable, polar and non-polar groups [\u003Ca href=\"#B2\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E2\u003C\u002Fa\u003E]. Ionizable groups include sulfonate, carboxylic acid, and phenolic hydroxyl groups. At a neutral pH of 7, mainly the first two can be considered dissociated (ionized) and hence hydrophilic. Phenolic hydroxyl groups are usually ionized at around pH 9–10 [\u003Ca href=\"#B54\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E54\u003C\u002Fa\u003E, \u003Ca href=\"#B55\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E55\u003C\u002Fa\u003E], but values extending to pH 5–12 have been reported [\u003Ca href=\"#B56\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E56\u003C\u002Fa\u003E]. Polar groups include various oxygen containing moieties due to the higher dipole moment of oxygen–carbon and oxygen-hydrogen linkages. These include ketones, aldehydes, and methoxy groups. Despite being polar, these groups are not considered operative hydrophilic groups [\u003Ca href=\"#B57\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E57\u003C\u002Fa\u003E]. Aliphatic hydroxyl and ether groups are also present to a great extent in lignosulfonates. These can be intrinsically hydrophilic; however, their functionality is determined by the surrounding molecular structure [\u003Ca href=\"#B57\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E57\u003C\u002Fa\u003E, \u003Ca href=\"#B58\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E58\u003C\u002Fa\u003E, \u003Ca href=\"#B59\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E59\u003C\u002Fa\u003E]. Because of this, the water-solubility of lignosulfonates arises from the presence of ionizable groups, i.e., sulfonate and carboxyl groups at neutral pH. Nonpolar groups include aromatic and aliphatic units, as found in the skeletal configuration of lignin. An overview of the common functional groups and linkages is given in \u003Ca href=\"#F4\" class=\"ref-link\" data-ref-style=\"fig\"\u003EFigure 4\u003C\u002Fa\u003E. This overview does not include additional functionalities, which may be grafted onto the lignosulfonates, e.g., by phosphorylation, alkylation, sulfobutylation or silylation [\u003Ca href=\"#B60\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E60\u003C\u002Fa\u003E].\u003C\u002Fp\u003E\u003Cfigure class=\"media-panel\" id=\"F4\"\u003E\u003Cdiv class=\"media\"\u003E\u003Cimg src=\"\u002F\u002Fcdnintech.com\u002Fmedia\u002Fchapter\u002F83868\u002F1680680847\u002Fmedia\u002FF4.png\" class=\"figure-link\" alt=\"\"\u003E\u003C\u002Fdiv\u003E\u003Cfigcaption class=\"caption\"\u003E\u003Ch4\u003EFigure 4.\u003C\u002Fh4\u003E\u003Cp\u003E\u003Cp xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" xmlns:xlink=\"http:\u002F\u002Fwww.w3.org\u002F1999\u002Fxlink\" xmlns:xsi=\"http:\u002F\u002Fwww.w3.org\u002F2001\u002FXMLSchema-instance\" id=\"p42\"\u003ECommonly encountered chemical bounds and functional groups in technical lignin. Image taken from [\u003Cxref rid=\"B2\" ref-type=\"bibr\"\u003E2\u003C\u002Fxref\u003E].\u003C\u002Fp\u003E\u003C\u002Fp\u003E\u003C\u002Ffigcaption\u003E\u003C\u002Ffigure\u003E\u003Cp id=\"p43\"\u003EThe abundance of functional groups can be of interest for two reasons. Firstly, this is an important parameter for chemical modification, as specific functional groups may be targeted. Secondly, the physicochemical properties of lignosulfonates are highly dependent on their composition. Hydrophobic interaction chromatography (HIC) has played an important role in characterizing lignosulfonates recently [\u003Ca href=\"#B61\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E61\u003C\u002Fa\u003E, \u003Ca href=\"#B62\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E62\u003C\u002Fa\u003E, \u003Ca href=\"#B63\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E63\u003C\u002Fa\u003E]. Based on this technique, the charge-to-size ratio was reportedly lower for more hydrophobic lignosulfonates [\u003Ca href=\"#B64\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E64\u003C\u002Fa\u003E]. Better performance as suspension or emulsion stabilizer was furthermore seen for more hydrophobic lignosulfonates [\u003Ca href=\"#B13\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E13\u003C\u002Fa\u003E, \u003Ca href=\"#B63\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E63\u003C\u002Fa\u003E]. This example illustrates, how the abundance of functional groups may impact the performance in technical applications.\u003C\u002Fp\u003E\u003Cp id=\"p44\"\u003ECompared to other technical lignins, lignosulfonates tend to exhibit a lower amount of phenolic hydroxyl groups [\u003Ca href=\"#B47\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E47\u003C\u002Fa\u003E]. While the sulfonate group is a distinct feature of lignosulfonates, the abundance of carboxylic acid groups is comparable to that of other technical lignins. A recent study was performed aqueous carbon black dispersions stabilized by sodium lignosulfonate, which also listed the composition of six commercial samples [\u003Ca href=\"#B46\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E46\u003C\u002Fa\u003E]. The values are summarized in \u003Ca href=\"#tab2\" class=\"ref-link\" data-ref-style=\"table\"\u003ETable 2\u003C\u002Fa\u003E. As all samples were of softwood origin, a higher methoxy content can be expected for hardwood lignosulfonates due to the monolignol composition.\u003C\u002Fp\u003E\u003Cdiv class=\"table-wrap\" id=\"tab2\"\u003E\u003Cdiv class=\"table-content\"\u003E\u003Ctable frame=\"hsides\" rules=\"groups\"\u003E\u003Ccol\u003E\u003Ccol\u003E\u003Cthead\u003E\u003Ctr\u003E\u003Cth\u003EParameter\u003C\u002Fth\u003E\u003Cth align=\"center\"\u003EApproximate range\u003C\u002Fth\u003E\u003C\u002Ftr\u003E\u003C\u002Fthead\u003E\u003Ctbody\u003E\u003Ctr\u003E\u003Ctd\u003EM\u003Csub\u003Ew\u003C\u002Fsub\u003E in g\u002Fmol\u003C\u002Ftd\u003E\u003Ctd align=\"center\"\u003E1800–4000\u003C\u002Ftd\u003E\u003C\u002Ftr\u003E\u003Ctr\u003E\u003Ctd\u003EM\u003Csub\u003En\u003C\u002Fsub\u003E in g\u002Fmol\u003C\u002Ftd\u003E\u003Ctd align=\"center\"\u003E6000–330,000\u003C\u002Ftd\u003E\u003C\u002Ftr\u003E\u003Ctr\u003E\u003Ctd\u003EPolydispersity index\u003C\u002Ftd\u003E\u003Ctd align=\"center\"\u003E3–83\u003C\u002Ftd\u003E\u003C\u002Ftr\u003E\u003Ctr\u003E\u003Ctd\u003EOrganic sulfur (wt.%)\u003C\u002Ftd\u003E\u003Ctd align=\"center\"\u003E2.1–9.4\u003C\u002Ftd\u003E\u003C\u002Ftr\u003E\u003Ctr\u003E\u003Ctd\u003ECarboxyl groups (wt.%)\u003C\u002Ftd\u003E\u003Ctd align=\"center\"\u003E8.3–14.9\u003C\u002Ftd\u003E\u003C\u002Ftr\u003E\u003Ctr\u003E\u003Ctd\u003EPhenolic hydroxyl groups (wt.%)\u003C\u002Ftd\u003E\u003Ctd align=\"center\"\u003E1.3–2.0\u003C\u002Ftd\u003E\u003C\u002Ftr\u003E\u003Ctr\u003E\u003Ctd\u003EMethoxy groups (wt.%)\u003C\u002Ftd\u003E\u003Ctd align=\"center\"\u003E7.3–15.4\u003C\u002Ftd\u003E\u003C\u002Ftr\u003E\u003C\u002Ftbody\u003E\u003C\u002Ftable\u003E\u003C\u002Fdiv\u003E\u003Cdiv class=\"table-caption\"\u003E\u003Ch3 class=\"heading\"\u003ETable 2.\u003C\u002Fh3\u003E\u003Cdiv class=\"text\"\u003E\u003Cp id=\"p45\"\u003EAbundance of functional groups of softwood sodium lignosulfonates according to Subramanian et al. [\u003Ca href=\"#B46\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E46\u003C\u002Fa\u003E].\u003C\u002Fp\u003E\u003C\u002Fdiv\u003E\u003Cdiv class=\"text\"\u003E\u003C\u002Fdiv\u003E\u003C\u002Fdiv\u003E\u003C\u002Fdiv\u003E\u003Cp id=\"p46\"\u003E\u003Ca href=\"#tab2\" class=\"ref-link\" data-ref-style=\"table\"\u003ETable 2\u003C\u002Fa\u003E also lists the number-average (M\u003Csub\u003En\u003C\u002Fsub\u003E) and mass-average molecular weight (M\u003Csub\u003Ew\u003C\u002Fsub\u003E). A polydispersity index of up to 83 accounts for a great variety in molecular mass, which is characteristic for lignin from sulfite pulping. The molecular weight can have several implications on the properties of lignosulfonates. It is naturally linked to the diffusion coefficient [\u003Ca href=\"#B65\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E65\u003C\u002Fa\u003E], which will further affect interfacial adsorption and related phenomena [\u003Ca href=\"#B13\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E13\u003C\u002Fa\u003E, \u003Ca href=\"#B66\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E66\u003C\u002Fa\u003E]. Research has shown that the degree of sulfonation decreases with increasing molecular weight [\u003Ca href=\"#B67\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E67\u003C\u002Fa\u003E]. Stearic screening can occur in lignosulfonates with high molecular weight [\u003Ca href=\"#B3\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E3\u003C\u002Fa\u003E]. This effect was used to explain, e.g., the lower effect on zeta potential by shielding ionizable groups [\u003Ca href=\"#B68\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E68\u003C\u002Fa\u003E] or the lower reactivity by screening of phenolic hydroxyl groups [\u003Ca href=\"#B3\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E3\u003C\u002Fa\u003E]. Overall, the molecular weight of lignosulfonates may span from less than 1000 g\u002Fmol to more than 400,000 g\u002Fmol [\u003Ca href=\"#B42\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E42\u003C\u002Fa\u003E, \u003Ca href=\"#B67\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E67\u003C\u002Fa\u003E]. The molecular weight ranges are thus higher than for other technical lignins [\u003Ca href=\"#B2\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E2\u003C\u002Fa\u003E]. In comparison, values of (1000–15,000 g\u002Fmol) have been reported for soda lignin, 1500–25,000 g\u002Fmol for Kraft lignin, and 500–5000 g\u002Fmol for organosolv lignin [\u003Ca href=\"#B3\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E3\u003C\u002Fa\u003E]. Acid hydrolysis lignin is closer to lignosulfonates in terms of molecular weight, where values of 1500–50,000 g\u002Fmol have been reported [\u003Ca href=\"#B69\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E69\u003C\u002Fa\u003E]. The molecular weight distribution of various lignosulfonates is illustrated in \u003Ca href=\"#F5\" class=\"ref-link\" data-ref-style=\"fig\"\u003EFigure 5\u003C\u002Fa\u003E. As can be seen, the molecular weight of the hardwood samples was consistently lower than that of softwood lignosulfonates. This difference is likely the result of the monolignol configuration, which can further affect the sulfite pulping process.\u003C\u002Fp\u003E\u003Cfigure class=\"media-panel\" id=\"F5\"\u003E\u003Cdiv class=\"media\"\u003E\u003Cimg src=\"\u002F\u002Fcdnintech.com\u002Fmedia\u002Fchapter\u002F83868\u002F1680680847\u002Fmedia\u002FF5.png\" class=\"figure-link\" alt=\"\"\u003E\u003C\u002Fdiv\u003E\u003Cfigcaption class=\"caption\"\u003E\u003Ch4\u003EFigure 5.\u003C\u002Fh4\u003E\u003Cp\u003E\u003Cp xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" xmlns:xlink=\"http:\u002F\u002Fwww.w3.org\u002F1999\u002Fxlink\" xmlns:xsi=\"http:\u002F\u002Fwww.w3.org\u002F2001\u002FXMLSchema-instance\" id=\"p47\"\u003EMolecular weight distribution of lignosulfonates originating from spruce [LS1 (&diams;), LS2 (▀) and LS3 (+)], a spruce-birch blend [LS5 (▲)], aspen [LS6 (*)], and eucalyptus [LS7 (●) and LS8 (×)]. Image taken from [\u003Cxref rid=\"B42\" ref-type=\"bibr\"\u003E42\u003C\u002Fxref\u003E].\u003C\u002Fp\u003E\u003C\u002Fp\u003E\u003C\u002Ffigcaption\u003E\u003C\u002Ffigure\u003E\u003C\u002Fdiv\u003E\u003C\u002Fdiv\u003E\u003Cdiv class=\"section\" id=\"sec_6\" data-lvl=\"1\"\u003E\u003Ch2 class=\"heading main-title\"\u003E3. Adsorption on surfaces and interfaces\u003C\u002Fh2\u003E\u003Cdiv class=\"section\" id=\"sec_6_2\" data-lvl=\"2\"\u003E\u003Ch3 class=\"heading section-title\"\u003E3.1 Adsorption\u003C\u002Fh3\u003E\u003Cp id=\"p48\"\u003EIt is generally agreed that adsorption of lignosulfonates follows the Langmuir isotherm [\u003Ca href=\"#B70\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E70\u003C\u002Fa\u003E, \u003Ca href=\"#B71\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E71\u003C\u002Fa\u003E, \u003Ca href=\"#B72\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E72\u003C\u002Fa\u003E, \u003Ca href=\"#B73\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E73\u003C\u002Fa\u003E]. The according framework was first published by Irving Langmuir in 1916, which described the adsorption of gasses on solids [\u003Ca href=\"#B74\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E74\u003C\u002Fa\u003E]. A common expression of the Langmuir equation is given in \u003Ca href=\"#E1\" class=\"ref-link\" data-ref-style=\"disp-formula\"\u003EEq. (1)\u003C\u002Fa\u003E, were \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m1\"\u003E\u003Cmml:mi mathvariant=\"normal\"\u003EΓ\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E corresponds to the amount of adsorbed species, \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m2\"\u003E\u003Cmml:msub\u003E\u003Cmml:mi mathvariant=\"normal\"\u003EΓ\u003C\u002Fmml:mi\u003E\u003Cmml:mi\u003Emax\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:msub\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E is the maximum amount adsorbed, \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m3\"\u003E\u003Cmml:mi\u003Ec\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E is the concentration of adsorbing species in bulk, and \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m4\"\u003E\u003Cmml:mi\u003EK\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E is the Langmuir equilibrium constant.\u003C\u002Fp\u003E\u003Cdiv id=\"df_E1\" class=\"formula panel\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m5\" specific-use=\"web-only\"\u003E\u003Cmml:mi mathvariant=\"normal\"\u003EΓ\u003C\u002Fmml:mi\u003E\u003Cmml:mo\u003E=\u003C\u002Fmml:mo\u003E\u003Cmml:mfrac\u003E\u003Cmml:mrow\u003E\u003Cmml:msub\u003E\u003Cmml:mi mathvariant=\"normal\"\u003EΓ\u003C\u002Fmml:mi\u003E\u003Cmml:mi\u003Emax\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:msub\u003E\u003Cmml:mi mathvariant=\"italic\"\u003EKc\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:mrow\u003E\u003Cmml:mrow\u003E\u003Cmml:mn\u003E1\u003C\u002Fmml:mn\u003E\u003Cmml:mo\u003E+\u003C\u002Fmml:mo\u003E\u003Cmml:mi mathvariant=\"italic\"\u003EKc\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:mrow\u003E\u003C\u002Fmml:mfrac\u003E\u003C\u002Fmml:math\u003E\u003Cspan class=\"equ\"\u003EE1\u003C\u002Fspan\u003E\u003C\u002Fdiv\u003E\u003Cp id=\"p49\"\u003EThe parameters \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m6\"\u003E\u003Cmml:msub\u003E\u003Cmml:mi mathvariant=\"normal\"\u003EΓ\u003C\u002Fmml:mi\u003E\u003Cmml:mi\u003Emax\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:msub\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E and \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m7\"\u003E\u003Cmml:mi\u003EK\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E can be determined via mass-balancing, i.e., measuring the adsorbed amount in dependence of concentration. This approach is simple for adsorption on solid surfaces, as the amount of non-adsorbing surfactant is equivalent to the remaining bulk concentration. An example for the adsorption of lignosulfonates on carbon black is given in \u003Ca href=\"#F6\" class=\"ref-link\" data-ref-style=\"fig\"\u003EFigure 6\u003C\u002Fa\u003E. The characteristic behavior accompanying Langmuir adsorption isotherms is a sharp increase of adsorbed amount at low concentrations, whereas higher concentrations yield a plateau.\u003C\u002Fp\u003E\u003Cfigure class=\"media-panel\" id=\"F6\"\u003E\u003Cdiv class=\"media\"\u003E\u003Cimg src=\"\u002F\u002Fcdnintech.com\u002Fmedia\u002Fchapter\u002F83868\u002F1680680847\u002Fmedia\u002FF6.png\" class=\"figure-link\" alt=\"\"\u003E\u003C\u002Fdiv\u003E\u003Cfigcaption class=\"caption\"\u003E\u003Ch4\u003EFigure 6.\u003C\u002Fh4\u003E\u003Cp\u003E\u003Cp xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" xmlns:xlink=\"http:\u002F\u002Fwww.w3.org\u002F1999\u002Fxlink\" xmlns:xsi=\"http:\u002F\u002Fwww.w3.org\u002F2001\u002FXMLSchema-instance\" id=\"p50\"\u003EAdsorption isotherm of lignosulfonate on 1 wt% carbon black along with Langmuir isotherm fitting. Image taken from [\u003Cxref rid=\"B46\" ref-type=\"bibr\"\u003E46\u003C\u002Fxref\u003E].\u003C\u002Fp\u003E\u003C\u002Fp\u003E\u003C\u002Ffigcaption\u003E\u003C\u002Ffigure\u003E\u003Cp id=\"p51\"\u003EDetermination of the Langmuir equation parameters to liquid–liquid systems is less straight forward than for liquid–solid dispersions. Emulsification is accompanied by an increase in specific surface area, which can be difficult to quantify. The surface or interfacial tension can be used instead of mass-balancing. Langmuir type adsorption implies the applicability of the Szyszkowski equation, as given in \u003Ca href=\"#E2\" class=\"ref-link\" data-ref-style=\"disp-formula\"\u003EEq. (2)\u003C\u002Fa\u003E. Here, the surface pressure \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m8\"\u003E\u003Cmml:mi mathvariant=\"normal\"\u003EΠ\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E is calculated as the difference of surface or interfacial tension without surfactant (\u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m9\"\u003E\u003Cmml:msub\u003E\u003Cmml:mi\u003Eγ\u003C\u002Fmml:mi\u003E\u003Cmml:mn\u003E0\u003C\u002Fmml:mn\u003E\u003C\u002Fmml:msub\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E) and at concentration \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m10\"\u003E\u003Cmml:mi\u003Ec\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E (\u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m11\"\u003E\u003Cmml:mi\u003Eγ\u003C\u002Fmml:mi\u003E\u003Cmml:mfenced open=\"(\" close=\")\"\u003E\u003Cmml:mi\u003Ec\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:mfenced\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E). The equation further involves the temperature \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m12\"\u003E\u003Cmml:mi\u003ET\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E, the ideal gas constant \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m13\"\u003E\u003Cmml:mi\u003ER\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E, and the constant \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m14\"\u003E\u003Cmml:mi\u003En\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E.\u003C\u002Fp\u003E\u003Cdiv id=\"df_E2\" class=\"formula panel\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m15\" specific-use=\"web-only\"\u003E\u003Cmml:mi mathvariant=\"normal\"\u003EΠ\u003C\u002Fmml:mi\u003E\u003Cmml:mo\u003E=\u003C\u002Fmml:mo\u003E\u003Cmml:msub\u003E\u003Cmml:mi\u003Eγ\u003C\u002Fmml:mi\u003E\u003Cmml:mn\u003E0\u003C\u002Fmml:mn\u003E\u003C\u002Fmml:msub\u003E\u003Cmml:mo\u003E−\u003C\u002Fmml:mo\u003E\u003Cmml:mi\u003Eγ\u003C\u002Fmml:mi\u003E\u003Cmml:mfenced open=\"(\" close=\")\"\u003E\u003Cmml:mi\u003Ec\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:mfenced\u003E\u003Cmml:mo\u003E=\u003C\u002Fmml:mo\u003E\u003Cmml:mi\u003En\u003C\u002Fmml:mi\u003E\u003Cmml:mi\u003ERT\u003C\u002Fmml:mi\u003E\u003Cmml:msub\u003E\u003Cmml:mi mathvariant=\"normal\"\u003EΓ\u003C\u002Fmml:mi\u003E\u003Cmml:mi\u003Em\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:msub\u003E\u003Cmml:mo\u003Eln\u003C\u002Fmml:mo\u003E\u003Cmml:mfenced open=\"(\" close=\")\"\u003E\u003Cmml:mrow\u003E\u003Cmml:mn\u003E1\u003C\u002Fmml:mn\u003E\u003Cmml:mo\u003E+\u003C\u002Fmml:mo\u003E\u003Cmml:mi mathvariant=\"italic\"\u003EKc\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:mrow\u003E\u003C\u002Fmml:mfenced\u003E\u003C\u002Fmml:math\u003E\u003Cspan class=\"equ\"\u003EE2\u003C\u002Fspan\u003E\u003C\u002Fdiv\u003E\u003Cp id=\"p52\"\u003EThe surface excess \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m16\"\u003E\u003Cmml:msub\u003E\u003Cmml:mi mathvariant=\"normal\"\u003EΓ\u003C\u002Fmml:mi\u003E\u003Cmml:mi\u003Em\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:msub\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E can further be determined using the Gibbs adsorption isotherm. As stated in \u003Ca href=\"#E3\" class=\"ref-link\" data-ref-style=\"disp-formula\"\u003EEq. (3)\u003C\u002Fa\u003E, this framework relies on the linear-logarithmic progression of surface tension \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m17\"\u003E\u003Cmml:mi\u003Eγ\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E with concentration \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m18\"\u003E\u003Cmml:mi\u003Ec\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E. It is important to note that the linear-logarithmic regime does not span over the entire concentration range. At low surfactant concentrations, the surface or interfacial tension approaches the surfactant-free case \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m19\"\u003E\u003Cmml:msub\u003E\u003Cmml:mi\u003Eγ\u003C\u002Fmml:mi\u003E\u003Cmml:mn\u003E0\u003C\u002Fmml:mn\u003E\u003C\u002Fmml:msub\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E asymptotically. At high lignosulfonate concentrations, agglomeration and other effects will decrease the observed slope [\u003Ca href=\"#B38\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E38\u003C\u002Fa\u003E, \u003Ca href=\"#B75\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E75\u003C\u002Fa\u003E]. A more detailed discussion of the surface and interfacial tension of lignosulfonates is given in Section 3.2.\u003C\u002Fp\u003E\u003Cdiv id=\"df_E3\" class=\"formula panel\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m20\" specific-use=\"web-only\"\u003E\u003Cmml:msub\u003E\u003Cmml:mi mathvariant=\"normal\"\u003EΓ\u003C\u002Fmml:mi\u003E\u003Cmml:mi\u003Em\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:msub\u003E\u003Cmml:mo\u003E=\u003C\u002Fmml:mo\u003E\u003Cmml:mo\u003E−\u003C\u002Fmml:mo\u003E\u003Cmml:mfrac\u003E\u003Cmml:mn\u003E1\u003C\u002Fmml:mn\u003E\u003Cmml:mrow\u003E\u003Cmml:mi\u003En\u003C\u002Fmml:mi\u003E\u003Cmml:mi\u003ERT\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:mrow\u003E\u003C\u002Fmml:mfrac\u003E\u003Cmml:mfenced open=\"(\" close=\")\"\u003E\u003Cmml:mfrac\u003E\u003Cmml:mrow\u003E\u003Cmml:mi\u003E∂\u003C\u002Fmml:mi\u003E\u003Cmml:mi\u003Eγ\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:mrow\u003E\u003Cmml:mrow\u003E\u003Cmml:mi\u003E∂\u003C\u002Fmml:mi\u003E\u003Cmml:mo\u003Eln\u003C\u002Fmml:mo\u003E\u003Cmml:mi\u003Ec\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:mrow\u003E\u003C\u002Fmml:mfrac\u003E\u003C\u002Fmml:mfenced\u003E\u003C\u002Fmml:math\u003E\u003Cspan class=\"equ\"\u003EE3\u003C\u002Fspan\u003E\u003C\u002Fdiv\u003E\u003Cp id=\"p53\"\u003EAssumptions can furthermore be made to determine the constant \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m21\"\u003E\u003Cmml:mi\u003En\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E. In case of strong surfactant electrolytes, such as \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m22\"\u003E\u003Cmml:mi\u003ER\u003C\u002Fmml:mi\u003E\u003Cmml:mo\u003E−\u003C\u002Fmml:mo\u003E\u003Cmml:mi\u003EO\u003C\u002Fmml:mi\u003E\u003Cmml:mo\u003E−\u003C\u002Fmml:mo\u003E\u003Cmml:mi\u003ES\u003C\u002Fmml:mi\u003E\u003Cmml:msubsup\u003E\u003Cmml:mi\u003EO\u003C\u002Fmml:mi\u003E\u003Cmml:mn\u003E3\u003C\u002Fmml:mn\u003E\u003Cmml:mo\u003E−\u003C\u002Fmml:mo\u003E\u003C\u002Fmml:msubsup\u003E\u003Cmml:msup\u003E\u003Cmml:mi mathvariant=\"italic\"\u003ENa\u003C\u002Fmml:mi\u003E\u003Cmml:mo\u003E+\u003C\u002Fmml:mo\u003E\u003C\u002Fmml:msup\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E, both the surfactant ion and the counterion must absorb, yielding a value of \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m23\"\u003E\u003Cmml:mi\u003En\u003C\u002Fmml:mi\u003E\u003Cmml:mo\u003E=\u003C\u002Fmml:mo\u003E\u003Cmml:mn\u003E2\u003C\u002Fmml:mn\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E [\u003Ca href=\"#B76\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E76\u003C\u002Fa\u003E]. A value of \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m24\"\u003E\u003Cmml:mi\u003En\u003C\u002Fmml:mi\u003E\u003Cmml:mo\u003E=\u003C\u002Fmml:mo\u003E\u003Cmml:mn\u003E1\u003C\u002Fmml:mn\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E corresponds to non-ionic surfactants or ionic surfactants in presence of high concentrations of an indifferent electrolyte, such as NaCl. Both assumptions have been applied to lignosulfonates and were found to yield conclusive results [\u003Ca href=\"#B13\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E13\u003C\u002Fa\u003E, \u003Ca href=\"#B66\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E66\u003C\u002Fa\u003E].\u003C\u002Fp\u003E\u003Cp id=\"p54\"\u003EBy applying the above framework, other information can also be extracted from surface and interfacial tension measurements. For example, the surface excess \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m25\"\u003E\u003Cmml:msub\u003E\u003Cmml:mi mathvariant=\"normal\"\u003EΓ\u003C\u002Fmml:mi\u003E\u003Cmml:mi\u003Em\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:msub\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E can be used to calculate the area per molecule, as stated in \u003Ca href=\"#E4\" class=\"ref-link\" data-ref-style=\"disp-formula\"\u003EEq. (4)\u003C\u002Fa\u003E [\u003Ca href=\"#B76\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E76\u003C\u002Fa\u003E]. Here, \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m26\"\u003E\u003Cmml:msub\u003E\u003Cmml:mi\u003EN\u003C\u002Fmml:mi\u003E\u003Cmml:mi\u003Eav\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:msub\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E denotes the Avogadro’s constant \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m27\"\u003E\u003Cmml:mn\u003E6.022\u003C\u002Fmml:mn\u003E\u003Cmml:mo\u003E×\u003C\u002Fmml:mo\u003E\u003Cmml:msup\u003E\u003Cmml:mn\u003E10\u003C\u002Fmml:mn\u003E\u003Cmml:mn\u003E23\u003C\u002Fmml:mn\u003E\u003C\u002Fmml:msup\u003E\u003Cmml:mspace width=\"0.25em\"\u003E\u003C\u002Fmml:mspace\u003E\u003Cmml:mi\u003Emo\u003C\u002Fmml:mi\u003E\u003Cmml:msup\u003E\u003Cmml:mi mathvariant=\"normal\"\u003El\u003C\u002Fmml:mi\u003E\u003Cmml:mrow\u003E\u003Cmml:mo\u003E−\u003C\u002Fmml:mo\u003E\u003Cmml:mn\u003E1\u003C\u002Fmml:mn\u003E\u003C\u002Fmml:mrow\u003E\u003C\u002Fmml:msup\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E.\u003C\u002Fp\u003E\u003Cdiv id=\"df_E4\" class=\"formula panel\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m28\" specific-use=\"web-only\"\u003E\u003Cmml:msub\u003E\u003Cmml:mi mathvariant=\"normal\"\u003EA\u003C\u002Fmml:mi\u003E\u003Cmml:mi mathvariant=\"normal\"\u003Em\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:msub\u003E\u003Cmml:mo\u003E=\u003C\u002Fmml:mo\u003E\u003Cmml:mfrac\u003E\u003Cmml:mn\u003E1\u003C\u002Fmml:mn\u003E\u003Cmml:mrow\u003E\u003Cmml:msub\u003E\u003Cmml:mi mathvariant=\"normal\"\u003EΓ\u003C\u002Fmml:mi\u003E\u003Cmml:mi\u003Em\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:msub\u003E\u003Cmml:msub\u003E\u003Cmml:mi\u003EN\u003C\u002Fmml:mi\u003E\u003Cmml:mi\u003Eav\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:msub\u003E\u003C\u002Fmml:mrow\u003E\u003C\u002Fmml:mfrac\u003E\u003C\u002Fmml:math\u003E\u003Cspan class=\"equ\"\u003EE4\u003C\u002Fspan\u003E\u003C\u002Fdiv\u003E\u003Cp id=\"p55\"\u003ESeveral authors have studied the adsorption kinetics of lignosulfonates on solid surfaces [\u003Ca href=\"#B71\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E71\u003C\u002Fa\u003E, \u003Ca href=\"#B72\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E72\u003C\u002Fa\u003E, \u003Ca href=\"#B77\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E77\u003C\u002Fa\u003E, \u003Ca href=\"#B78\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E78\u003C\u002Fa\u003E, \u003Ca href=\"#B79\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E79\u003C\u002Fa\u003E, \u003Ca href=\"#B80\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E80\u003C\u002Fa\u003E]. The reports generally agree that pseudo second-order kinetics provided the best fit. Such kinetic can be expressed as written in \u003Ca href=\"#E5\" class=\"ref-link\" data-ref-style=\"disp-formula\"\u003EEq. (5)\u003C\u002Fa\u003E, where \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m29\"\u003E\u003Cmml:msub\u003E\u003Cmml:mi\u003Eq\u003C\u002Fmml:mi\u003E\u003Cmml:mi\u003Et\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:msub\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E is the adsorbed amount at time \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m30\"\u003E\u003Cmml:mi\u003Et\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E, \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m31\"\u003E\u003Cmml:msub\u003E\u003Cmml:mi\u003Eq\u003C\u002Fmml:mi\u003E\u003Cmml:mi\u003Ee\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:msub\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E is the amount adsorbed at equilibrium, and \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m32\"\u003E\u003Cmml:mi\u003Ek\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E is the rate constant.\u003C\u002Fp\u003E\u003Cdiv id=\"df_E5\" class=\"formula panel\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m33\" specific-use=\"web-only\"\u003E\u003Cmml:mfrac\u003E\u003Cmml:mi mathvariant=\"normal\"\u003Et\u003C\u002Fmml:mi\u003E\u003Cmml:msub\u003E\u003Cmml:mi mathvariant=\"normal\"\u003Eq\u003C\u002Fmml:mi\u003E\u003Cmml:mi mathvariant=\"normal\"\u003Et\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:msub\u003E\u003C\u002Fmml:mfrac\u003E\u003Cmml:mo\u003E=\u003C\u002Fmml:mo\u003E\u003Cmml:mfrac\u003E\u003Cmml:mn\u003E1\u003C\u002Fmml:mn\u003E\u003Cmml:mrow\u003E\u003Cmml:mi\u003Ek\u003C\u002Fmml:mi\u003E\u003Cmml:msubsup\u003E\u003Cmml:mi\u003Eq\u003C\u002Fmml:mi\u003E\u003Cmml:mi\u003Ee\u003C\u002Fmml:mi\u003E\u003Cmml:mn\u003E2\u003C\u002Fmml:mn\u003E\u003C\u002Fmml:msubsup\u003E\u003C\u002Fmml:mrow\u003E\u003C\u002Fmml:mfrac\u003E\u003Cmml:mo\u003E+\u003C\u002Fmml:mo\u003E\u003Cmml:mfrac\u003E\u003Cmml:mi\u003Et\u003C\u002Fmml:mi\u003E\u003Cmml:msub\u003E\u003Cmml:mi\u003Eq\u003C\u002Fmml:mi\u003E\u003Cmml:mi\u003Ee\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:msub\u003E\u003C\u002Fmml:mfrac\u003E\u003C\u002Fmml:math\u003E\u003Cspan class=\"equ\"\u003EE5\u003C\u002Fspan\u003E\u003C\u002Fdiv\u003E\u003Cp id=\"p56\"\u003E\u003Ca href=\"#E5\" class=\"ref-link\" data-ref-style=\"disp-formula\"\u003EEq. (5)\u003C\u002Fa\u003E can be fitted to experimental data by plotting \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m34\"\u003E\u003Cmml:mfrac\u003E\u003Cmml:mi\u003Et\u003C\u002Fmml:mi\u003E\u003Cmml:msub\u003E\u003Cmml:mi\u003Eq\u003C\u002Fmml:mi\u003E\u003Cmml:mi\u003Et\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:msub\u003E\u003C\u002Fmml:mfrac\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E against \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m35\"\u003E\u003Cmml:mi\u003Et\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E, yielding \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m36\"\u003E\u003Cmml:mfrac\u003E\u003Cmml:mn\u003E1\u003C\u002Fmml:mn\u003E\u003Cmml:msub\u003E\u003Cmml:mi\u003Eq\u003C\u002Fmml:mi\u003E\u003Cmml:mi\u003Ee\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:msub\u003E\u003C\u002Fmml:mfrac\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E as the slope and \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m37\"\u003E\u003Cmml:mfrac\u003E\u003Cmml:mn\u003E1\u003C\u002Fmml:mn\u003E\u003Cmml:mrow\u003E\u003Cmml:mi\u003Ek\u003C\u002Fmml:mi\u003E\u003Cmml:msubsup\u003E\u003Cmml:mi\u003Eq\u003C\u002Fmml:mi\u003E\u003Cmml:mi\u003Ee\u003C\u002Fmml:mi\u003E\u003Cmml:mn\u003E2\u003C\u002Fmml:mn\u003E\u003C\u002Fmml:msubsup\u003E\u003C\u002Fmml:mrow\u003E\u003C\u002Fmml:mfrac\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E as the intersection. This model is, however, limited to adsorption from liquid onto solid phase. Kinetic modeling of lignosulfonate adsorption at liquid–liquid interfaces has also been attempted; yet, the results indicated that water–oil adsorption was not diffusion-controlled [\u003Ca href=\"#B66\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E66\u003C\u002Fa\u003E]. It usually takes hours or days to attain an equilibrium state at the liquid-air or liquid–liquid interface [\u003Ca href=\"#B66\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E66\u003C\u002Fa\u003E, \u003Ca href=\"#B81\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E81\u003C\u002Fa\u003E, \u003Ca href=\"#B82\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E82\u003C\u002Fa\u003E]. This time span is greater than for simple monodisperse surfactants. Different explanations have been given for this behavior. The lignosulfonate can undergo diffusion exchange at the interface, replacing molecules with a lower diffusion coefficient but higher effect on interfacial tension. In addition, the individual macromolecules may be subject to rearrangement, both with respect to the interface and to each other [\u003Ca href=\"#B2\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E2\u003C\u002Fa\u003E]. Such realignment of conformation has been described, e.g., for petroleum asphaltenes [\u003Ca href=\"#B83\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E83\u003C\u002Fa\u003E, \u003Ca href=\"#B84\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E84\u003C\u002Fa\u003E]. Both lignosulfonates and asphaltenes share common characteristics, e.g., both are polybranched, exhibit a tendency for self-association, and require overnight storage, as the emulsions would be less stable if processed immediately after emulsification [\u003Ca href=\"#B13\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E13\u003C\u002Fa\u003E, \u003Ca href=\"#B85\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E85\u003C\u002Fa\u003E]. Analogies have therefore been drawn between these two species in terms of their interfacial behavior [\u003Ca href=\"#B2\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E2\u003C\u002Fa\u003E, \u003Ca href=\"#B66\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E66\u003C\u002Fa\u003E].\u003C\u002Fp\u003E\u003C\u002Fdiv\u003E\u003Cdiv class=\"section\" id=\"sec_7_2\" data-lvl=\"2\"\u003E\u003Ch3 class=\"heading section-title\"\u003E3.2 Effect on surface and interfacial tension\u003C\u002Fh3\u003E\u003Cp id=\"p57\"\u003EMeasuring surface tension is a useful tool, e.g., for assessing the behavior of lignosulfonates in solution or their interactions with other components [\u003Ca href=\"#B38\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E38\u003C\u002Fa\u003E, \u003Ca href=\"#B86\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E86\u003C\u002Fa\u003E]. In addition, the interfacial tension provides a measure for the ease of emulsification [\u003Ca href=\"#B13\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E13\u003C\u002Fa\u003E]. The effect on surface or interfacial tension is related to the amphiphilic property of lignosulfonates, containing both hydrophilic and hydrophobic moieties. From a molecular point of view, the lignosulfonate macromolecule can attain a lower state of energy by extending its hydrophilic moieties into the water, while facing the hydrophobic parts away from it. The decrease in surface tension at increasing surfactant concentration can be explained by different mechanisms. Firstly, adsorption and desorption are occurring simultaneously, where an equilibrium is attained if the adsorption rate is equal and opposite to the desorption rate. By increasing the surfactant concentration, it is statistically more likely for a surfactant molecule to be in the right position and conformation to undergo adsorption. This would hence drive the adsorption–desorption equilibrium towards a higher surface coverage. Secondly, lignosulfonates are polyelectrolytes. By increasing the lignosulfonate concentration, the electrolyte concentration is also increased. As has been shown by small-angle X-ray scattering (SAXS), the effective surface charge of lignosulfonates decreases at increasing concentration [\u003Ca href=\"#B87\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E87\u003C\u002Fa\u003E]. Higher concentrations of a common ion indeed enhance effects such as counterion condensation, charge screening, and the dissociation equilibrium [\u003Ca href=\"#B88\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E88\u003C\u002Fa\u003E]. Water-solubility is ensured by the ionic groups of lignosulfonates, so a lower effective charge would have destabilizing effect. At a lower water-solubility, the equilibrium would hence be shifted to increased surface or interface adsorption. This effect concurs with the observations that lignosulfonates can be precipitated by salt addition (salting-out) [\u003Ca href=\"#B89\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E89\u003C\u002Fa\u003E] and that emulsion stabilization is highest, if the stabilizers are on the verge of precipitation [\u003Ca href=\"#B90\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E90\u003C\u002Fa\u003E].\u003C\u002Fp\u003E\u003Cp id=\"p58\"\u003ELignosulfonate adsorption at aqueous surfaces is evidenced, among others, by a decrease in surface tension [\u003Ca href=\"#B13\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E13\u003C\u002Fa\u003E, \u003Ca href=\"#B38\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E38\u003C\u002Fa\u003E, \u003Ca href=\"#B91\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E91\u003C\u002Fa\u003E]. Within a certain range, this decrease follows a linear-logarithmic progression with concentration [\u003Ca href=\"#B13\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E13\u003C\u002Fa\u003E, \u003Ca href=\"#B38\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E38\u003C\u002Fa\u003E]. Below this range, the surface tension of the pure liquid is approached asymptotically. At high lignosulfonate concentrations, the slope of the surface tension decreases. Some authors have explained this behavior with the onset of lignosulfonate aggregation [\u003Ca href=\"#B75\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E75\u003C\u002Fa\u003E, \u003Ca href=\"#B92\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E92\u003C\u002Fa\u003E], but other effects cannot be ruled out. Measurements of the surface tension with respect to concentration are shown in \u003Ca href=\"#F7\" class=\"ref-link\" data-ref-style=\"fig\"\u003EFigure 7\u003C\u002Fa\u003E.\u003C\u002Fp\u003E\u003Cfigure class=\"media-panel\" id=\"F7\"\u003E\u003Cdiv class=\"media\"\u003E\u003Cimg src=\"\u002F\u002Fcdnintech.com\u002Fmedia\u002Fchapter\u002F83868\u002F1680680847\u002Fmedia\u002FF7.png\" class=\"figure-link\" alt=\"\"\u003E\u003C\u002Fdiv\u003E\u003Cfigcaption class=\"caption\"\u003E\u003Ch4\u003EFigure 7.\u003C\u002Fh4\u003E\u003Cp\u003E\u003Cp xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" xmlns:xlink=\"http:\u002F\u002Fwww.w3.org\u002F1999\u002Fxlink\" xmlns:xsi=\"http:\u002F\u002Fwww.w3.org\u002F2001\u002FXMLSchema-instance\" id=\"p59\"\u003EEquilibrium surface tension in dependence of surfactant concentration. Comparison of lignosulfonates (LS) with polyelectrolyte polymers (left) [\u003Cxref rid=\"B38\" ref-type=\"bibr\"\u003E38\u003C\u002Fxref\u003E] or with the surfactants dodecyl benzenesulfonate (DBS), nonylphenyl polyoxyethylene glycol (PONP) and polysorbate 20 (PS20) (right) [\u003Cxref rid=\"B92\" ref-type=\"bibr\"\u003E92\u003C\u002Fxref\u003E].\u003C\u002Fp\u003E\u003C\u002Fp\u003E\u003C\u002Ffigcaption\u003E\u003C\u002Ffigure\u003E\u003Cp id=\"p60\"\u003EIn comparison with commercial surfactants, the effect on surface or interfacial tension is often less at the same mass concentration [\u003Ca href=\"#B75\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E75\u003C\u002Fa\u003E, \u003Ca href=\"#B82\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E82\u003C\u002Fa\u003E, \u003Ca href=\"#B92\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E92\u003C\u002Fa\u003E]. However, in comparison with other polyelectrolyte polymers, the effect on surface tension can be considerably higher [\u003Ca href=\"#B38\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E38\u003C\u002Fa\u003E]. This circumstance is likely related to the chemical composition and structure, which define macroscopic properties such as solubility, hydrophilic–lipophilic balance (HLB), or surface coverage.\u003C\u002Fp\u003E\u003C\u002Fdiv\u003E\u003Cdiv class=\"section\" id=\"sec_8_2\" data-lvl=\"2\"\u003E\u003Ch3 class=\"heading section-title\"\u003E3.3 Parameters affecting the surface activity of lignosulfonates\u003C\u002Fh3\u003E\u003Cp id=\"p61\"\u003EThere are several external factors, which govern the surface activity of lignosulfonates, in addition to the intrinsic properties such as composition and abundance of functional groups. These factors include, but are not limited to:\u003Cul\u003E\u003Cli\u003E\u003Cp id=\"p62\"\u003ESalinity\u003C\u002Fp\u003E\u003C\u002Fli\u003E\u003Cli\u003E\u003Cp id=\"p63\"\u003EpH\u003C\u002Fp\u003E\u003C\u002Fli\u003E\u003Cli\u003E\u003Cp id=\"p64\"\u003ETemperature\u003C\u002Fp\u003E\u003C\u002Fli\u003E\u003Cli\u003E\u003Cp id=\"p65\"\u003ECo-solvents in the aqueous phase\u003C\u002Fp\u003E\u003C\u002Fli\u003E\u003Cli\u003E\u003Cp id=\"p66\"\u003EOil phase composition\u003C\u002Fp\u003E\u003C\u002Fli\u003E\u003C\u002Ful\u003E\u003C\u002Fp\u003E\u003Cp id=\"p67\"\u003EIt has been shown that increasing salinity with simple monovalent electrolytes, such as NaCl, can have the same effect as increasing lignosulfonate concentration [\u003Ca href=\"#B38\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E38\u003C\u002Fa\u003E, \u003Ca href=\"#B66\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E66\u003C\u002Fa\u003E]. The effect of NaCl concentration on surface or interfacial tension is illustrated in \u003Ca href=\"#F8\" class=\"ref-link\" data-ref-style=\"fig\"\u003EFigure 8\u003C\u002Fa\u003E, which is marked by same linear-logarithmic progression as in \u003Ca href=\"#F7\" class=\"ref-link\" data-ref-style=\"fig\"\u003EFigure 7\u003C\u002Fa\u003E. As discussed earlier, increasing the concentration of a common ion facilitates a lower effective surface charge, which further enhances surface or interface adsorption. The similarities in observed surface tension hence corroborate that the surface adsorption of lignosulfonates is also driven by salinity. It could further be argued that outside the tested concentration range in \u003Ca href=\"#F8\" class=\"ref-link\" data-ref-style=\"fig\"\u003EFigure 8\u003C\u002Fa\u003E, the same slope-decrease or plateau would be visible is in \u003Ca href=\"#F7\" class=\"ref-link\" data-ref-style=\"fig\"\u003EFigure 7\u003C\u002Fa\u003E. While this may be plausible, it has yet to be demonstrated experimentally.\u003C\u002Fp\u003E\u003Cfigure class=\"media-panel\" id=\"F8\"\u003E\u003Cdiv class=\"media\"\u003E\u003Cimg src=\"\u002F\u002Fcdnintech.com\u002Fmedia\u002Fchapter\u002F83868\u002F1680680847\u002Fmedia\u002FF8.png\" class=\"figure-link\" alt=\"\"\u003E\u003C\u002Fdiv\u003E\u003Cfigcaption class=\"caption\"\u003E\u003Ch4\u003EFigure 8.\u003C\u002Fh4\u003E\u003Cp\u003E\u003Cp xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" xmlns:xlink=\"http:\u002F\u002Fwww.w3.org\u002F1999\u002Fxlink\" xmlns:xsi=\"http:\u002F\u002Fwww.w3.org\u002F2001\u002FXMLSchema-instance\" id=\"p68\"\u003EEffect of NaCl concentration on the surface tension of 0.01 wt.% lignosulfonate in water (left) [\u003Cxref rid=\"B38\" ref-type=\"bibr\"\u003E38\u003C\u002Fxref\u003E]. Effect of NaCl or lignosulfonate concentration on the tension of the water-xylene interface (right) [\u003Cxref rid=\"B66\" ref-type=\"bibr\"\u003E66\u003C\u002Fxref\u003E].\u003C\u002Fp\u003E\u003C\u002Fp\u003E\u003C\u002Ffigcaption\u003E\u003C\u002Ffigure\u003E\u003Cp id=\"p69\"\u003EHowever, the data exhibited in \u003Ca href=\"#F7\" class=\"ref-link\" data-ref-style=\"fig\"\u003EFigures 7\u003C\u002Fa\u003E and \u003Ca href=\"#F8\" class=\"ref-link\" data-ref-style=\"fig\"\u003E8\u003C\u002Fa\u003E represents a simplified case. In both instances, the counterion was solely the monovalent sodium ion, as only sodium lignosulfonate and NaCl were used. In presence of multivalent cations, the surface phenomena of lignosulfonates are more complex. Di- or trivalent cations, for example, were shown to induce interface gelling [\u003Ca href=\"#B66\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E66\u003C\u002Fa\u003E]. As illustrated in \u003Ca href=\"#F9\" class=\"ref-link\" data-ref-style=\"fig\"\u003EFigure 9\u003C\u002Fa\u003E, such interfaces behave inelastically, exhibiting wrinkles and cracks upon deformation. Pendant drop tensiometry relies on the applicability of the Young-Laplace equation. Since this is not the case for inelastic interfaces, the technique fails to predict accurate interfacial tension. Similar challenges are evident for other techniques, such as the Du Noüy ring method or spinning drop tensiometry.\u003C\u002Fp\u003E\u003Cfigure class=\"media-panel\" id=\"F9\"\u003E\u003Cdiv class=\"media\"\u003E\u003Cimg src=\"\u002F\u002Fcdnintech.com\u002Fmedia\u002Fchapter\u002F83868\u002F1680680847\u002Fmedia\u002FF9.png\" class=\"figure-link\" alt=\"\"\u003E\u003C\u002Fdiv\u003E\u003Cfigcaption class=\"caption\"\u003E\u003Ch4\u003EFigure 9.\u003C\u002Fh4\u003E\u003Cp\u003E\u003Cp xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" xmlns:xlink=\"http:\u002F\u002Fwww.w3.org\u002F1999\u002Fxlink\" xmlns:xsi=\"http:\u002F\u002Fwww.w3.org\u002F2001\u002FXMLSchema-instance\" id=\"p70\"\u003EDroplet retraction in pendant drop video-tensiometry. In incompressible interface layer is visible as wrinkling of the droplet surface, which was formed by sodium lignosulfonate in presence of CaCl\u003Csub\u003E2\u003C\u002Fsub\u003E. Image taken from [\u003Cxref rid=\"B66\" ref-type=\"bibr\"\u003E66\u003C\u002Fxref\u003E].\u003C\u002Fp\u003E\u003C\u002Fp\u003E\u003C\u002Ffigcaption\u003E\u003C\u002Ffigure\u003E\u003Cp id=\"p71\"\u003ELowering the pH can further enhance the effect of lignosulfonates on surface tension [\u003Ca href=\"#B91\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E91\u003C\u002Fa\u003E]. This circumstance is in analogy to the salting-out effect of simple electrolytes. Phenolic moieties are said to ionize at around pH 9–10, while the carboxylic acid groups ionize at pH 3–4 [\u003Ca href=\"#B54\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E54\u003C\u002Fa\u003E, \u003Ca href=\"#B55\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E55\u003C\u002Fa\u003E]. A lower pH can hence reduce the total charge of the lignosulfonate macromolecules. This would further reduce the water-solubility and thereby drive the equilibrium towards higher adsorption. However, the discussed effect is valid only if the lignosulfonates remain water-soluble. If precipitation is evident, then the bulk concentration would decrease, which would also reduce surface and interface adsorption.\u003C\u002Fp\u003E\u003Cp id=\"p72\"\u003EAs depicted in \u003Ca href=\"#F10\" class=\"ref-link\" data-ref-style=\"fig\"\u003EFigure 10\u003C\u002Fa\u003E, increasing the temperature can also increase the effect of lignosulfonates on surface tension. At higher temperature, the hydrodynamic radius of lignosulfonates decreases [\u003Ca href=\"#B93\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E93\u003C\u002Fa\u003E]. Thermodynamically speaking, the entropy is higher at elevated temperatures. This can enable a larger number of possible conformations, thus reducing the average molecular dimensions [\u003Ca href=\"#B88\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E88\u003C\u002Fa\u003E]. As a result, lignosulfonate aggregation and a reduction of zeta potential have been reported at elevated temperature [\u003Ca href=\"#B94\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E94\u003C\u002Fa\u003E]. These two effects indicate solution-destabilization, which could further promote surface adsorption.\u003C\u002Fp\u003E\u003Cfigure class=\"media-panel\" id=\"F10\"\u003E\u003Cdiv class=\"media\"\u003E\u003Cimg src=\"\u002F\u002Fcdnintech.com\u002Fmedia\u002Fchapter\u002F83868\u002F1680680847\u002Fmedia\u002FF10.png\" class=\"figure-link\" alt=\"\"\u003E\u003C\u002Fdiv\u003E\u003Cfigcaption class=\"caption\"\u003E\u003Ch4\u003EFigure 10.\u003C\u002Fh4\u003E\u003Cp\u003E\u003Cp xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" xmlns:xlink=\"http:\u002F\u002Fwww.w3.org\u002F1999\u002Fxlink\" xmlns:xsi=\"http:\u002F\u002Fwww.w3.org\u002F2001\u002FXMLSchema-instance\" id=\"p73\"\u003ESurface tension of water and 1 g\u002Fl lignosulfonate in water. Image taken from [\u003Cxref rid=\"B93\" ref-type=\"bibr\"\u003E93\u003C\u002Fxref\u003E].\u003C\u002Fp\u003E\u003C\u002Fp\u003E\u003C\u002Ffigcaption\u003E\u003C\u002Ffigure\u003E\u003Cp id=\"p74\"\u003ECo-solvents in the aqueous phase can alter characteristics such as the solution parameter and the dielectric constant. This will inevitably also affect the surface behavior of the lignosulfonates. The addition of low molecular weight alcohols yielded a decrease of surface charge and slight interparticle association [\u003Ca href=\"#B87\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E87\u003C\u002Fa\u003E]. The effect was thereby similar as to increasing the ionic strength, implying solution destabilization of lignosulfonates by alcohol addition. On the other hand, hydrophobic interaction chromatography uses water\u002Fethanol and water\u002F2-propanol mixtures to eluate the more hydrophobic fractions [\u003Ca href=\"#B64\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E64\u003C\u002Fa\u003E], which would suggest that water\u002Falcohol mixtures are a better solvent for these. This is corroborated by the fact that the surface pressure decreased due to ethanol addition [\u003Ca href=\"#B81\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E81\u003C\u002Fa\u003E], i.e. fewer lignosulfonate molecules would enter the interface. Corresponding measurements of interfacial tension are shown in \u003Ca href=\"#F10\" class=\"ref-link\" data-ref-style=\"fig\"\u003EFigure 10\u003C\u002Fa\u003E. Overall, the effects of adding alcohols are hence counteracting, i.e., reduction of effective charge (destabilizing) and solubility improvement (stabilizing). It is thus not surprising that the emulsion stability could be both improved and reduced after alcohol addition (\u003Ca href=\"#F11\" class=\"ref-link\" data-ref-style=\"fig\"\u003EFigure 11\u003C\u002Fa\u003E) [\u003Ca href=\"#B81\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E81\u003C\u002Fa\u003E].\u003C\u002Fp\u003E\u003Cfigure class=\"media-panel\" id=\"F11\"\u003E\u003Cdiv class=\"media\"\u003E\u003Cimg src=\"\u002F\u002Fcdnintech.com\u002Fmedia\u002Fchapter\u002F83868\u002F1680680847\u002Fmedia\u002FF11.png\" class=\"figure-link\" alt=\"\"\u003E\u003C\u002Fdiv\u003E\u003Cfigcaption class=\"caption\"\u003E\u003Ch4\u003EFigure 11.\u003C\u002Fh4\u003E\u003Cp\u003E\u003Cp xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" xmlns:xlink=\"http:\u002F\u002Fwww.w3.org\u002F1999\u002Fxlink\" xmlns:xsi=\"http:\u002F\u002Fwww.w3.org\u002F2001\u002FXMLSchema-instance\" id=\"p75\"\u003ETension of the mineral oil–water interface in dependence of ethanol concentration. The samples contained 1 g\u002Fl lignosulfonate (LS) and 20 mM NaCl as background electrolyte. Figure taken from [\u003Cxref rid=\"B81\" ref-type=\"bibr\"\u003E81\u003C\u002Fxref\u003E].\u003C\u002Fp\u003E\u003C\u002Fp\u003E\u003C\u002Ffigcaption\u003E\u003C\u002Ffigure\u003E\u003Cp id=\"p76\"\u003EThe addition of non-solvents to water will eventually lead to lignosulfonate precipitation [\u003Ca href=\"#B87\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E87\u003C\u002Fa\u003E]. In this case, the interfacial activity would also decrease, as the bulk concentration is lower [\u003Ca href=\"#B66\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E66\u003C\u002Fa\u003E]. Solvent shifting can be useful for the production of functional micro- and nanoparticles from lignin [\u003Ca href=\"#B95\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E95\u003C\u002Fa\u003E]. However, the technology bears limited importance for this chapter, as the resulting Pickering-emulsions tend to be less stable [\u003Ca href=\"#B66\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E66\u003C\u002Fa\u003E].\u003C\u002Fp\u003E\u003Cp id=\"p77\"\u003EAt last, the oil phase composition can also affect the interfacial activity of lignin. A simple explanation for this can be based on the concept of the hydrophilic–lipophilic balance (HLB). Surfactants can generally be classified according to their HLB, where lower HLB values account for more lipophilic surfactants and high values for more hydrophilic ones. It is generally agreed that an HLB of 3–6 is characteristic for water-in-oil (W\u002FO) emulsifiers, whereas 8–18 are suited for oil-in-water (O\u002FW) emulsifiers [\u003Ca href=\"#B76\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E76\u003C\u002Fa\u003E]. According to the HLB model, optimum emulsion stability is given, when a surfactant-blend matches the HLB value of the emulsified liquids. In analogy to that, the interfacial tension is also said to exhibit a minimum at the optimal HLB of the surfactant mixture. The concept is illustrated in \u003Ca href=\"#F12\" class=\"ref-link\" data-ref-style=\"fig\"\u003EFigure 12\u003C\u002Fa\u003E.\u003C\u002Fp\u003E\u003Cfigure class=\"media-panel\" id=\"F12\"\u003E\u003Cdiv class=\"media\"\u003E\u003Cimg src=\"\u002F\u002Fcdnintech.com\u002Fmedia\u002Fchapter\u002F83868\u002F1680680847\u002Fmedia\u002FF12.png\" class=\"figure-link\" alt=\"\"\u003E\u003C\u002Fdiv\u003E\u003Cfigcaption class=\"caption\"\u003E\u003Ch4\u003EFigure 12.\u003C\u002Fh4\u003E\u003Cp\u003E\u003Cp xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" xmlns:xlink=\"http:\u002F\u002Fwww.w3.org\u002F1999\u002Fxlink\" xmlns:xsi=\"http:\u002F\u002Fwww.w3.org\u002F2001\u002FXMLSchema-instance\" id=\"p78\"\u003EVariation of emulsion stability, droplet size, and interfacial tension with percentage of surfactant with high HLB. Figure reproduced from [\u003Cxref rid=\"B76\" ref-type=\"bibr\"\u003E76\u003C\u002Fxref\u003E].\u003C\u002Fp\u003E\u003C\u002Fp\u003E\u003C\u002Ffigcaption\u003E\u003C\u002Ffigure\u003E\u003Cp id=\"p79\"\u003EOils with low polarity, such as paraffins and mineral oil, tend to have a required HLF for O\u002FW emulsions of 9–11, whereas more polar oils are in the range of 12–17, e.g., oleic acid, chlorinated paraffins, and aromatics such as toluene [\u003Ca href=\"#B96\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E96\u003C\u002Fa\u003E]. The HLB scale can hence also be an indicator for the compatibility or affinity of surfactants towards a certain oil phase. Lignosulfonates were reported to have an HLB of 11.6 based on their composition [\u003Ca href=\"#B97\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E97\u003C\u002Fa\u003E], but the effective HLB is likely higher than this, as the cited value is a rough estimation based on the elementary composition. Among others, it does not consider stearic effects. In addition, the contribution of the sulfonate group to the effective HLB is generally high. There are few studies comparing the stability of different oils emulsified with lignosulfonates. Experience shows that aromatic solvents, e.g., toluene or xylene (HLB = 14–15), tend yield more stable than emulsions with mineral oil (HLB = 10) [\u003Ca href=\"#B13\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E13\u003C\u002Fa\u003E]. Accordingly, it was demonstrated that the effect on interfacial tension of xylene was greater than on mineral oil, as plotted in \u003Ca href=\"#F12\" class=\"ref-link\" data-ref-style=\"fig\"\u003EFigure 12\u003C\u002Fa\u003E. It would only make sense that lignosulfonates, comprising a polyaromatic structure, also have a higher affinity to aromatic oils than to paraffinic ones. Based on their behavior, lignosulfonates can be classified as O\u002FW emulsion stabilizers with an effective HLB of 10–18 (\u003Ca href=\"#F13\" class=\"ref-link\" data-ref-style=\"fig\"\u003EFigure 13\u003C\u002Fa\u003E).\u003C\u002Fp\u003E\u003Cfigure class=\"media-panel\" id=\"F13\"\u003E\u003Cdiv class=\"media\"\u003E\u003Cimg src=\"\u002F\u002Fcdnintech.com\u002Fmedia\u002Fchapter\u002F83868\u002F1680680847\u002Fmedia\u002FF13.png\" class=\"figure-link\" alt=\"\"\u003E\u003C\u002Fdiv\u003E\u003Cfigcaption class=\"caption\"\u003E\u003Ch4\u003EFigure 13.\u003C\u002Fh4\u003E\u003Cp\u003E\u003Cp xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" xmlns:xlink=\"http:\u002F\u002Fwww.w3.org\u002F1999\u002Fxlink\" xmlns:xsi=\"http:\u002F\u002Fwww.w3.org\u002F2001\u002FXMLSchema-instance\" id=\"p80\"\u003EEffect of molecular weight and oil phase on interfacial tension. Figure taken from [\u003Cxref rid=\"B13\" ref-type=\"bibr\"\u003E13\u003C\u002Fxref\u003E].\u003C\u002Fp\u003E\u003C\u002Fp\u003E\u003C\u002Ffigcaption\u003E\u003C\u002Ffigure\u003E\u003C\u002Fdiv\u003E\u003Cdiv class=\"section\" id=\"sec_9_2\" data-lvl=\"2\"\u003E\u003Ch3 class=\"heading section-title\"\u003E3.4 Interactions with other surfactants\u003C\u002Fh3\u003E\u003Cp id=\"p81\"\u003EThe presence of other surfactants can affect the surface activity of lignosulfonate. Surfactants can be distinguished based on their charge, i.e., non-ionic, anionic, cationic, and zwitterionic surfactants. Another classification would be based on the structure, that is, polymeric and non-polymeric surfactants. Electrostatic interactions with lignosulfonates are eminent, if the co-surfactant carries a charge. Surfactant interactions will hence be discussed for each individual type in this sub-chapter.\u003C\u002Fp\u003E\u003Cp id=\"p82\"\u003EInteractions with non-ionic surfactants can be due to effects such as hydrogen bonding or hydrophobic interactions. Straight-chain alcohols can exhibit surfactant-like properties, if the chain length is at least four carbon atoms or more [\u003Ca href=\"#B98\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E98\u003C\u002Fa\u003E]. The effect of these was studied by Qiu et al., who concluded that alcohols can improve the surface activity of lignosulfonate [\u003Ca href=\"#B86\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E86\u003C\u002Fa\u003E]. The authors attributed the largest effect to alcohols with a chain-length of at least 10 carbon atoms, which was evidence by an increase in zeta potential of TiO\u003Csub\u003E2\u003C\u002Fsub\u003E particles. Such behavior would suggest cooperative adsorption. Still, the author conducted experiments at a constant alcohol\u002Flignosulfonate ratio, which makes delineating individual contributions difficult, as the lignosulfonate concentration would increase at increasing alcohol levels. Low molecular weight alcohols can indeed increase counterion condensation on lignosulfonates [\u003Ca href=\"#B87\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E87\u003C\u002Fa\u003E], which could facilitate a higher surface coverage. Simon et al. further studied the interfacial tension of lignosulfonate solutions in presence of asphaltenes [\u003Ca href=\"#B82\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E82\u003C\u002Fa\u003E]. The authors concluded that interfacial adsorption was competitive, which is a potential detriment for emulsion stability. At last, Askvik et al. concluded that lignosulfonates and non-ionic surfactants did not associate, due to the small contribution of hydrophobic interaction [\u003Ca href=\"#B38\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E38\u003C\u002Fa\u003E]. Current literate hence disagrees, whether blending lignosulfonates with non-ionic surfactants has a positive effect. Yet, some cases may indeed benefit from such mixtures.\u003C\u002Fp\u003E\u003Cp id=\"p83\"\u003EAnionic surfactants can interact with lignosulfonates by electrostatic repulsion, which would suggest competitive adsorption. Still, combining lignosulfonates with other anionic surfactants can be beneficial, as both species increase the ionic strength. As has been discussed previously, increasing salinity will also facilitate more interfacial adsorption [\u003Ca href=\"#B66\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E66\u003C\u002Fa\u003E]. This perception is supported by a study on blending lignosulfonates and sodium dodecyl sulfate (SDS) [\u003Ca href=\"#B75\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E75\u003C\u002Fa\u003E], which showed that the presence of lignosulfonates decreased the critical micelle concentration (CMC) of SDS. A beneficial effect was also found in the context of enhanced oil recovery (EOR) [\u003Ca href=\"#B99\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E99\u003C\u002Fa\u003E, \u003Ca href=\"#B100\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E100\u003C\u002Fa\u003E, \u003Ca href=\"#B101\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E101\u003C\u002Fa\u003E]. By blending petroleum sulfonates, sodium chloride, 2-propanol, and lignosulfonates, interfacial tension values as low as \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m38\"\u003E\u003Cmml:mn\u003E1\u003C\u002Fmml:mn\u003E\u003Cmml:mo\u003E×\u003C\u002Fmml:mo\u003E\u003Cmml:msup\u003E\u003Cmml:mn\u003E10\u003C\u002Fmml:mn\u003E\u003Cmml:mrow\u003E\u003Cmml:mo\u003E−\u003C\u002Fmml:mo\u003E\u003Cmml:mn\u003E3\u003C\u002Fmml:mn\u003E\u003C\u002Fmml:mrow\u003E\u003C\u002Fmml:msup\u003E\u003Cmml:mi\u003EmN\u003C\u002Fmml:mi\u003E\u003Cmml:mo\u003E\u002F\u003C\u002Fmml:mo\u003E\u003Cmml:mi mathvariant=\"normal\"\u003Em\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E were obtained [\u003Ca href=\"#B100\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E100\u003C\u002Fa\u003E]. Another implementation would be the use of lignosulfonates as sacrificial adsorbents [\u003Ca href=\"#B16\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E16\u003C\u002Fa\u003E, \u003Ca href=\"#B102\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E102\u003C\u002Fa\u003E]. Here, the rock formations are initially saturated with lignosulfonates, after which a second flood with a different surfactant mixture would be injected. While this application does not directly relate to emulsion stabilization, it shows that adsorption was also competitive.\u003C\u002Fp\u003E\u003Cp id=\"p84\"\u003ECationic surfactants interact with lignosulfonates electrostatically, which can yield the formation of lignosulfonate-cationic surfactant complexes [\u003Ca href=\"#B38\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E38\u003C\u002Fa\u003E]. Improved solubility of such complexes in oil media has been reported [\u003Ca href=\"#B103\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E103\u003C\u002Fa\u003E]. Still, a challenge with such systems is the formation of a water-insoluble complexes. In such cases, the surfactants precipitate and are no longer available for interfacial adsorption, hence yielding mixed effects on emulsion stabilization [\u003Ca href=\"#B38\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E38\u003C\u002Fa\u003E].\u003C\u002Fp\u003E\u003Cp id=\"p85\"\u003EIt has long been established that lignosulfonates can associate with cationic polyelectrolytes, forming insoluble complexes, colloids, and macroscopic precipitates [\u003Ca href=\"#B104\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E104\u003C\u002Fa\u003E]. Association of lignosulfonates with chitosan reportedly forms such complexes at a sulfonate\u002Famine ratio close to 1.0, suggesting that all sulfonate groups are accessible for interactions [\u003Ca href=\"#B105\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E105\u003C\u002Fa\u003E]. No complex formation was reported at pH 8, which entails that it was indeed electrostatic interactions governing the association of these two compounds. Another interesting application is the formation of multilayers via layer-by-layer association of lignosulfonates and cationic polyelectrolytes [\u003Ca href=\"#B106\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E106\u003C\u002Fa\u003E, \u003Ca href=\"#B107\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E107\u003C\u002Fa\u003E]. This self-assembly was reportedly governed by electrostatic interactions, hydrogen bonding, and cation-π interactions.\u003C\u002Fp\u003E\u003Cp id=\"p86\"\u003EIt can be concluded that strong interactions exist between lignosulfonates and cationic surfactants or polymers. Still, these interactions frequently yield precipitates, which would shift the emulsion stabilization mechanism from interfacial adsorption to that of a Pickering emulsion. Beneficial interactions can occur due to mixing lignosulfonates with anionic or non-ionic surfactants, but these may depend on the actual system and the application mode.\u003C\u002Fp\u003E\u003C\u002Fdiv\u003E\u003C\u002Fdiv\u003E\u003Cdiv class=\"section\" id=\"sec_11\" data-lvl=\"1\"\u003E\u003Ch2 class=\"heading main-title\"\u003E4. Emulsion stabilization mechanisms\u003C\u002Fh2\u003E\u003Cdiv class=\"section\" id=\"sec_11_2\" data-lvl=\"2\"\u003E\u003Ch3 class=\"heading section-title\"\u003E4.1 Basic concepts\u003C\u002Fh3\u003E\u003Cp id=\"p87\"\u003EEmulsion stabilization entails the prevention or delay of the coalescence event. Coalescence is the fusing of two or more droplets to form one larger droplet. The limiting case for coalescence is complete phase separation, i.e., the oil and the water being separated into two distinct phases. Coalescence involves film drainage, during which the continuous phase is displaced between the coalescing droplets. Flocculation usually precedes coalescence, in which the dispersed droplets collect to form larger aggregates. Creaming or sedimentation occurs, if the flocculated droplets accumulate at the top (creaming) or the bottom (sedimentation) of the continuous phase. Centrifugation of emulsions stabilized with lignosulfonates can yield the formation of a dense packed layer (DPL) of droplets, which exhibit thixotropy and viscoelastic behavior [\u003Ca href=\"#B13\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E13\u003C\u002Fa\u003E].\u003C\u002Fp\u003E\u003Cp id=\"p88\"\u003EFundamentally speaking, the use of a stabilizer (surfactant and\u002For polymer) introduces an energy barrier between the droplets [\u003Ca href=\"#B76\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E76\u003C\u002Fa\u003E]. The lowest state of energy would be a system, which is completely phase separated. Yet, the transition from emulsion to complete phase separation may become noncontinuous in presence of a stabilizer. Emulsions stabilized with lignosulfonates are hence only kinetically stable. This entails that with time, the emulsions are expected to return to original state, i.e., a fully coalesced and phase separated system. Still, this transition is hindered to the extent that emulsion can remain in their emulsified state over a period of months or even years.\u003C\u002Fp\u003E\u003Cp id=\"p89\"\u003EThe interfacial tension is an important parameter, as low interfacial tension reduces the energy required for emulsification. In addition, this parameter can be used to study interfacial phenomena and interactions in the aqueous phase. A known stabilizer tends to be more effective at parameters, which yield a higher reduction of interfacial tension. Still, the reduction of interfacial tension in general is no guarantee for forming stable emulsions. There are examples of surfactants, which substantially decrease the interfacial tension, but do not produce stable emulsions or even destabilize existing systems. The latter are referred to as demulsifiers or emulsion breakers. The important point is that interfacial tension measurements can yield complementary information, but it should not be taken as a sole measure to probe emulsion stability. Interfacial adsorption is a prerequisite for an efficient stabilizer; however, emulsion stabilization involves several other mechanisms, which will be discussed in detail further on.\u003C\u002Fp\u003E\u003C\u002Fdiv\u003E\u003Cdiv class=\"section\" id=\"sec_12_2\" data-lvl=\"2\"\u003E\u003Ch3 class=\"heading section-title\"\u003E4.2 Stearic hindrance\u003C\u002Fh3\u003E\u003Cp id=\"p90\"\u003EStearic hindrance or stearic repulsion relies on the presence of the surfactant or polymer at the interface. By imposing spatial obstacles, the oil within the droplets is prevented from coalescing. Stearic repulsion is an important mechanism for non-ionic surfactants and polymers, as these lack the contribution from electrostatic repulsion.\u003C\u002Fp\u003E\u003Cp id=\"p91\"\u003EStearic repulsion is aided by a positive osmotic free energy of interaction, which states that the affinity of the adsorbed species to the continuous phase (water) is greater than to each other [\u003Ca href=\"#B76\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E76\u003C\u002Fa\u003E]. As such, complete film drainage can be prevented, as the surfactant or polymer favors the retention of water between the oil droplets.\u003C\u002Fp\u003E\u003Cp id=\"p92\"\u003EA second effect is of entropic nature, also referred to as volume restriction or elastic interaction [\u003Ca href=\"#B76\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E76\u003C\u002Fa\u003E]. A significant overlap of the polymer chains can be favored by hydrophobic or van der Waals interactions. Separating these chains would require energy, which can act as a barrier to prevent coalescence. This phenomenon will be discussed in further detail during Section 4.5.\u003C\u002Fp\u003E\u003C\u002Fdiv\u003E\u003Cdiv class=\"section\" id=\"sec_13_2\" data-lvl=\"2\"\u003E\u003Ch3 class=\"heading section-title\"\u003E4.3 Marangoni effect\u003C\u002Fh3\u003E\u003Cp id=\"p93\"\u003EThe Marangoni effect, also referred to as Marangoni-Gibbs effect, is a common effect that facilitates emulsion stabilization with simple surfactants. It is related to the mass transfer along the interface between two fluids due to a concentration gradient. In analogy to Fick’s law of diffusion, mass transfer of surfactant molecules is directed towards areas with lower concentration. As the oil droplets approach, the surfactant layer between each droplet and the continuous phase can be displaced. This will in turn yield a concentration gradient. Surfactant molecules are hence drawn back into the contact area between the oil droplets, yielding a stabilizing effect. An illustration of the Marangoni effect is given in \u003Ca href=\"#F14\" class=\"ref-link\" data-ref-style=\"fig\"\u003EFigure 14\u003C\u002Fa\u003E.\u003C\u002Fp\u003E\u003Cfigure class=\"media-panel\" id=\"F14\"\u003E\u003Cdiv class=\"media\"\u003E\u003Cimg src=\"\u002F\u002Fcdnintech.com\u002Fmedia\u002Fchapter\u002F83868\u002F1680680847\u002Fmedia\u002FF14.png\" class=\"figure-link\" alt=\"\"\u003E\u003C\u002Fdiv\u003E\u003Cfigcaption class=\"caption\"\u003E\u003Ch4\u003EFigure 14.\u003C\u002Fh4\u003E\u003Cp\u003E\u003Cp xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" xmlns:xlink=\"http:\u002F\u002Fwww.w3.org\u002F1999\u002Fxlink\" xmlns:xsi=\"http:\u002F\u002Fwww.w3.org\u002F2001\u002FXMLSchema-instance\" id=\"p94\"\u003EIllustration of the Marangoni effect during film drainage. Image taken from [\u003Cxref rid=\"B108\" ref-type=\"bibr\"\u003E108\u003C\u002Fxref\u003E].\u003C\u002Fp\u003E\u003C\u002Fp\u003E\u003C\u002Ffigcaption\u003E\u003C\u002Ffigure\u003E\u003Cp id=\"p95\"\u003EAttribution of the Marangoni effect to emulsion stabilization with lignosulfonates is given only implicitly, as the contribution of individual effects is often difficult to delineate. Still, the described effect is likely of importance, as lignosulfonates are subject to interfacial diffusion in the same manner as other surfactants.\u003C\u002Fp\u003E\u003C\u002Fdiv\u003E\u003Cdiv class=\"section\" id=\"sec_14_2\" data-lvl=\"2\"\u003E\u003Ch3 class=\"heading section-title\"\u003E4.4 Electrostatic repulsion\u003C\u002Fh3\u003E\u003Cp id=\"p96\"\u003EIn aqueous solution, lignosulfonates can attain a negative charge due to the dissociation of anionic groups. When adsorbed at the interface, these groups will contribute to an overall negative charge. Coulomb forces are then acting between the interfaces of different oil droplets, yielding electrostatic repulsion. This mechanism has been described for stabilization of both particles and emulsions with lignosulfonates [\u003Ca href=\"#B38\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E38\u003C\u002Fa\u003E, \u003Ca href=\"#B46\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E46\u003C\u002Fa\u003E, \u003Ca href=\"#B109\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E109\u003C\u002Fa\u003E]. Related phenomena are frequently studied by measuring the electrophoretic mobility of the dispersed particles or droplets, i.e., the zeta potential [\u003Ca href=\"#B38\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E38\u003C\u002Fa\u003E, \u003Ca href=\"#B70\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E70\u003C\u002Fa\u003E].\u003C\u002Fp\u003E\u003Cp id=\"p97\"\u003EElectrostatic repulsion is highly affected by the composition of the aqueous phase. Increasing electrolyte concentrations or the presence of less polar solvents will affect counterion condensation [\u003Ca href=\"#B87\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E87\u003C\u002Fa\u003E]. Charge screening and a lower degree of dissociation can then lessen the repulsion between anionic groups [\u003Ca href=\"#B88\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E88\u003C\u002Fa\u003E]. This could explain the destabilizing effect, which the presence of low molecular weight alcohols can have [\u003Ca href=\"#B81\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E81\u003C\u002Fa\u003E]. Still, increasing the concentration of simple electrolytes tends to improve stability, if the lignosulfonate is not precipitated from solution [\u003Ca href=\"#B66\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E66\u003C\u002Fa\u003E]. This effect is likely attributed to the fact that increasing salinity can enhance other effects, such as increased interfacial adsorption. The pH furthermore affects electrostatic repulsion. It has been reported that higher pH induces larger changes of the zeta potential, as the lignosulfonate macromolecules exhibit a higher degree of ionization [\u003Ca href=\"#B70\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E70\u003C\u002Fa\u003E, \u003Ca href=\"#B110\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E110\u003C\u002Fa\u003E].\u003C\u002Fp\u003E\u003C\u002Fdiv\u003E\u003Cdiv class=\"section\" id=\"sec_15_2\" data-lvl=\"2\"\u003E\u003Ch3 class=\"heading section-title\"\u003E4.5 Viscoelastic interface films\u003C\u002Fh3\u003E\u003Cp id=\"p98\"\u003EIt has long been established that droplet coalescence is affected by the stability of interfacial layers [\u003Ca href=\"#B111\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E111\u003C\u002Fa\u003E]. From a purely mechanical point of view, an emulsion would naturally be more stable, if the dispersed droplets were coated by a rigid interface layer. The term rigid hereby refers to the inelastic behavior, as can also be observed for lignosulfonates [\u003Ca href=\"#B66\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E66\u003C\u002Fa\u003E]. These systems are, however, not entirely rigid. Deformation may occur to some extent, bearing both elastic and viscose contributions, hence the terminology viscoelastic interface films.\u003C\u002Fp\u003E\u003Cp id=\"p99\"\u003EUpon deformation, a purely elastic film will store the exerted work as potential energy. If the force is no longer acting, the system will return to the originate state or even oscillate, if the viscose contribution is small or negligible. Viscose forces can be viewed in analogy to friction, since energy is dissipated upon deformation, which cannot be retrieved during relaxation. Based on this, the complex modulus \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m39\"\u003E\u003Cmml:msup\u003E\u003Cmml:mi\u003EE\u003C\u002Fmml:mi\u003E\u003Cmml:mo\u003E&lowast;\u003C\u002Fmml:mo\u003E\u003C\u002Fmml:msup\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E can be modeled as in \u003Ca href=\"#E6\" class=\"ref-link\" data-ref-style=\"disp-formula\"\u003EEq. (6)\u003C\u002Fa\u003E, i.e., as the sum of the elastic contribution \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m40\"\u003E\u003Cmml:msup\u003E\u003Cmml:mi\u003EE\u003C\u002Fmml:mi\u003E\u003Cmml:mo\u003E′\u003C\u002Fmml:mo\u003E\u003C\u002Fmml:msup\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E and the viscose contribution \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m41\"\u003E\u003Cmml:msup\u003E\u003Cmml:mi\u003EE\u003C\u002Fmml:mi\u003E\u003Cmml:mrow\u003E\u003Cmml:mo\u003E′\u003C\u002Fmml:mo\u003E\u003Cmml:mo\u003E′\u003C\u002Fmml:mo\u003E\u003C\u002Fmml:mrow\u003E\u003C\u002Fmml:msup\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E. These contributions are also referred to as the apparent elastic dilatational modulus and the apparent viscous dilatational modulus, respectively, as \u003Ca href=\"#E6\" class=\"ref-link\" data-ref-style=\"disp-formula\"\u003EEq. (6)\u003C\u002Fa\u003E is based on the framework of dilatational interfacial rheology. During this measurement technique, a droplet is suspended in a continuous phase in presence of surfactants (see \u003Ca href=\"#F9\" class=\"ref-link\" data-ref-style=\"fig\"\u003EFigure 9\u003C\u002Fa\u003E), while undergoing volume expansion and contraction at the frequency \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m42\"\u003E\u003Cmml:mi\u003Eω\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E. This allows the complex modulus \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m43\"\u003E\u003Cmml:msup\u003E\u003Cmml:mi\u003EE\u003C\u002Fmml:mi\u003E\u003Cmml:mo\u003E&lowast;\u003C\u002Fmml:mo\u003E\u003C\u002Fmml:msup\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E to be determined in terms of the change of interfacial tension \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m44\"\u003E\u003Cmml:mi mathvariant=\"italic\"\u003Edσ\u003C\u002Fmml:mi\u003E\u003Cmml:mfenced open=\"(\" close=\")\"\u003E\u003Cmml:mi\u003Et\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:mfenced\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E divided by the change in interface area \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m45\"\u003E\u003Cmml:mi\u003Ed\u003C\u002Fmml:mi\u003E\u003Cmml:mo\u003Eln\u003C\u002Fmml:mo\u003E\u003Cmml:mi\u003EA\u003C\u002Fmml:mi\u003E\u003Cmml:mfenced open=\"(\" close=\")\"\u003E\u003Cmml:mi\u003Et\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:mfenced\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E.\u003C\u002Fp\u003E\u003Cdiv id=\"df_E6\" class=\"formula panel\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m46\" specific-use=\"web-only\"\u003E\u003Cmml:msup\u003E\u003Cmml:mi\u003EE\u003C\u002Fmml:mi\u003E\u003Cmml:mo\u003E&lowast;\u003C\u002Fmml:mo\u003E\u003C\u002Fmml:msup\u003E\u003Cmml:mfenced open=\"(\" close=\")\"\u003E\u003Cmml:mi\u003Eω\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:mfenced\u003E\u003Cmml:mo\u003E=\u003C\u002Fmml:mo\u003E\u003Cmml:msup\u003E\u003Cmml:mi\u003EE\u003C\u002Fmml:mi\u003E\u003Cmml:mo\u003E′\u003C\u002Fmml:mo\u003E\u003C\u002Fmml:msup\u003E\u003Cmml:mfenced open=\"(\" close=\")\"\u003E\u003Cmml:mi\u003Eω\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:mfenced\u003E\u003Cmml:mo\u003E+\u003C\u002Fmml:mo\u003E\u003Cmml:mi\u003Ei\u003C\u002Fmml:mi\u003E\u003Cmml:msup\u003E\u003Cmml:mi\u003EE\u003C\u002Fmml:mi\u003E\u003Cmml:mrow\u003E\u003Cmml:mo\u003E′\u003C\u002Fmml:mo\u003E\u003Cmml:mo\u003E′\u003C\u002Fmml:mo\u003E\u003C\u002Fmml:mrow\u003E\u003C\u002Fmml:msup\u003E\u003Cmml:mfenced open=\"(\" close=\")\"\u003E\u003Cmml:mi\u003Eω\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:mfenced\u003E\u003Cmml:mo\u003E=\u003C\u002Fmml:mo\u003E\u003Cmml:mfrac\u003E\u003Cmml:mrow\u003E\u003Cmml:mi mathvariant=\"italic\"\u003Edσ\u003C\u002Fmml:mi\u003E\u003Cmml:mfenced open=\"(\" close=\")\"\u003E\u003Cmml:mi\u003Et\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:mfenced\u003E\u003C\u002Fmml:mrow\u003E\u003Cmml:mrow\u003E\u003Cmml:mi\u003Ed\u003C\u002Fmml:mi\u003E\u003Cmml:mo\u003Eln\u003C\u002Fmml:mo\u003E\u003Cmml:mi\u003EA\u003C\u002Fmml:mi\u003E\u003Cmml:mfenced open=\"(\" close=\")\"\u003E\u003Cmml:mi\u003Et\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:mfenced\u003E\u003C\u002Fmml:mrow\u003E\u003C\u002Fmml:mfrac\u003E\u003C\u002Fmml:math\u003E\u003Cspan class=\"equ\"\u003EE6\u003C\u002Fspan\u003E\u003C\u002Fdiv\u003E\u003Cp id=\"p100\"\u003EPendant drop tensiometry has the advantage of yielding information on both interfacial tension and interfacial rheology. The technique ceases to function, however, if droplet contraction and expansion is not entirely viscoelastic, as the Young Laplace equation is no longer valid. Other techniques to measure surface rheology include the oscillating barrier method, capillary waves, Langmuir trough, and surface rotational shear rheometry [\u003Ca href=\"#B112\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E112\u003C\u002Fa\u003E]. The latter two have been successfully applied for studying the interfacial behavior of lignosulfonates.\u003C\u002Fp\u003E\u003Cp id=\"p101\"\u003EResults from interfacial shear rheology of lignosulfonates are depicted in \u003Ca href=\"#F15\" class=\"ref-link\" data-ref-style=\"fig\"\u003EFigure 15\u003C\u002Fa\u003E. Frequency sweeps are of interest, as these can be used to characterize the interfacial properties. As can be seen, the elastic modulus \u003Cem\u003E\u003Citalic xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" xmlns:xlink=\"http:\u002F\u002Fwww.w3.org\u002F1999\u002Fxlink\" xmlns:xsi=\"http:\u002F\u002Fwww.w3.org\u002F2001\u002FXMLSchema-instance\"\u003EE’\u003C\u002Fitalic\u003E\u003C\u002Fem\u003E and the viscose modulus \u003Cem\u003E\u003Citalic xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" xmlns:xlink=\"http:\u002F\u002Fwww.w3.org\u002F1999\u002Fxlink\" xmlns:xsi=\"http:\u002F\u002Fwww.w3.org\u002F2001\u002FXMLSchema-instance\"\u003EE”\u003C\u002Fitalic\u003E\u003C\u002Fem\u003E are intersecting or approaching each other in cases, where only monovalent cations are present. The interfacial response is hence entirely viscoelastic. In presence of multivalent cations, i.e., Ca\u003Csup\u003E2+\u003C\u002Fsup\u003E and Al\u003Csup\u003E3+\u003C\u002Fsup\u003E, the elastic and viscose modulus are approximately parallel to each other. This behavior is characteristic for that of gelled interfaces. It appears that multivalent cations can function as connectors between the lignosulfonate molecules, imposing a stronger cohesion to the interface film. This gelling is a reasonable explanation for the observed rigidity in \u003Ca href=\"#F9\" class=\"ref-link\" data-ref-style=\"fig\"\u003EFigure 9\u003C\u002Fa\u003E.\u003C\u002Fp\u003E\u003Cfigure class=\"media-panel\" id=\"F15\"\u003E\u003Cdiv class=\"media\"\u003E\u003Cimg src=\"\u002F\u002Fcdnintech.com\u002Fmedia\u002Fchapter\u002F83868\u002F1680680847\u002Fmedia\u002FF15.png\" class=\"figure-link\" alt=\"\"\u003E\u003C\u002Fdiv\u003E\u003Cfigcaption class=\"caption\"\u003E\u003Ch4\u003EFigure 15.\u003C\u002Fh4\u003E\u003Cp\u003E\u003Cp xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" xmlns:xlink=\"http:\u002F\u002Fwww.w3.org\u002F1999\u002Fxlink\" xmlns:xsi=\"http:\u002F\u002Fwww.w3.org\u002F2001\u002FXMLSchema-instance\" id=\"p102\"\u003EFrequency sweep of 1.8 g\u002Fl sodium lignosulfonate and in presence of different electrolytes at 0.2% strain. The oil phase is made of xylene isomer blend. Figure taken from [\u003Cxref rid=\"B66\" ref-type=\"bibr\"\u003E66\u003C\u002Fxref\u003E].\u003C\u002Fp\u003E\u003C\u002Fp\u003E\u003C\u002Ffigcaption\u003E\u003C\u002Ffigure\u003E\u003Cp id=\"p103\"\u003EIncreasing the lignosulfonate concentration has shown to decrease the interfacial tension (see \u003Ca href=\"#F8\" class=\"ref-link\" data-ref-style=\"fig\"\u003EFigure 8\u003C\u002Fa\u003E). While the same could be expected for the interfacial modulus, experimental evidence shows that this is not the case. As depicted in \u003Ca href=\"#F16\" class=\"ref-link\" data-ref-style=\"fig\"\u003EFigure 16\u003C\u002Fa\u003E, the interfacial modulus will increase to a maximum, after which a decrease is noted. It appears that electrolytic effects govern this behavior, as the same maximum was observed for adding simple electrolytes. The maximum has indeed been correlated with a maximum in emulsion stability and the onset of lignosulfonate precipitation [\u003Ca href=\"#B66\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E66\u003C\u002Fa\u003E]. The observed phenomena are hence in line with two long established principles: Emulsions can be stabilized by the formation of viscoelastic interface layers and the emulsion stability tends to be best, if the stabilizing agent is on the verge of precipitation [\u003Ca href=\"#B90\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E90\u003C\u002Fa\u003E, \u003Ca href=\"#B111\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E111\u003C\u002Fa\u003E]. If the solubility limit is exceeded, precipitation yields the formation of particles, hence shifting the stabilization mechanism to that of a Pickering emulsion. This type of mechanism will be discussed in the next sub-chapter.\u003C\u002Fp\u003E\u003Cfigure class=\"media-panel\" id=\"F16\"\u003E\u003Cdiv class=\"media\"\u003E\u003Cimg src=\"\u002F\u002Fcdnintech.com\u002Fmedia\u002Fchapter\u002F83868\u002F1680680847\u002Fmedia\u002FF16.png\" class=\"figure-link\" alt=\"\"\u003E\u003C\u002Fdiv\u003E\u003Cfigcaption class=\"caption\"\u003E\u003Ch4\u003EFigure 16.\u003C\u002Fh4\u003E\u003Cp\u003E\u003Cp xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" xmlns:xlink=\"http:\u002F\u002Fwww.w3.org\u002F1999\u002Fxlink\" xmlns:xsi=\"http:\u002F\u002Fwww.w3.org\u002F2001\u002FXMLSchema-instance\" id=\"p104\"\u003EInterfacial moduli in dependence of lignosulfonate or added salt concentration. Data was obtained using interfacial shear rheology and xylene isomer blend as the oil phase. Figures taken from [\u003Cxref rid=\"B66\" ref-type=\"bibr\"\u003E66\u003C\u002Fxref\u003E].\u003C\u002Fp\u003E\u003C\u002Fp\u003E\u003C\u002Ffigcaption\u003E\u003C\u002Ffigure\u003E\u003C\u002Fdiv\u003E\u003Cdiv class=\"section\" id=\"sec_16_2\" data-lvl=\"2\"\u003E\u003Ch3 class=\"heading section-title\"\u003E4.6 Particle stabilization\u003C\u002Fh3\u003E\u003Cp id=\"p105\"\u003EParticle stabilization of emulsions involves the presence of a third (solid) phase. The solid phase is usually present as a colloidal dispersion, exhibiting particle sizes of approximately 1 nm to 1 μm. These particles can adsorb at the oil–water interface, forming bilayers and bridging monolayers [\u003Ca href=\"#B113\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E113\u003C\u002Fa\u003E]. The stabilizing mechanism is based on coherent particle layers around the dispersed liquid, preventing coalescence by acting as a steric (mechanical) barrier. A particle stabilized emulsion is also referred to as Pickering emulsion. Interest has currently shifted from using inorganic particles to adopting bio-based systems, which includes the use of cellulose, chitin, starch, proteins, and lignin [\u003Ca href=\"#B114\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E114\u003C\u002Fa\u003E].\u003C\u002Fp\u003E\u003Cp id=\"p106\"\u003EParticle stabilization is usually not the primary mechanism, with which lignosulfonates stabilize emulsions. In aqueous solution at low salinity, lignosulfonates are usually well-dissolved and hence act by molecular adsorption at the interface. Certain conditions, however, can induce lignosulfonate precipitation, which will shift the stabilization mechanism to that of a Pickering emulsion [\u003Ca href=\"#B66\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E66\u003C\u002Fa\u003E]. In addition, lignosulfonate aggregation can occur at concentrations as low as 0.05 g\u002Fl [\u003Ca href=\"#B55\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E55\u003C\u002Fa\u003E]. Aggregation is reportedly facilitated by π–π stacking, hydrogen bonding, and hydrophobic interactions [\u003Ca href=\"#B93\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E93\u003C\u002Fa\u003E, \u003Ca href=\"#B115\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E115\u003C\u002Fa\u003E, \u003Ca href=\"#B116\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E116\u003C\u002Fa\u003E]. At the right conditions, aggregate dimensions can be in the range of colloidal dispersions. Based on the diffusion coefficient of lignosulfonates obtained from dilatational interfacial rheology, it was concluded that lignosulfonates undergo interfacial adsorption in the aggregated state [\u003Ca href=\"#B66\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E66\u003C\u002Fa\u003E]. Interfacially adsorbed aggregates could furthermore act by particle stabilization. It is important to note that lignosulfonate aggregation occurs gradually over a broad concentration range. The contribution of aggregates to the overall emulsion stability would hence build up in increments. This contrasts with precipitation, where an immediate shift to particle stabilization is observed at the precipitation onset.\u003C\u002Fp\u003E\u003C\u002Fdiv\u003E\u003C\u002Fdiv\u003E\u003Cdiv class=\"section\" id=\"sec_18\" data-lvl=\"1\"\u003E\u003Ch2 class=\"heading main-title\"\u003E5. Summary and conclusion\u003C\u002Fh2\u003E\u003Cp id=\"p107\"\u003EThis chapter detailed the fundamentals of emulsion stabilization with lignosulfonates. First, basic concepts, the industrial production, as well as chemical make-up and structure of lignosulfonates were discussed. Second, the effect of lignosulfonates on surface and interfacial tension was described. Third, the fundamental mechanisms behind emulsion stabilization with lignosulfonates were explained.\u003C\u002Fp\u003E\u003Cp id=\"p108\"\u003ELignosulfonates are bio-based specialty chemicals and function as surfactants due to their amphiphilic property. Lignosulfonates are readily water-soluble as they comprise ionizable moieties, i.e., sulfonate and carboxylic acid groups at neutral pH. They can hence be utilized in a variety of technical applications, which includes the stabilization of oil-in-water emulsions. Surface and interface adsorption of lignosulfonates is evidenced by a reduction in surface and interfacial tension. Parameters that can enhance the effect on interfacial tension include increased salinity, a reduction in pH, and the presence of co-solvents or co-surfactants. A high reduction of interfacial tension is generally beneficial, as this suggests enhanced interfacial adsorption and reduces the energy required during emulsification. While interfacial adsorption is a prerequisite for an efficient emulsion stabilizer, the stabilization mechanism is related to other phenomena as well. For lignosulfonates, these mechanisms include stearic hindrance, electrostatic repulsion, the Marangoni-Gibbs effect, the formation of viscoelastic interface layers, and particle stabilization. The stabilization mechanisms are furthermore affected by the composition of the lignosulfonates as well as the aqueous and oil phase. Parameters that increase the interfacial activity and yield the formation of more cohesive interface layers are beneficial, as both effects tend to promote emulsion stability.\u003C\u002Fp\u003E\u003Cp id=\"p109\"\u003EThere has been an increased interest in biopolymers recently, as these are inherently more sustainable than petroleum-derived polymers. Lignosulfonates are no exception to that trend, which is also mirrored by the large variety of lignosulfonate products on the market today. Emulsion stabilization is one of the application areas, which still has the potential for growth. This chapter was hence dedicated to the fundamentals of emulsion stabilization with lignosulfonates, in the hope that this may aid their utilization in new areas and products.\u003C\u002Fp\u003E\u003C\u002Fdiv\u003E\u003Cdiv class=\"section\" id=\"sec_22\" data-lvl=\"1\"\u003E\u003Ch2 class=\"heading main-title\"\u003EConflict of interest\u003C\u002Fh2\u003E\u003Cp id=\"p110\"\u003EThe author declares no conflict of interest.\u003C\u002Fp\u003E\u003C\u002Fdiv\u003E\n","keywords":"lignin, lignosulfonates, surfactant, emulsion, dispersion, stabilizer, interfacial activity, colloid chemistry","chapterPDFUrl":"https:\u002F\u002Fcdn.intechopen.com\u002Fpdfs\u002F83868.pdf","chapterXML":"https:\u002F\u002Fmts.intechopen.com\u002Fsource\u002Fxml\u002F83868.xml","webChapterXML":"s3:\u002F\u002Fintech-chapter-xmls\u002Fxmls-chapter\u002F83868\u002F1679400603\u002F","downloadPdfUrl":"\u002Fchapter\u002Fpdf-download\u002F83868","previewPdfUrl":"\u002Fchapter\u002Fpdf-preview\u002F83868","cdnMediaBaseUrl":"s3:\u002F\u002Fintech-cdn\u002Fmedia\u002Fchapter\u002F83868\u002F1680680847\u002F","totalDownloads":276,"totalViews":1995,"totalCrossrefCites":4,"totalDimensionsCites":4,"totalAltmetricsMentions":0,"introChapter":false,"impactScore":1,"impactScorePercentile":67,"impactScoreQuartile":3,"hasAltmetrics":0,"dateSubmitted":"August 13th 2022","dateReviewed":"August 23rd 2022","datePrePublished":"September 30th 2022","datePublished":"April 5th 2023","dateFinished":"September 29th 2022","readingETA":"0","abstract":"Lignosulfonates are biobased surfactants and specialty chemicals. Due to their amphiphilic nature, they can be utilized in many technical applications, such as plasticizers, dispersants, stabilizers, and agrochemical formulations. Here, their ability to stabilize emulsions plays an important role. This chapter hence explains the fundamentals of emulsion stabilization with lignosulfonates. First, basic concepts are introduced along with the production and chemical make-up of lignosulfonates. Second, the interfacial activity is discussed. Parameters that affect interfacial activity and emulsion stabilization efficiency of lignosulfonates are furthermore treated. Such parameters may include salinity, pH, the presence of cosolvents and cosurfactants. Third, the underlying mechanisms of emulsion stabilization are outlined. The goal of this chapter is to introduce the reader to important fundamentals, and to draw the link between basic research and industrial practice.","reviewType":"peer-reviewed","bibtexUrl":"\u002Fchapter\u002Fbibtex\u002F83868","risUrl":"\u002Fchapter\u002Fris\u002F83868","isPublished":true,"isOnlineFirst":false,"isDeactivated":0,"noAds":0,"subseries":null,"book":{"id":"11902","type":"book","title":"Lignin","subtitle":"Chemistry, Structure, and Application","fullTitle":"Lignin - Chemistry, Structure, and Application","slug":"lignin-chemistry-structure-and-application","publishedDate":"April 5th 2023","bookSignature":"Arpit Sand and Jaya Tuteja","coverURL":"https:\u002F\u002Fcdn.intechopen.com\u002Fbooks\u002Fimages_new\u002F11902.jpg","cdnCoverURL":"https:\u002F\u002Fcdnintech.com\u002Fbooks\u002F11902\u002F1713446456-271484287\u002Fcover.jpg","cdnCoverURL300":"https:\u002F\u002Fcdnintech.com\u002Fbooks\u002F11902\u002F1713446456-271484287\u002Fcover-300.jpg","cdnWebCoverURL":"https:\u002F\u002Fcdnintech.com\u002Fbooks\u002F11902\u002F1718282379-1978756798\u002Fweb-cover.jpg","cdnWebCoverURL300":"https:\u002F\u002Fcdnintech.com\u002Fbooks\u002F11902\u002F1718282379-1978756798\u002Fweb-cover-300.jpg","cdnCoverWithTextURL":"https:\u002F\u002Fcdnintech.com\u002Fbooks\u002F11902\u002F1718120008-497112668\u002Fcover-text.jpg","cdnCoverWithTextURL300":"https:\u002F\u002Fcdnintech.com\u002Fbooks\u002F11902\u002F1718120008-497112668\u002Fcover-text-300.jpg","licenceType":"CC BY 3.0","editedByType":"Edited by","isbn":"978-1-83968-546-0","price":119,"printIsbn":"978-1-83968-545-3","pdfIsbn":"978-1-83968-861-4","reviewType":"peer-reviewed","numberOfWosCitations":0,"isAvailableForWebshopOrdering":true,"isPublished":true,"isPublisherCbs":false,"kuFlag":false,"noAdsSub":0,"editors":[{"id":"287032","title":"Associate Prof.","name":"Arpit","middleName":null,"surname":"Sand","slug":"arpit-sand","fullName":"Arpit Sand"}],"equalEditorOne":null,"equalEditorTwo":null,"equalEditorThree":null,"coeditorOne":{"id":"453331","title":"Dr.","name":"Jaya","middleName":null,"surname":"Tuteja","slug":"jaya-tuteja","fullName":"Jaya Tuteja"},"coeditorTwo":null,"coeditorThree":null,"coeditorFour":null,"coeditorFive":null,"topics":[{"id":"915"}],"productType":{"id":"1","title":"Edited Volume","chapterContentType":"chapter","authoredCaption":"Edited by"},"chapters":[{"id":"86050","type":"chapter","title":"Introductory Chapter: Introduction to Structure Properties and Application of Lignin","slug":"introductory-chapter-introduction-to-structure-properties-and-application-of-lignin","totalDownloads":280,"totalCrossrefCites":0,"signatures":"Jaya Tuteja and Arpit Sand","reviewType":"peer-reviewed","authors":[{"id":"287032","title":"Associate Prof.","name":"Arpit","middleName":null,"surname":"Sand","fullName":"Arpit Sand","slug":"arpit-sand"},{"id":"517944","title":"Dr.","name":"Jaya","middleName":null,"surname":"Tuteja","fullName":"Jaya Tuteja","slug":"jaya-tuteja"}]},{"id":"83779","type":"chapter","title":"Composition and Role of Lignin in Biochemicals","slug":"composition-and-role-of-lignin-in-biochemicals","totalDownloads":344,"totalCrossrefCites":1,"signatures":"Tawaf Ali Shah, Li Zhihe, Li Zhiyu and Zhang Andong","reviewType":"peer-reviewed","authors":[{"id":"469288","title":"Dr.","name":"Tawaf Ali","middleName":null,"surname":"Shah","fullName":"Tawaf Ali Shah","slug":"tawaf-ali-shah"},{"id":"469884","title":"Prof.","name":"Li","middleName":null,"surname":"Zhihe","fullName":"Li Zhihe","slug":"li-zhihe"},{"id":"469885","title":"Dr.","name":"Li","middleName":null,"surname":"Zhiyu","fullName":"Li Zhiyu","slug":"li-zhiyu"},{"id":"477660","title":"Dr.","name":"Zhang","middleName":null,"surname":"Andong","fullName":"Zhang Andong","slug":"zhang-andong"}]},{"id":"85056","type":"chapter","title":"Perspective Chapter: Potential of Lignin Valorization with Emphasis on Bioepoxy Production","slug":"perspective-chapter-potential-of-lignin-valorization-with-emphasis-on-bioepoxy-production","totalDownloads":227,"totalCrossrefCites":2,"signatures":"Mohamed H. El-Moayed, Justin Kühn, Sea-Hyun Lee, Mahmoud Farag and Sherif Mehanny","reviewType":"peer-reviewed","authors":[{"id":"189039","title":"Prof.","name":"Sherif","middleName":null,"surname":"Mehanny","fullName":"Sherif Mehanny","slug":"sherif-mehanny"},{"id":"302358","title":"Prof.","name":"Mahmoud","middleName":null,"surname":"Farag","fullName":"Mahmoud Farag","slug":"mahmoud-farag"},{"id":"474969","title":"Mr.","name":"Mohamed","middleName":null,"surname":"H. El-Moayed","fullName":"Mohamed H. 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Introduction","level":"1"},{"id":"sec_2","title":"2. Fundamentals","level":"1"},{"id":"sec_2_2","title":"2.1 Definitions and distinctions","level":"2"},{"id":"sec_3_2","title":"2.2 Production","level":"2"},{"id":"sec_4_2","title":"2.3 Structure and composition","level":"2"},{"id":"sec_6","title":"3. Adsorption on surfaces and interfaces","level":"1"},{"id":"sec_6_2","title":"3.1 Adsorption","level":"2"},{"id":"sec_7_2","title":"3.2 Effect on surface and interfacial tension","level":"2"},{"id":"sec_8_2","title":"3.3 Parameters affecting the surface activity of lignosulfonates","level":"2"},{"id":"sec_9_2","title":"3.4 Interactions with other surfactants","level":"2"},{"id":"sec_11","title":"4. Emulsion stabilization mechanisms","level":"1"},{"id":"sec_11_2","title":"4.1 Basic concepts","level":"2"},{"id":"sec_12_2","title":"4.2 Stearic hindrance","level":"2"},{"id":"sec_13_2","title":"4.3 Marangoni effect","level":"2"},{"id":"sec_14_2","title":"4.4 Electrostatic repulsion","level":"2"},{"id":"sec_15_2","title":"4.5 Viscoelastic interface films","level":"2"},{"id":"sec_16_2","title":"4.6 Particle stabilization","level":"2"},{"id":"sec_18","title":"5. Summary and conclusion","level":"1"},{"id":"sec_22","title":"Conflict of interest","level":"1"}],"chapterReferences":[{"id":"B1","body":"\u003Cref id=\"B1\"\u003E\u003Cmixed-citation publication-type=\"book\"\u003ESixta H. Handbook of Pulp. Weinheim, Germany: Wiley-vch; 2006\u003C\u002Fmixed-citation\u003E\u003C\u002Fref\u003E"},{"id":"B2","body":"\u003Cref id=\"B2\"\u003E\u003Cmixed-citation publication-type=\"journal\"\u003ERuwoldt J. 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Rosa Elena","authors":[{"id":"352954","title":"Dr.","name":"Ramiro","middleName":null,"surname":"Escudero","fullName":"Ramiro Escudero","slug":"ramiro-escudero"},{"id":"423622","title":"Dr.","name":"González","middleName":null,"surname":"Jeovani Pineda","fullName":"González Jeovani Pineda","slug":"gonzalez-jeovani-pineda"},{"id":"423623","title":"Dr.","name":"Pérez","middleName":null,"surname":"Rosa Elena","fullName":"Pérez Rosa Elena","slug":"perez-rosa-elena"}]},{"id":"77655","title":"Bacterial Cellulose: Multipurpose Biodegradable Robust Nanomaterial","slug":"bacterial-cellulose-multipurpose-biodegradable-robust-nanomaterial","signatures":"Agata Kołodziejczyk","authors":[{"id":"352705","title":"Dr.","name":"Agata","middleName":null,"surname":"Kołodziejczyk","fullName":"Agata Kołodziejczyk","slug":"agata-kolodziejczyk"}]},{"id":"77170","title":"Biorefinery System of Lignocellulosic Biomass Using Steam Explosion","slug":"biorefinery-system-of-lignocellulosic-biomass-using-steam-explosion","signatures":"Chikako Asada, Sholahuddin and Yoshitoshi Nakamura","authors":[{"id":"355779","title":"Prof.","name":"Yoshitoshi","middleName":null,"surname":"Nakamura","fullName":"Yoshitoshi Nakamura","slug":"yoshitoshi-nakamura"},{"id":"357468","title":"Dr.","name":"Chikako","middleName":null,"surname":"Asada","fullName":"Chikako Asada","slug":"chikako-asada"},{"id":"357502","title":"Dr.","name":"Sholahuddin","middleName":null,"surname":"Sholahuddin","fullName":"Sholahuddin Sholahuddin","slug":"sholahuddin-sholahuddin"}]},{"id":"77422","title":"New Ethylenediamine Crosslinked 2D-Cellulose Adsorbent for Nanoencapsulation Removal of Pb (II) and Cu (II) Heavy Metal Ions: Synthesis, Characterization Application, and RSM-Modeling","slug":"new-ethylenediamine-crosslinked-2d-cellulose-adsorbent-for-nanoencapsulation-removal-of-pb-ii-and-cu","signatures":"Issam Jilal, Soufian El Barkany, Zahra Bahari, Youssef El Ouardi, Mohamed Loutou, Hassan Amhamdi, Mohamed Abou-Salama, Amin Salhi, Abderrahmane El Idrissi and Katri Laatikainen","authors":[{"id":"175289","title":"Prof.","name":"Soufian","middleName":null,"surname":"El Barkany","fullName":"Soufian El Barkany","slug":"soufian-el-barkany"},{"id":"175590","title":"Prof.","name":"Abderahmane","middleName":null,"surname":"El Idrissi","fullName":"Abderahmane El Idrissi","slug":"abderahmane-el-idrissi"},{"id":"356243","title":"Dr.","name":"Issam","middleName":null,"surname":"Jilal","fullName":"Issam Jilal","slug":"issam-jilal"},{"id":"356244","title":"Prof.","name":"Zahra","middleName":null,"surname":"Bahari","fullName":"Zahra Bahari","slug":"zahra-bahari"},{"id":"356245","title":"Dr.","name":"Youssef","middleName":null,"surname":"El Ouardi","fullName":"Youssef El Ouardi","slug":"youssef-el-ouardi"},{"id":"356246","title":"Prof.","name":"Hassan","middleName":null,"surname":"Amhamdi","fullName":"Hassan Amhamdi","slug":"hassan-amhamdi"},{"id":"356247","title":"Prof.","name":"Mohamed","middleName":null,"surname":"Loutoua","fullName":"Mohamed Loutoua","slug":"mohamed-loutoua"},{"id":"356248","title":"Prof.","name":"Mohamed","middleName":null,"surname":"Abou-Salama","fullName":"Mohamed Abou-Salama","slug":"mohamed-abou-salama"},{"id":"356250","title":"Prof.","name":"Amin","middleName":null,"surname":"Salhi","fullName":"Amin Salhi","slug":"amin-salhi"},{"id":"356811","title":"Prof.","name":"Katri","middleName":null,"surname":"Laatikainen","fullName":"Katri Laatikainen","slug":"katri-laatikainen"}]},{"id":"78810","title":"Conversion of Cellulose into Value-Added Products","slug":"conversion-of-cellulose-into-value-added-products","signatures":"Lethiwe D. 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Mthembu","slug":"lethiwe-d.-mthembu"},{"id":"428553","title":"Dr.","name":"Rishi","middleName":null,"surname":"Gupta","fullName":"Rishi Gupta","slug":"rishi-gupta"},{"id":"447976","title":"Prof.","name":"Nirmala","middleName":null,"surname":"Deenadayalu","fullName":"Nirmala Deenadayalu","slug":"nirmala-deenadayalu"}]},{"id":"77903","title":"Cellulose as a Natural Emulsifier: From Nanocelluloses to Macromolecules","slug":"cellulose-as-a-natural-emulsifier-from-nanocelluloses-to-macromolecules","signatures":"Carolina Costa, Bruno Medronho, Björn Lindman, Håkan Edlund and Magnus Norgren","authors":[{"id":"175614","title":"Dr.","name":"Bruno","middleName":null,"surname":"Medronho","fullName":"Bruno Medronho","slug":"bruno-medronho"},{"id":"355285","title":"Ph.D. Student","name":"Carolina","middleName":null,"surname":"Costa","fullName":"Carolina Costa","slug":"carolina-costa"},{"id":"355319","title":"Dr.","name":"Magnus","middleName":null,"surname":"Norgren","fullName":"Magnus Norgren","slug":"magnus-norgren"},{"id":"355323","title":"Dr.","name":"Håkan","middleName":null,"surname":"Edlund","fullName":"Håkan Edlund","slug":"hakan-edlund"},{"id":"355324","title":"Dr.","name":"Björn","middleName":null,"surname":"Lindman","fullName":"Björn Lindman","slug":"bjorn-lindman"}]}]}],"publishedBooks":[],"publishedBooksByAuthor":[]},"onlineFirst":{"chapter":{"type":"chapter","id":"84631","title":"Perspective Chapter: Pattern Recognition for Mass-Spectrometry-Based Proteomics","doi":"10.5772\u002Fintechopen.108422","slug":"perspective-chapter-pattern-recognition-for-mass-spectrometry-based-proteomics","body":"\u003Cdiv class=\"section\" id=\"sec_1\" data-lvl=\"1\"\u003E\u003Ch2 class=\"heading main-title\"\u003E1. Introduction\u003C\u002Fh2\u003E\u003Cp id=\"p2\"\u003ECentral Dogma theory highlights the flow of information in most living systems from DNA to RNA to Proteins, in which the four bases – adenine (A), cytosine (C), guanine (G), and thymine (T) in DNA or Uracil (U) in RNA) – encode the 20 amino acids that are the building blocks of proteins. Proteomics is essentially the study of 100 s to 1000s of proteins in a single shot, made possible by the advancements in multiplexing technologies.\u003C\u002Fp\u003E\u003Cp id=\"p3\"\u003EProteins are the functional elements of biology, and the information encoded in DNA or RNA represents a potential protein that may or may not actually be manufactured by the cell. DNA sequencing has enabled the development of the field of proteomics by allowing the prediction of the amino acid sequences of the encoded proteins. The expression of a particular gene leads to the formation of a protein which plays a vital role in running the cellular machinery – from providing structural support to catalysis as enzymes, and even controlling gene expression. These proteins, in turn, form the key components of biological pathways, and may be biomarkers or targets for drugs. They can form complexes and operate through cellular pathways, in which even a single point mutation can lead to a disease state.\u003C\u002Fp\u003E\u003Cp id=\"p4\"\u003EAmino acids are the building blocks of peptides, and ultimately proteins, which are then folded into unique three-dimensional shapes. Internal bonding within proteins is essential for stabilizing their structure, and the final folded form is essential for the functional activity. Through the years, innumerable techniques have been used to determine the structure of proteins, but lately, artificial intelligence (AI) is being increasingly adopted to determine the shape taken by proteins [\u003Ca href=\"#B1\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E1\u003C\u002Fa\u003E].\u003C\u002Fp\u003E\u003Cp id=\"p5\"\u003EThe Human Genome Project (HGP) mapped the genes to the entire protein collection as expressed in the approximately 230 cell types [\u003Ca href=\"#B2\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E2\u003C\u002Fa\u003E]. Based on data available in public databases [\u003Ca href=\"#B3\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E3\u003C\u002Fa\u003E], it is estimated that there are about 20,300–20,500 protein-coding human genes. Legrain, et.al, [\u003Ca href=\"#B4\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E4\u003C\u002Fa\u003E] indicated that approximately 30% of these genes lacked experimental evidence at the protein level.\u003C\u002Fp\u003E\u003Cp id=\"p6\"\u003EThe general applications of Artificial Intelligence (AI), Machine Learning (ML), and Deep Learning (DL) to proteomics include annotation and MS spectral analysis. This approach started in 2000, but gained momentum after 2006, when it was used for peptide fragmentation [\u003Ca href=\"#B5\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E5\u003C\u002Fa\u003E, \u003Ca href=\"#B6\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E6\u003C\u002Fa\u003E] and identification [\u003Ca href=\"#B7\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E7\u003C\u002Fa\u003E]. AI deviates from classical statistical analysis in that it can handle huge volumes of data and makes fewer assumptions.\u003C\u002Fp\u003E\u003Cp id=\"p7\"\u003EMS data for proteins can be generated from peptides using either the ‘bottom-up” approach [\u003Ca href=\"#B8\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E8\u003C\u002Fa\u003E], or from an intact protein using the “top-down” approach [\u003Ca href=\"#B9\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E9\u003C\u002Fa\u003E]. In 2013, Swan, et al. suggested the use of machine learning for analyzing, and interpreting large sets of MS data [\u003Ca href=\"#B10\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E10\u003C\u002Fa\u003E]. Two areas of applications highlighted included direct analysis of mass spectral peaks, and proteins identified by sequence database search, which involves relative protein quantification. The outcome from this analysis would facilitate the identification of disease biomarkers and the classification samples as applicable to diagnostics. Challenges include protein prediction, quantification, use of ML, and dealing with small sample sizes.\u003C\u002Fp\u003E\u003Cp id=\"p8\"\u003EIn the early stages of \u003Cem\u003E\u003Citalic xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" xmlns:xlink=\"http:\u002F\u002Fwww.w3.org\u002F1999\u002Fxlink\" xmlns:xsi=\"http:\u002F\u002Fwww.w3.org\u002F2001\u002FXMLSchema-instance\"\u003Ein silico\u003C\u002Fitalic\u003E\u003C\u002Fem\u003E design, researchers generated computer models of protein folding, and created 3D models for understanding drug binding mechanisms. Now, AI is being increasingly used in proteomics, and this has gained increased importance due to the current COVID-19 pandemic. This approach can be used to generate vaccines and to keep pace with the rate at which virus is mutating. Thus, AI is playing a larger role in figuring out the shape of proteins [\u003Ca href=\"#B1\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E1\u003C\u002Fa\u003E] with implications for all aspects of drug research. Complex interactions between proteins in living systems can be deciphered by feeding the right inputs to the algorithms, leading to more accurate results by leveraging AI. ML algorithms can learn the relationship between sequencing data and relating it to the function of the proteins. These algorithms can easily predict mutations. As a result, protein engineering is experiencing rapid growth due to the application of AI and Ml algorithms.\u003Cdiv class=\"table-wrap\" id=\"tab1\"\u003E\u003Cdiv class=\"table-content\"\u003E\u003Ctable frame=\"hsides\" rules=\"groups\"\u003E\u003Ccol\u003E\u003Ccol\u003E\u003Cthead\u003E\u003Ctr\u003E\u003Cth align=\"left\"\u003EProteomics Vocabulary\u003C\u002Fth\u003E\u003Cth align=\"left\"\u003EMeaning\u003C\u002Fth\u003E\u003C\u002Ftr\u003E\u003C\u002Fthead\u003E\u003Ctbody\u003E\u003Ctr\u003E\u003Ctd\u003EAmino acid\u003C\u002Ftd\u003E\u003Ctd\u003EA biological molecule with the general structure\u003Cbr\u003ENH\u003Csub\u003E2\u003C\u002Fsub\u003E-HCR\u003Csub\u003E1\u003C\u002Fsub\u003E-COOH\u003C\u002Ftd\u003E\u003C\u002Ftr\u003E\u003Ctr\u003E\u003Ctd\u003EPeptide\u003C\u002Ftd\u003E\u003Ctd\u003EA short chain of amino acids, coupled thru the amide bond\u003Cbr\u003ENH\u003Csub\u003E2\u003C\u002Fsub\u003E-HCR\u003Csub\u003E1\u003C\u002Fsub\u003E-CO-NH-HCR\u003Csub\u003E2\u003C\u002Fsub\u003E-COOH\u003C\u002Ftd\u003E\u003C\u002Ftr\u003E\u003Ctr\u003E\u003Ctd\u003EProtein\u003C\u002Ftd\u003E\u003Ctd\u003EA molecule composed of one or more chains of amino acids. Proteins often function as part of protein complexes (see [\u003Ca href=\"#B11\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E11\u003C\u002Fa\u003E] for examples)\u003C\u002Ftd\u003E\u003C\u002Ftr\u003E\u003Ctr\u003E\u003Ctd\u003EPost-translation modification\u003C\u002Ftd\u003E\u003Ctd\u003EA modification of a peptide (e.g. acetylation, ubiquitination, phosphorylation, truncation) that occurs after the peptide or protein is synthesized in the cell\u003C\u002Ftd\u003E\u003C\u002Ftr\u003E\u003Ctr\u003E\u003Ctd\u003EBiomarker\u003C\u002Ftd\u003E\u003Ctd\u003EA biological molecule whose concentration is correlated with a disease state or condition.\u003C\u002Ftd\u003E\u003C\u002Ftr\u003E\u003Ctr\u003E\u003Ctd\u003EMass Spectrometry (MS)\u003C\u002Ftd\u003E\u003Ctd\u003EA separation technique that separates charged molecules on the basis of their mass-to-charge ratios (m\u002Fz values). It can be a qualitative or quantitative technique.\u003Cbr\u003EMS is a gas-phase technique that can be interfaced with a separation technique such as gas chromatography or liquid chromatography.\u003C\u002Ftd\u003E\u003C\u002Ftr\u003E\u003Ctr\u003E\u003Ctd\u003EMatrix-assisted Laser Desorption\u002FIonization (MALDI)\u003C\u002Ftd\u003E\u003Ctd\u003EOne of the important “soft” ionization techniques used in biological MS. Sample is co-evaporated with a matrix -- a compound that assists in the transfer of one or more protons to the analyte.\u003Cbr\u003ESample is dried, and is the analyte is ionized with a laser.\u003C\u002Ftd\u003E\u003C\u002Ftr\u003E\u003Ctr\u003E\u003Ctd\u003EElectrospray ionization (ESI)\u003C\u002Ftd\u003E\u003Ctd\u003EOne of the important “soft” ionization techniques used in biological MS. The sample is ionized as it passes thru a high-voltage needle. Typically, 2–3 protons are added to a peptide, while dozens of protons can be transferred to a protein.\u003C\u002Ftd\u003E\u003C\u002Ftr\u003E\u003Ctr\u003E\u003Ctd\u003ETandem mass spectrometry (MS\u002FMS)\u003C\u002Ftd\u003E\u003Ctd\u003EA MS technique that involves two stages of m\u002Fz-based separation. First, a mass spectrum is generated. Then, a selected precursor ion is passed into a region of the instrument where it is fragmented, and then a second mass spectrum is generated.\u003C\u002Ftd\u003E\u003C\u002Ftr\u003E\u003C\u002Ftbody\u003E\u003C\u002Ftable\u003E\u003C\u002Fdiv\u003E\u003Cdiv class=\"table-caption\"\u003E\u003Ch3 class=\"heading\"\u003E\u003C\u002Fh3\u003E\u003Cdiv class=\"text\"\u003E\u003C\u002Fdiv\u003E\u003Cdiv class=\"text\"\u003E\u003C\u002Fdiv\u003E\u003C\u002Fdiv\u003E\u003C\u002Fdiv\u003E\u003C\u002Fp\u003E\u003Cp id=\"p9\"\u003EUncovering biomarkers for drug discovery has been the driving force behind many of the advances in proteomics [\u003Ca href=\"#B12\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E12\u003C\u002Fa\u003E]. The advanced applications of AI, ML, and DL algorithms, have added a new dimension to the understanding of the causes of neurological diseases such as Alzheimer’s and Huntington’s diseases, to the design and development of monoclonal antibodies to fight various types of cancer, and to the development of vaccines to combat infectious diseases. These biomarker studies, in turn, have their roots in relating the presence or absence of certain proteins to diseases states [\u003Ca href=\"#B13\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E13\u003C\u002Fa\u003E, \u003Ca href=\"#B14\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E14\u003C\u002Fa\u003E]. The current trend is movement from a “one-size-fits all” model to personalized\u002Fprecision medicine approach, in which the treatments are based on the needs of the specific individual or sub-populations [\u003Ca href=\"#B15\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E15\u003C\u002Fa\u003E].\u003C\u002Fp\u003E\u003C\u002Fdiv\u003E\u003Cdiv class=\"section\" id=\"sec_2\" data-lvl=\"1\"\u003E\u003Ch2 class=\"heading main-title\"\u003E2. Introduction to artificial intelligence\u003C\u002Fh2\u003E\u003Cp id=\"p10\"\u003ECentral to artificial intelligence is the idea of a model. A model is a mathematical representation of something. If the thing being modeled is physical, the model is sometimes called a digital twin. The model can have several functions, e.g. it can forecast the current situation into the future, it can calculate aspects of the situation that are difficult to measure from other aspects that are easy to measure, and it can represent sophisticated patterns and make them available for practical use in automating a variety of processes. Models based on the laws of physics or engineering are known as first-principles models and are computational in nature. Models generally have placeholders for numerical values. These parameters or coefficients must be determined in some way. For physics-based models, they must be experimentally determined. In artificial intelligence, these coefficients are “learned” from data using computational recipes called algorithms.\u003Cdiv class=\"table-wrap\" id=\"tab2\"\u003E\u003Cdiv class=\"table-content\"\u003E\u003Ctable frame=\"hsides\" rules=\"groups\"\u003E\u003Ccol\u003E\u003Ccol\u003E\u003Cthead\u003E\u003Ctr\u003E\u003Cth align=\"left\"\u003EAI Vocabulary\u003C\u002Fth\u003E\u003Cth align=\"left\"\u003EMeaning\u003C\u002Fth\u003E\u003C\u002Ftr\u003E\u003C\u002Fthead\u003E\u003Ctbody\u003E\u003Ctr\u003E\u003Ctd\u003EArtificial Intelligence (AI)\u003C\u002Ftd\u003E\u003Ctd\u003EUmbrella term for many diverse methods that convert a dataset into a model.\u003C\u002Ftd\u003E\u003C\u002Ftr\u003E\u003Ctr\u003E\u003Ctd\u003EMachine Learning (ML)\u003C\u002Ftd\u003E\u003Ctd\u003ESubset of AI that deals with numerical data, as opposed to image or language data.\u003C\u002Ftd\u003E\u003C\u002Ftr\u003E\u003Ctr\u003E\u003Ctd\u003EDeep Learning (DL)\u003C\u002Ftd\u003E\u003Ctd\u003EModern term for AI that is largely synonymous with AI emphasizing that it uses models of many “layers,” which is a sign of model complexity that became practical after about 2010.\u003C\u002Ftd\u003E\u003C\u002Ftr\u003E\u003Ctr\u003E\u003Ctd\u003ENeural Networks\u003C\u002Ftd\u003E\u003Ctd\u003EOne of the many methods and model types available in AI and ML.\u003C\u002Ftd\u003E\u003C\u002Ftr\u003E\u003Ctr\u003E\u003Ctd\u003ETraining\u003C\u002Ftd\u003E\u003Ctd\u003EThe process of determining model coefficients from data.\u003C\u002Ftd\u003E\u003C\u002Ftr\u003E\u003Ctr\u003E\u003Ctd\u003EInference\u003C\u002Ftd\u003E\u003Ctd\u003EThe process of applying a trained model to a novel data point.\u003C\u002Ftd\u003E\u003C\u002Ftr\u003E\u003Ctr\u003E\u003Ctd\u003ELabels\u003C\u002Ftd\u003E\u003Ctd\u003EThe human-provided information that augments the dataset with the desired result for each data point in the dataset. Using both the data and the labels, the training process attempts to reconstruct the connection between them, allowing the model to compute the output from the data.\u003C\u002Ftd\u003E\u003C\u002Ftr\u003E\u003C\u002Ftbody\u003E\u003C\u002Ftable\u003E\u003C\u002Fdiv\u003E\u003Cdiv class=\"table-caption\"\u003E\u003Ch3 class=\"heading\"\u003E\u003C\u002Fh3\u003E\u003Cdiv class=\"text\"\u003E\u003C\u002Fdiv\u003E\u003Cdiv class=\"text\"\u003E\u003C\u002Fdiv\u003E\u003C\u002Fdiv\u003E\u003C\u002Fdiv\u003E\u003C\u002Fp\u003E\u003Cp id=\"p11\"\u003EMachine learning (ML) or artificial intelligence (AI) is the name given to a large collection of diverse methods that aim to produce models given enough empirical data. They do not require the use of physical laws or the specification of physical characteristics. They determine the dependency of the variables among each other by using the data, and only the data. That is not to say that there is no more need for a human expert. The human expert is essential but the way the expertise is supplied is very different to the first-principles model – for ML or AI the human domain knowledge is supplied in the form of labels. Labels are human-generated manual annotations to empirical data that identify aspects of relevance. In proteomics that might be the name of a certain peptide whose mass spectrometry signature has been determined and so on.\u003C\u002Fp\u003E\u003Cp id=\"p12\"\u003EThe subject of ML and AI has three main parts. First, it consists of many prototypical model types that could be applied to the data at hand. These are known by names such as neural networks, decision trees, or k-means clustering; we will not dive deeply into what these mean. Second, each of these types comes with several recipes, called algorithms that tell us how to calculate the model coefficients from a data set. This calculation is also called training the model. After training, the initial prototype has been turned into a model for the specific dataset that we provided. Third, the finished model must be deployed so that it can be used. It is generally far easier and quicker to evaluate a model than to train a model. In fact, this is one of the primary features of ML and AI that make it so attractive: Once trained, the model can be used in real-time. However, it needs to be embedded in the right infrastructure to unfold its potential.\u003C\u002Fp\u003E\u003Cp id=\"p13\"\u003EAssociated with ML and AI are two essential topics that are at the heart of data science. First, the data must be suitably prepared for learning. Second, the resultant model must be adequately tested, and its performance must be demonstrated using rigorous mathematical means. This pre-processing and post-processing before and after ML or AI is applied to round out the scientific part of a data science project.\u003C\u002Fp\u003E\u003Cp id=\"p14\"\u003EWhile the field of AI began in the 1950’s, it has had a rocky evolution over time. It is really only after about 2010 that the most recent push, known as deep learning (DL), had wide-spread practical success. It is around 2015 that several tasks could be handled by AI with a higher accuracy than by humans. This was and remains the most important practical ramification that underlines the automation benefit of AI – if AI can do something about as well as humans can do it, then we can get AI to do it more rapidly and at lower cost.\u003C\u002Fp\u003E\u003Cp id=\"p15\"\u003EThe difference between the three subjects of AI, ML, and DL is very blurred and most people use these terms as synonyms. As such, it is difficult to try to draw a boundary line between them, as most authors will not agree on any one particular demarcation. It is generally accepted, however, that ML deals only with numerical data, so visual and language data are reserved for AI.\u003C\u002Fp\u003E\u003C\u002Fdiv\u003E\u003Cdiv class=\"section\" id=\"sec_3\" data-lvl=\"1\"\u003E\u003Ch2 class=\"heading main-title\"\u003E3. Protein identification\u003C\u002Fh2\u003E\u003Cp id=\"p16\"\u003EThe proteome is the collection of all proteins present in biofluids, cells, and tissues while proteomics is the study of the proteome. Essentially, in qualitative proteomics, we ask which proteins are present and in quantitative proteomics we ask in what quantities they are present. The first challenges appear when we realize that not all proteins are present in every part of the body in equal measure, for example, in a blood sample. Furthermore, some proteins are present in large quantities while others are present only in trace amounts [\u003Ca href=\"#B16\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E16\u003C\u002Fa\u003E]. In fact, the most common 22 proteins represent over 99% of the total proteome by mass but it is the remaining tens of thousands of proteins that are potentially interesting as biomarkers [\u003Ca href=\"#B17\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E17\u003C\u002Fa\u003E, \u003Ca href=\"#B18\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E18\u003C\u002Fa\u003E, \u003Ca href=\"#B19\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E19\u003C\u002Fa\u003E, \u003Ca href=\"#B20\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E20\u003C\u002Fa\u003E]. There is a practical challenge to resolve the interesting part of the proteome in the presence of an overwhelming amount of what, in data analytic terms, is background noise. The dynamic range of proteins in biofluids or cells or tissues presents a challenge to the detection and identification of low-abundance proteins.\u003C\u002Fp\u003E\u003Cdiv class=\"section\" id=\"sec_3_2\" data-lvl=\"2\"\u003E\u003Ch3 class=\"heading section-title\"\u003E3.1 Protein and peptide mass spectra\u003C\u002Fh3\u003E\u003Cp id=\"p17\"\u003EWorking backwards, determining the amino acid sequence, and thereby the mass of a protein, requires breaking it down to peptides. This can be accomplished by chemical or enzymatic methods, with the resulting peptides being electrically charged leading to partial ionization. They are then separated based on their mass-to-charge (m\u002Fz) ratios, using electrical and\u002For magnetic fields [\u003Ca href=\"#B21\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E21\u003C\u002Fa\u003E]. The technology that makes this practicable is called mass spectrometry (MS) which has been the driving force behind proteomics [\u003Ca href=\"#B22\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E22\u003C\u002Fa\u003E, \u003Ca href=\"#B23\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E23\u003C\u002Fa\u003E]. For the purposes of this paper, we will not go into the physical, biological, or chemical mechanisms underlying this complex procedure. We will simply treat MS as a mechanism that produces a spectrum like shown in \u003Ca href=\"#F1\" class=\"ref-link\" data-ref-style=\"fig\"\u003EFigure 1\u003C\u002Fa\u003E. A peptide mass spectrum can be thought of as a plot of m\u002Fz values (on the x-axis) versus intensities (y axis). Intensities are proportional to the amount of material at that m\u002Fz ratio, as well as also the sensitivity of that peptide. It is immediately clear from the spectrum in \u003Ca href=\"#F1\" class=\"ref-link\" data-ref-style=\"fig\"\u003EFigure 1\u003C\u002Fa\u003E is that certain m\u002Fz values are present in the material and others are absent.\u003C\u002Fp\u003E\u003Cfigure class=\"media-panel\" id=\"F1\"\u003E\u003Cdiv class=\"media\"\u003E\u003Cimg src=\"\u002F\u002Fcdnintech.com\u002Fmedia\u002Fchapter\u002F84631\u002F1722402682-88437392\u002Fmedia\u002FF1.png\" class=\"figure-link\" alt=\"\"\u003E\u003C\u002Fdiv\u003E\u003Cfigcaption class=\"caption\"\u003E\u003Ch4\u003EFigure 1.\u003C\u002Fh4\u003E\u003Cp\u003E\u003Cp id=\"p18\"\u003EProtein identification using peptide mass fingerprinting. The gel plug containing the protein was digested with trypsin, and the peptides were extracted. A sequence coverage of 19% was obtained, allowing the identification of this protein from a database search. Reprinted from [\u003Ca href=\"#B24\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E24\u003C\u002Fa\u003E], with permission.\u003C\u002Fp\u003E\u003C\u002Fp\u003E\u003C\u002Ffigcaption\u003E\u003C\u002Ffigure\u003E\u003C\u002Fdiv\u003E\u003Cdiv class=\"section\" id=\"sec_4_2\" data-lvl=\"2\"\u003E\u003Ch3 class=\"heading section-title\"\u003E3.2 Peptide mass fingerprinting\u003C\u002Fh3\u003E\u003Cp id=\"p19\"\u003EIf the sample that was digested was pure, i.e., if it was generated from the digestion of a single protein, the observed result would be a unique signature or fingerprint of that protein. Protein identification of single proteins or simple mixtures can be done by determining the molecular weights (MWs) of the resulting tryptic fragment ions (if trypsin is the enzyme used to digest the protein) and comparing them to a library of such signatures. This approach is called peptide mass fingerprinting [\u003Ca href=\"#B25\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E25\u003C\u002Fa\u003E].\u003C\u002Fp\u003E\u003C\u002Fdiv\u003E\u003Cdiv class=\"section\" id=\"sec_5_2\" data-lvl=\"2\"\u003E\u003Ch3 class=\"heading section-title\"\u003E3.3 Sequence-tag approach\u003C\u002Fh3\u003E\u003Cp id=\"p20\"\u003EMore complex mixtures require additional separation steps. In about 2000, a method was developed using two dimensions of mass spectrometry – called MS\u002FMS, MS\u003Csup\u003E2\u003C\u002Fsup\u003E, or tandem mass spectrometry. This is ideal for the analysis of peptides because a peptide cleaves between adjacent amino acids. In this technique (called the sequence-tag approach), a peptide is selected based on its mass in the first stage of mass spectrometry, fragmented further, and then mass analyzed again. The amino acid sequence can be manually “read” from the mass differences in the spectrum or the peptide. The peptide molecular weight, and a few fragment ions are often sufficient to identify a protein (\u003Ca href=\"#F2\" class=\"ref-link\" data-ref-style=\"fig\"\u003EFigure 2\u003C\u002Fa\u003E). In the automated version of this approach, the peptide and its parent protein can be identified from a genome-based library of protein amino acid sequences [\u003Ca href=\"#B26\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E26\u003C\u002Fa\u003E, \u003Ca href=\"#B27\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E27\u003C\u002Fa\u003E, \u003Ca href=\"#B28\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E28\u003C\u002Fa\u003E, \u003Ca href=\"#B29\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E29\u003C\u002Fa\u003E].\u003C\u002Fp\u003E\u003Cfigure class=\"media-panel\" id=\"F2\"\u003E\u003Cdiv class=\"media\"\u003E\u003Cimg src=\"\u002F\u002Fcdnintech.com\u002Fmedia\u002Fchapter\u002F84631\u002F1722402682-88437392\u002Fmedia\u002FF2.png\" class=\"figure-link\" alt=\"\"\u003E\u003C\u002Fdiv\u003E\u003Cfigcaption class=\"caption\"\u003E\u003Ch4\u003EFigure 2.\u003C\u002Fh4\u003E\u003Cp\u003E\u003Cp id=\"p21\"\u003EProtein identification using the sequence-tag approach. Identification of a tryptic digest of a gel-separated protein using the sequence-tag approach. The molecular ion of an unknown peptide (at m\u002Fz 908) was selected and fragmented. A nearly complete amino-acid sequence of the peptide T-A-V-D-T-V-F-R was obtained, which led to the identification of the protein KAA1309\u002FKAA1354. Reprinted from [\u003Ca href=\"#B24\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E24\u003C\u002Fa\u003E], with permission.\u003C\u002Fp\u003E\u003C\u002Fp\u003E\u003C\u002Ffigcaption\u003E\u003C\u002Ffigure\u003E\u003C\u002Fdiv\u003E\u003Cdiv class=\"section\" id=\"sec_6_2\" data-lvl=\"2\"\u003E\u003Ch3 class=\"heading section-title\"\u003E3.4 Fingerprinting by AI\u003C\u002Fh3\u003E\u003Cp id=\"p22\"\u003EThe application of AI can vastly improve the untangling the complexity of MS-based data analytics. Several database-search software programs are already in widespread use for the interpretation of LC\u002FMS\u002FMS data. These include Mascot [\u003Ca href=\"#B30\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E30\u003C\u002Fa\u003E], Sequest [\u003Ca href=\"#B31\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E31\u003C\u002Fa\u003E], and X!Tandem [\u003Ca href=\"#B32\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E32\u003C\u002Fa\u003E].\u003C\u002Fp\u003E\u003Cp id=\"p23\"\u003EMass spectral peaks can be characterized using their position on the horizontal axis, width, and height. Therefore, a full spectrum \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m1\"\u003E\u003Cmml:mi\u003Es\u003C\u002Fmml:mi\u003E\u003Cmml:mfenced open=\"(\" close=\")\"\u003E\u003Cmml:mi\u003Ex\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:mfenced\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E is the summation of several Gaussian distributions, one for each peak,\u003C\u002Fp\u003E\u003Cdiv id=\"df_E1\" class=\"formula panel\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m2\" specific-use=\"web-only\"\u003E\u003Cmml:mi\u003Es\u003C\u002Fmml:mi\u003E\u003Cmml:mfenced open=\"(\" close=\")\"\u003E\u003Cmml:mi\u003Ex\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:mfenced\u003E\u003Cmml:mo\u003E=\u003C\u002Fmml:mo\u003E\u003Cmml:munderover\u003E\u003Cmml:mo\u003E∑\u003C\u002Fmml:mo\u003E\u003Cmml:mrow\u003E\u003Cmml:mi\u003Ei\u003C\u002Fmml:mi\u003E\u003Cmml:mo\u003E=\u003C\u002Fmml:mo\u003E\u003Cmml:mn\u003E1\u003C\u002Fmml:mn\u003E\u003C\u002Fmml:mrow\u003E\u003Cmml:mi\u003EN\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:munderover\u003E\u003Cmml:msub\u003E\u003Cmml:mi\u003EH\u003C\u002Fmml:mi\u003E\u003Cmml:mi\u003Ei\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:msub\u003E\u003Cmml:mo mathvariant=\"italic\"\u003Eexp\u003C\u002Fmml:mo\u003E\u003Cmml:mfenced open=\"(\" close=\")\"\u003E\u003Cmml:mfrac\u003E\u003Cmml:mrow\u003E\u003Cmml:mo\u003E−\u003C\u002Fmml:mo\u003E\u003Cmml:msup\u003E\u003Cmml:mfenced open=\"(\" close=\")\"\u003E\u003Cmml:mrow\u003E\u003Cmml:mi\u003Ex\u003C\u002Fmml:mi\u003E\u003Cmml:mo\u003E−\u003C\u002Fmml:mo\u003E\u003Cmml:msub\u003E\u003Cmml:mi\u003Eμ\u003C\u002Fmml:mi\u003E\u003Cmml:mi\u003Ei\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:msub\u003E\u003C\u002Fmml:mrow\u003E\u003C\u002Fmml:mfenced\u003E\u003Cmml:mn\u003E2\u003C\u002Fmml:mn\u003E\u003C\u002Fmml:msup\u003E\u003C\u002Fmml:mrow\u003E\u003Cmml:mrow\u003E\u003Cmml:mn\u003E2\u003C\u002Fmml:mn\u003E\u003Cmml:msup\u003E\u003Cmml:msub\u003E\u003Cmml:mi\u003Eσ\u003C\u002Fmml:mi\u003E\u003Cmml:mi\u003Ei\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:msub\u003E\u003Cmml:mn\u003E2\u003C\u002Fmml:mn\u003E\u003C\u002Fmml:msup\u003E\u003C\u002Fmml:mrow\u003E\u003C\u002Fmml:mfrac\u003E\u003C\u002Fmml:mfenced\u003E\u003Cmml:mo\u003E+\u003C\u002Fmml:mo\u003E\u003Cmml:mi\u003Eε\u003C\u002Fmml:mi\u003E\u003Cmml:mfenced open=\"(\" close=\")\"\u003E\u003Cmml:mi\u003Ex\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:mfenced\u003E\u003C\u002Fmml:math\u003E\u003Cspan class=\"equ\"\u003EE1\u003C\u002Fspan\u003E\u003C\u002Fdiv\u003E\u003Cp id=\"p24\"\u003Ewhere \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m3\"\u003E\u003Cmml:msub\u003E\u003Cmml:mi\u003EH\u003C\u002Fmml:mi\u003E\u003Cmml:mi\u003Ei\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:msub\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E is the peak height, \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m4\"\u003E\u003Cmml:msub\u003E\u003Cmml:mi\u003Eμ\u003C\u002Fmml:mi\u003E\u003Cmml:mi\u003Ei\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:msub\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E is the peak position, \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m5\"\u003E\u003Cmml:msub\u003E\u003Cmml:mi\u003Eσ\u003C\u002Fmml:mi\u003E\u003Cmml:mi\u003Ei\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:msub\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E is the line width, \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m6\"\u003E\u003Cmml:mi\u003EN\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E is the number of peaks present in the spectrum, and \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m7\"\u003E\u003Cmml:mi\u003Eε\u003C\u002Fmml:mi\u003E\u003Cmml:mfenced open=\"(\" close=\")\"\u003E\u003Cmml:mi\u003Ex\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:mfenced\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E is the noise. With this approximation, we readily obtain \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m8\"\u003E\u003Cmml:mi\u003EN\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E tuples of \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m9\"\u003E\u003Cmml:mfenced open=\"(\" close=\")\" separators=\",,\"\u003E\u003Cmml:msub\u003E\u003Cmml:mi\u003EH\u003C\u002Fmml:mi\u003E\u003Cmml:mi\u003Ei\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:msub\u003E\u003Cmml:msub\u003E\u003Cmml:mi\u003Eμ\u003C\u002Fmml:mi\u003E\u003Cmml:mi\u003Ei\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:msub\u003E\u003Cmml:msub\u003E\u003Cmml:mi\u003Eσ\u003C\u002Fmml:mi\u003E\u003Cmml:mi\u003Ei\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:msub\u003E\u003C\u002Fmml:mfenced\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E that characterize the spectrum. If these peaks correspond to peptides, this is the “peptide mass fingerprint” of the protein in the sample. This can now be compared to a library of \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m10\"\u003E\u003Cmml:mi\u003EM\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E reference spectra \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m11\"\u003E\u003Cmml:msub\u003E\u003Cmml:mi\u003Eγ\u003C\u002Fmml:mi\u003E\u003Cmml:mi\u003Ej\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:msub\u003E\u003Cmml:mfenced open=\"(\" close=\")\"\u003E\u003Cmml:mi\u003Ex\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:mfenced\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E for a library index \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m12\"\u003E\u003Cmml:mi\u003Ej\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E. In fact, we look for the best linear combination of reference spectra that explains the spectrum at hand, which is the optimization problem\u003C\u002Fp\u003E\u003Cdiv id=\"df_E2\" class=\"formula panel\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m13\" specific-use=\"web-only\"\u003E\u003Cmml:munder\u003E\u003Cmml:mo\u003Emin\u003C\u002Fmml:mo\u003E\u003Cmml:msub\u003E\u003Cmml:mi\u003Eα\u003C\u002Fmml:mi\u003E\u003Cmml:mi\u003Ej\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:msub\u003E\u003C\u002Fmml:munder\u003E\u003Cmml:mfenced open=\"(\" close=\")\"\u003E\u003Cmml:mrow\u003E\u003Cmml:mi\u003Es\u003C\u002Fmml:mi\u003E\u003Cmml:mfenced open=\"(\" close=\")\"\u003E\u003Cmml:mi\u003Ex\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:mfenced\u003E\u003Cmml:mo\u003E−\u003C\u002Fmml:mo\u003E\u003Cmml:munderover\u003E\u003Cmml:mo\u003E∑\u003C\u002Fmml:mo\u003E\u003Cmml:mrow\u003E\u003Cmml:mi\u003Ej\u003C\u002Fmml:mi\u003E\u003Cmml:mo\u003E=\u003C\u002Fmml:mo\u003E\u003Cmml:mn\u003E1\u003C\u002Fmml:mn\u003E\u003C\u002Fmml:mrow\u003E\u003Cmml:mi\u003EM\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:munderover\u003E\u003Cmml:msub\u003E\u003Cmml:mi\u003Eα\u003C\u002Fmml:mi\u003E\u003Cmml:mi\u003Ej\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:msub\u003E\u003Cmml:msub\u003E\u003Cmml:mi\u003Eγ\u003C\u002Fmml:mi\u003E\u003Cmml:mi\u003Ej\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:msub\u003E\u003Cmml:mfenced open=\"(\" close=\")\"\u003E\u003Cmml:mi\u003Ex\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:mfenced\u003E\u003C\u002Fmml:mrow\u003E\u003C\u002Fmml:mfenced\u003E\u003C\u002Fmml:math\u003E\u003Cspan class=\"equ\"\u003EE2\u003C\u002Fspan\u003E\u003C\u002Fdiv\u003E\u003Cp id=\"p25\"\u003ENumerically, we will want to add the additional criterion that this should be a sparse fit, i.e., as many \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m14\"\u003E\u003Cmml:msub\u003E\u003Cmml:mi\u003Eα\u003C\u002Fmml:mi\u003E\u003Cmml:mi\u003Ej\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:msub\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E as possible should be equal to zero. As every \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m15\"\u003E\u003Cmml:msub\u003E\u003Cmml:mi\u003Eγ\u003C\u002Fmml:mi\u003E\u003Cmml:mi\u003Ej\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:msub\u003E\u003Cmml:mfenced open=\"(\" close=\")\"\u003E\u003Cmml:mi\u003Ex\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:mfenced\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E uniquely corresponds to a specific protein, this results in an identification of the proteins present, with \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m16\"\u003E\u003Cmml:msub\u003E\u003Cmml:mi\u003Eα\u003C\u002Fmml:mi\u003E\u003Cmml:mi\u003Ej\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:msub\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E providing the relative abundance of each.\u003C\u002Fp\u003E\u003C\u002Fdiv\u003E\u003Cdiv class=\"section\" id=\"sec_7_2\" data-lvl=\"2\"\u003E\u003Ch3 class=\"heading section-title\"\u003E3.5 Temporal evolution of spectra\u003C\u002Fh3\u003E\u003Cp id=\"p26\"\u003EWhen a MS analysis is repeated at regular intervals in time leading to a time-series analysis of spectra, i.e., \u003Cspan class=\"inline-formula\"\u003E\u003Cmml:math xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" id=\"m17\"\u003E\u003Cmml:mi\u003Es\u003C\u002Fmml:mi\u003E\u003Cmml:mfenced open=\"(\" close=\")\"\u003E\u003Cmml:mi\u003Ex\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:mfenced\u003E\u003Cmml:mo\u003E→\u003C\u002Fmml:mo\u003E\u003Cmml:mi\u003Es\u003C\u002Fmml:mi\u003E\u003Cmml:mfenced open=\"(\" close=\")\" separators=\",\"\u003E\u003Cmml:mi\u003Ex\u003C\u002Fmml:mi\u003E\u003Cmml:mi\u003Et\u003C\u002Fmml:mi\u003E\u003C\u002Fmml:mfenced\u003E\u003C\u002Fmml:math\u003E\u003C\u002Fspan\u003E, changes over time can be detected. This is especially interesting as molecular effects in a protein’s environment can induce structural changes that imply functional changes in that protein. Mass spectrometry can detect such changes [\u003Ca href=\"#B33\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E33\u003C\u002Fa\u003E]. We have been able to observe changes due to protein degradation as a function of time, and therefore recommend procedures to avoid adverse conditions that could affect clinical results. In \u003Ca href=\"#F3\" class=\"ref-link\" data-ref-style=\"fig\"\u003EFigure 3\u003C\u002Fa\u003E, we display such a time-series which we used to detect protein degradation during processing delays that occur while a plasma sample is waiting to be processed in a clinical setting [\u003Ca href=\"#B34\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E34\u003C\u002Fa\u003E] or during transport at room temperature (\u003Ca href=\"#F3\" class=\"ref-link\" data-ref-style=\"fig\"\u003EFigure 3\u003C\u002Fa\u003E) [\u003Ca href=\"#B35\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E35\u003C\u002Fa\u003E].\u003C\u002Fp\u003E\u003Cfigure class=\"media-panel\" id=\"F3\"\u003E\u003Cdiv class=\"media\"\u003E\u003Cimg src=\"\u002F\u002Fcdnintech.com\u002Fmedia\u002Fchapter\u002F84631\u002F1722402682-88437392\u002Fmedia\u002FF3.png\" class=\"figure-link\" alt=\"\"\u003E\u003C\u002Fdiv\u003E\u003Cfigcaption class=\"caption\"\u003E\u003Ch4\u003EFigure 3.\u003C\u002Fh4\u003E\u003Cp\u003E\u003Cp id=\"p27\"\u003EHeatmap representing 143 proteins quantified in at least 80% of the 50 plasma samples thawed (a) quickly on ice (QU), or (B) overnight at 4°C (O\u002FN). All values were normalized to the respective time point 0 h. missing values are depicted in gray. Yellow areas represent log2 values from −0.25 to 0.25, corresponding to an approximately 1.19-fold difference in protein concentration compared to the respective time point 0 h. blue and red colors indicate concentrations that are >1.2-fold lower\u002Fhigher than the 0 h time point. Sections of the heatmaps with MRM assays that are unstable or particularly stable are shown, and gene names represented by the surrogate peptides quantified are given. (reprinted from Gaithers, et al. 2022 [\u003Ca href=\"#B34\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E34\u003C\u002Fa\u003E], with permission).\u003C\u002Fp\u003E\u003C\u002Fp\u003E\u003C\u002Ffigcaption\u003E\u003C\u002Ffigure\u003E\u003Cp id=\"p28\"\u003EAI has specific impact on MS based proteomics, wherein it facilitates the assignment of fragmentation spectra to actual peptide identifications, and thereby assisting with the quantitation. This data integration has an influence across wide range of proteomics applications including; expression proteomics, networks highlighting complex protein interactions in cellular pathways, impact of post-translational modifications (PTMs), and cross-functional relationships with other omics studies. PTMs of proteins act as signals for localization, degradation, and other functions. Analyzing PTM-bearing peptides is challenging considering the wide spectrum of isoforms, and the complexity of their fragmentation spectra. They might not even follow the tryptic peptide cleavage rules. AI applications can be adopted to solve this challenge and the initial work was highlighted by Wang et al. in 2017 [\u003Ca href=\"#B36\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E36\u003C\u002Fa\u003E], and Yang et al. in 2021 [\u003Ca href=\"#B37\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E37\u003C\u002Fa\u003E]. This can also be applied to Major Histo Compatibility (MHC) Class I and II peptides. The identification rates of these peptides were increased by several fold, as highlighted by Li et al. in 2020 [\u003Ca href=\"#B38\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E38\u003C\u002Fa\u003E].\u003C\u002Fp\u003E\u003Cp id=\"p29\"\u003EIn addition to direct spectral analysis using DL, the application can also be extended for predicting chromatographic separation retention times. This can be accomplished by direct modeling or through transfer learning [\u003Ca href=\"#B39\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E39\u003C\u002Fa\u003E]. Combining DL for predicting MS\u002FMS spectra with retention times provides more value than experimental library search using Data Independent Acquisition (DIA) [\u003Ca href=\"#B40\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E40\u003C\u002Fa\u003E]. This in turn opens the door for combining Dl with real-time data acquisition. The image captioning feature in DL can be used to sequence peptides from MS\u002FMS without the need for a database (DeepNovo) and has shown a 5–20% improvement over other DeNovo sequencing tools [\u003Ca href=\"#B41\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E41\u003C\u002Fa\u003E]. The DIA-NN (Data Independent Acquisition Neural networks) program is one example where deep neural networks were able to increase the sensitivity of matching DIA fragmentation to \u003Cem\u003E\u003Citalic xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" xmlns:xlink=\"http:\u002F\u002Fwww.w3.org\u002F1999\u002Fxlink\" xmlns:xsi=\"http:\u002F\u002Fwww.w3.org\u002F2001\u002FXMLSchema-instance\"\u003Ein-silico\u003C\u002Fitalic\u003E\u003C\u002Fem\u003E derived spectral libraries [\u003Ca href=\"#B42\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E42\u003C\u002Fa\u003E].\u003C\u002Fp\u003E\u003Cp id=\"p30\"\u003EThere are challenges to MS based analysis of proteins and this pertains to accurately recognizing the protein patterns. MS analysis is done by reviewing smaller parts of amino acid sequences, and then this data is searched against a database, and assigned to proteins. In doing so, some proteins are missed. This challenge can be overcome by training neural networks to recognize protein patterns, with minimal or no errors. Commercial software such as Prosit from the technical University of Munich is available to accomplish this task. AI can also be used to analyze large datasets, and Ml algorithms have been developed by scientists from Novo Nordisk Foundation for Protein Research, and Niels Bohr Institute for recognizing protein patterns in a rapid manner [\u003Ca href=\"#B43\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E43\u003C\u002Fa\u003E].\u003C\u002Fp\u003E\u003C\u002Fdiv\u003E\u003Cdiv class=\"section\" id=\"sec_8_2\" data-lvl=\"2\"\u003E\u003Ch3 class=\"heading section-title\"\u003E3.6 Analysis of mass spectra\u003C\u002Fh3\u003E\u003Cp id=\"p31\"\u003EMuch of the data generated by “shotgun” (non-targeted) proteomics is predictable by ML if adequate training data is available. ML methods can analyze the patterns in the data to identify biomarkers, and Dl can be used to extract additional features. Over the past two decades, AI has been increasingly applied to bottom-up MS-based proteomics analyses. In this regard, ML algorithms, have been used for peptide identification, predicting retention times [\u003Ca href=\"#B44\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E44\u003C\u002Fa\u003E, \u003Ca href=\"#B45\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E45\u003C\u002Fa\u003E, \u003Ca href=\"#B46\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E46\u003C\u002Fa\u003E], as well as for MS\u002FMS spectrum prediction [\u003Ca href=\"#B5\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E5\u003C\u002Fa\u003E, \u003Ca href=\"#B47\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E47\u003C\u002Fa\u003E, \u003Ca href=\"#B48\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E48\u003C\u002Fa\u003E]. The earliest ML tool for proteomics was the Percolator algorithm [\u003Ca href=\"#B7\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E7\u003C\u002Fa\u003E], which was able to increase the number of identified peptides by 5–16% [\u003Ca href=\"#B49\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E49\u003C\u002Fa\u003E]. These algorithms has found value in identifying peptides, and have also been used for matching MS1-identified features with value for protein quantitation [\u003Ca href=\"#B50\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E50\u003C\u002Fa\u003E]. It was Zhou, et al. in 2017 [\u003Ca href=\"#B51\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E51\u003C\u002Fa\u003E] who used DL for predicting fragmentation spectra of a peptide from its sequence. DL approaches have gained much value for predicting peptide behavior from sequences, considering the availability of large amount of peptides in databases such as PRIDE [\u003Ca href=\"#B52\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E52\u003C\u002Fa\u003E]. In 2020, Liu, et al. [\u003Ca href=\"#B53\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E53\u003C\u002Fa\u003E] showed that DL can be used to predict full MS\u002FMS spectra, as opposed to just backbone fragment intensities.\u003C\u002Fp\u003E\u003Cp id=\"p32\"\u003EIn comparing experimental results from one sample to a library of reference data that have themselves been obtained from experiments, we must be aware that measurement errors and noise are ubiquitous. Both sides of the comparison are not just imprecise, but some peptides might be missing in the data – peptides expected by the library might be missing in our data sample, or peptides present in our data sample might be missing in the library [\u003Ca href=\"#B54\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E54\u003C\u002Fa\u003E]. In practice, the matching is often done via a similarity score [\u003Ca href=\"#B21\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E21\u003C\u002Fa\u003E]. Despite this development, the key challenge for mass spectrometry in proteomics is to develop data analysis tools [\u003Ca href=\"#B8\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E8\u003C\u002Fa\u003E].\u003C\u002Fp\u003E\u003Cp id=\"p33\"\u003EIn some of the established analysis tool, outliers are removed by performing the Grubbs test [\u003Ca href=\"#B55\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E55\u003C\u002Fa\u003E], but the foundational assumption of this test is that the data is normally distributed. In the case of a normal spectrum, this is unfortunately not the case, as most data points are at the low end of the relative abundance scale. We must find other ways of cleaning up a spectrum and analyzing it.\u003C\u002Fp\u003E\u003Cp id=\"p34\"\u003EDepending on the technique, the peaks in the mass spectrum will either be individual peptides (in peptide mass fingerprinting), or fragment ions (in a tandem MS (i.e., an MS\u002FMS) experiment). The peak heights or intensities depend on the relative sensitivities of the peptide or fragment ion and the abundances of that component in the mixture under investigation. As with all experimental methods, the presence of noise makes analysis difficult and can hide small peaks in the spectrum; the well-known signal-to-noise (S\u002FN) ratio challenge. Similarly, this analysis depends on the availability of a library of known spectra for proteins or peptides – standards against which the experimental spectrum must be compared. The scientific analysis of the data must begin with an experimental spectrum by removing as much noise from it as possible. There are two common ways of doing this: filtering and subtraction.\u003C\u002Fp\u003E\u003Cp id=\"p35\"\u003EOne method of filtering is to transform the spectrum into its companion domain by using the Fourier Transform. We may then delete the low frequency (high-band-pass filter) or high frequency (low-band-pass filter) features. We can also multiply the frequency features by a factor (Wiener filter [\u003Ca href=\"#B56\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E56\u003C\u002Fa\u003E]) in order to suppress the noisy elements not caught by band passing. If we have a more sophisticated idea of the mechanism producing the noise, we could use a Kalman filter [\u003Ca href=\"#B57\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E57\u003C\u002Fa\u003E] as well, which is a statistical estimation of the joint probability distribution of all independent variables in an effort to extract a linear quadratic probabilistic model of the error. After this, the spectrum is transformed back into its original form, again using a Fourier Transform. It is now de-noised. These methods are very computationally efficient and have been incorporated into in many different software tools. If the noise source is deemed to be white noise (i.e., structure free), then these methods are probably the best one can do.\u003C\u002Fp\u003E\u003Cp id=\"p36\"\u003ESubtraction is a method by which the noise signal is simply subtracted from the real signal. For this, we must either measure the noise signal or model it in some computational way. The way to experimentally measure the noise is to pass a well-known pure protein source through the identical experimental setup and measure its signal. This would best be done with several different pure proteins so that the signals could be compared, and a holistic noise spectrum built up. Modeling the noise source amounts to constructing a first-principles computer simulation of the process, which may not be commercially feasible.\u003C\u002Fp\u003E\u003Cp id=\"p37\"\u003EUnfortunately, real-world noise is always structured and never completely white. Thus, removing structured noise consumes significantly more effort. This is the reason that so much developmental work in mass spectrometry instrumentation has been focused on the physical apparatus in trying to get ever cleaner signals [\u003Ca href=\"#B58\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E58\u003C\u002Fa\u003E]. Nonetheless, these can always be cleaned further by data analytics.\u003C\u002Fp\u003E\u003C\u002Fdiv\u003E\u003C\u002Fdiv\u003E\u003Cdiv class=\"section\" id=\"sec_10\" data-lvl=\"1\"\u003E\u003Ch2 class=\"heading main-title\"\u003E4. Applications\u003C\u002Fh2\u003E\u003Cp id=\"p38\"\u003EIn living systems, proteins can exert their functional influence either individually and\u002For by interacting with other molecules. The latter can be studied in-depth by using interactomics to pull down the complexes, and then analyzing the network of molecules involved in the interactions. The data derived from this analysis needs to be integrated and studied along with data from genomics, epigenomics, transcriptomics, metabolomics, and lipidomics. AI is gaining increased attention both for biomarker discovery, and validation, as well as for integrating proteomics data with other omics data along with clinical data to derive a more complete picture of the patient’s health status. Specifically the data can be used in predicting 3D structure of a target protein, drug-protein interactions, and \u003Cem\u003E\u003Citalic xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" xmlns:xlink=\"http:\u002F\u002Fwww.w3.org\u002F1999\u002Fxlink\" xmlns:xsi=\"http:\u002F\u002Fwww.w3.org\u002F2001\u002FXMLSchema-instance\"\u003Ede novo\u003C\u002Fitalic\u003E\u003C\u002Fem\u003E drug design.\u003C\u002Fp\u003E\u003Cdiv class=\"section\" id=\"sec_10_2\" data-lvl=\"2\"\u003E\u003Ch3 class=\"heading section-title\"\u003E4.1 Biomarker discovery and validation\u003C\u002Fh3\u003E\u003Cp id=\"p39\"\u003EMS based proteomics can be leveraged to identify the “needle in the haystack” along with quantitative data, with one or more unique proteins turning out to be the biomarkers of choice for clinical diagnostics, and\u002For drug discovery -- potentially leading to development of therapeutics. Commencing the analysis with a large sample set from multiple cohorts, proteomic datasets that can be assembled into correlation maps [\u003Ca href=\"#B59\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E59\u003C\u002Fa\u003E]. This will allow us to identify and understand proteins that are co-regulated and those that are connected in their functional pathways. ML can aid in uncovering signals and predictors, leading to the creation of decision trees, and grouping classes based on specific features. Methods are also available to differentiate between classes based on unique features, and it assists in interpretability, and accurate classification [\u003Ca href=\"#B60\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E60\u003C\u002Fa\u003E]. One pitfall to watch out for is the over-fitting arising from the training dataset. Identification of biomarkers by ML needs rigorous oversight on classifying the positives, and negatives diagonally, with the incorrect ones being off-diagonal, and reflected in the ROC curves.\u003C\u002Fp\u003E\u003Cp id=\"p40\"\u003EPractical outcomes for applying ML techniques to proteomic data sets for circulating biomarkers in alcoholic liver disease was shown by Matthias Mann’s group [\u003Ca href=\"#B61\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E61\u003C\u002Fa\u003E]. Additionally, they also showed the classification of biomarkers for Alzheimer’s disease from CSF in a three cohort study [\u003Ca href=\"#B62\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E62\u003C\u002Fa\u003E]. In their observations, they felt that the ML methods performed well, with the only consideration being the data points used to train the model. The next step would be to translate these potential biomarkers into a clinical test, which will undergo a rigorous scrutiny by the regulatory agencies. If this involves a multi-analyte panel, then the entire pipeline, including the ML method needs to be simple, robust, explainable, and reproducible in order to obtain the regulatory approval. In this regard the ML acts as the final step in filtering the complex proteomics dataset into selectable biomarker candidates that can pass the acid test of the regulatory bodies. One of the key considerations for the outcomes from the AI based analysis is the chance of bias when the datasets are derived from a non-diverse source [\u003Ca href=\"#B63\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E63\u003C\u002Fa\u003E]. Overcoming this bias will require the analysis of samples from diverse populations.\u003C\u002Fp\u003E\u003Cp id=\"p41\"\u003EAlthough a few proteins in a cell are present in high abundance, it is the remaining tens of thousands of proteins that are potentially interesting as biomarkers [\u003Ca href=\"#B17\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E17\u003C\u002Fa\u003E, \u003Ca href=\"#B18\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E18\u003C\u002Fa\u003E, \u003Ca href=\"#B19\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E19\u003C\u002Fa\u003E, \u003Ca href=\"#B20\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E20\u003C\u002Fa\u003E]. To determine a biomarker of a disease, one has to be able to quantitatively compare samples from patients with different disease states. This poses additional challenges, the first is detection sensitivity, the second (if the method is to have clinical value), it has to be reproducible in both intra- and inter laboratory studies [\u003Ca href=\"#B64\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E64\u003C\u002Fa\u003E, \u003Ca href=\"#B65\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E65\u003C\u002Fa\u003E].\u003C\u002Fp\u003E\u003Cp id=\"p42\"\u003EAI has been successfully applied to biomarker identification based on MS data [\u003Ca href=\"#B10\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E10\u003C\u002Fa\u003E]. In a recent paper [\u003Ca href=\"#B66\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E66\u003C\u002Fa\u003E], machine learning was used to accurately predict the survival of COVID patients on the day they were admitted to the hospital ICU, based on the plasma concentrations of 10 proteins and 5 metabolites, as determined by MS. While humans can visually detect differences in the concentration of a single protein biomarker, but for sorting out the data from thousands of proteins, computerized methods are needed. In effect, one is trying to detect a decision surface in n-dimensional space. This is typically done by Principal Component Analysis (PCA). Both the proteomics and metabolomics markers allowed the prediction of survival separately, with accuracies of 83% (AUC 0.90) and 84% (AUC 0.93), respectively. When combined, however, the concentration measurements of all markers yielded an accuracy of 92% (AUC 0.97), see \u003Ca href=\"#F4\" class=\"ref-link\" data-ref-style=\"fig\"\u003EFigure 4\u003C\u002Fa\u003E.\u003C\u002Fp\u003E\u003Cfigure class=\"media-panel\" id=\"F4\"\u003E\u003Cdiv class=\"media\"\u003E\u003Cimg src=\"\u002F\u002Fcdnintech.com\u002Fmedia\u002Fchapter\u002F84631\u002F1722402682-88437392\u002Fmedia\u002FF4.png\" class=\"figure-link\" alt=\"\"\u003E\u003C\u002Fdiv\u003E\u003Cfigcaption class=\"caption\"\u003E\u003Ch4\u003EFigure 4.\u003C\u002Fh4\u003E\u003Cp\u003E\u003Cp id=\"p43\"\u003EReliable and accurate prediction of survival upon hospitalization. (A) The performance of the support vector machine classifier was used to predict COVID-19 patient survival based on proteomics (10 proteins), metabolomics (5 metabolites), and combined multi-omics models (10 proteins +5 metabolites) and using all data points (days 0, 2, 7 after admission). (B) Receiver-operating characteristic (ROC) curves show that the best performance was obtained with the multi-omics model (10 proteins +5 metabolites). (C) ROC curve analysis for proteomics-only, metabolomics-only, and multi-omics models at different time points after admission (days 0, 2, or 7). Upper row – Proteomics model based on 10 proteins, middle row – Metabolomics model based on 5 metabolites, bottom row – Combined multi-omics model based on 10 proteins and 5 metabolites. (figure and figure legend from [\u003Ca href=\"#B66\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E66\u003C\u002Fa\u003E], with permission).\u003C\u002Fp\u003E\u003C\u002Fp\u003E\u003C\u002Ffigcaption\u003E\u003C\u002Ffigure\u003E\u003Cp id=\"p44\"\u003EWhen combined with real-world evidence (RWE) about diseases [\u003Ca href=\"#B67\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E67\u003C\u002Fa\u003E, \u003Ca href=\"#B68\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E68\u003C\u002Fa\u003E] from published literature, databases, images, patient health records, and clinical data [\u003Ca href=\"#B69\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E69\u003C\u002Fa\u003E, \u003Ca href=\"#B70\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E70\u003C\u002Fa\u003E] the overall insight lends itself well for the current trends in personalized\u002Fprecision medicine. From individual to cohorts, this analysis can be extended to population studies, where ML, DL, and text mining lend themselves to the extraction of relationships between all interacting partners [\u003Ca href=\"#B71\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E71\u003C\u002Fa\u003E, \u003Ca href=\"#B72\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E72\u003C\u002Fa\u003E]. Knowledge graphs [\u003Ca href=\"#B73\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E73\u003C\u002Fa\u003E] highlight the complex interactions in a biological network, and the insight derived from analyzing these knowledge graphs are more insightful. Clinical Knowledge Graphs (CKG) which contain millions of protein nodes, and greater than 100 million connections were developed by Mathias Mann’s group [\u003Ca href=\"#B74\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E74\u003C\u002Fa\u003E]. This in turn has been used to integrate knowledge from the proteome project [\u003Ca href=\"#B75\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E75\u003C\u002Fa\u003E], and ML and DL algorithms can be leveraged to study these knowledge graphs.\u003C\u002Fp\u003E\u003C\u002Fdiv\u003E\u003Cdiv class=\"section\" id=\"sec_11_2\" data-lvl=\"2\"\u003E\u003Ch3 class=\"heading section-title\"\u003E4.2 Multiomics and proteomic data integration\u003C\u002Fh3\u003E\u003Cp id=\"p45\"\u003EDeriving a meaningful outcome that is representative of the final phenotype also needs the interaction of other omics data along with that of the proteomics data. Molecular interactions in living systems are complex, and proteins tend to interact with nucleic acids, other proteins, lipids, and small molecules in exerting the cellular function. Proteins bind to DNA or RNA which, in turn, has an influence on replication, transcription, DNA repair, and transport, translation, splicing, and silencing in the case of RNA [\u003Ca href=\"#B76\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E76\u003C\u002Fa\u003E]. Protein-protein interactions are critical in many cellular processes; for example in the use of therapeutic monoclonal antibodies [\u003Ca href=\"#B77\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E77\u003C\u002Fa\u003E], peptide drugs [\u003Ca href=\"#B78\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E78\u003C\u002Fa\u003E], and chimeric antigen receptor T cells [\u003Ca href=\"#B79\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E79\u003C\u002Fa\u003E]. Proteins interact with lipids in multiple ways and this has functional significance such as selective transport, and cell-cell communication [\u003Ca href=\"#B80\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E80\u003C\u002Fa\u003E]. Finally, protein interactions with small molecules especially drugs can be analyzed by leveraging mass spectrometry [\u003Ca href=\"#B81\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E81\u003C\u002Fa\u003E].\u003C\u002Fp\u003E\u003Cp id=\"p46\"\u003EElucidating these complex interactions of proteins with other molecules can be accomplished by using baits in a pull-down assay [\u003Ca href=\"#B82\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E82\u003C\u002Fa\u003E]. These interactome analyses generates complex data, and the application of ML, and DL technologies is still at the early stages with most of it being used for data pre-processing [\u003Ca href=\"#B83\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E83\u003C\u002Fa\u003E]. As of today, the lack of detailed analyses using AI techniques probably arises from the lack of adequate sample sets of data, validation data, and the ability to interpret the data [\u003Ca href=\"#B63\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E63\u003C\u002Fa\u003E]. Ribosomal Binding Protein-RNA (RBP-RNA) interactions are of importance to drug discovery and to other biological functions, because of their critical role in gene expression [\u003Ca href=\"#B84\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E84\u003C\u002Fa\u003E]. The paradigms for studying these interactions include; binding site prediction, binding preference prediction, and a merged approach that predicts both the binding sites, and binding preference [\u003Ca href=\"#B85\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E85\u003C\u002Fa\u003E]. DL methodologies add value to the study of RBP-RNA interactions by operating directly on the structure data [\u003Ca href=\"#B86\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E86\u003C\u002Fa\u003E, \u003Ca href=\"#B87\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E87\u003C\u002Fa\u003E].\u003C\u002Fp\u003E\u003Cp id=\"p47\"\u003EProteins tend to operate through complexes to maintain the functional aspects of a living organism. Understanding the interactome, will intern shed light on the complex aspects of biology in these organisms, and also facilitate drug development. Lack of structural knowledge of many proteins prevented the construction of an interactome. This changed in 2020 when DeepMind released AI technologies termed “AlphaFold”, and “RoseTTAFold”, that enabled the prediction of protein structures from the gene sequences. Researchers from UT Southwestern and University of Washington, used AI and evolutionary analysis to produce 3D models of eukaryotic protein interactions. Their study, published in Science ([\u003Ca href=\"#B88\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E88\u003C\u002Fa\u003E], identified 100 protein complexes, and provided structural models for 700 previously uncharacterized ones [\u003Ca href=\"#B89\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E89\u003C\u002Fa\u003E].\u003C\u002Fp\u003E\u003Cp id=\"p48\"\u003EIt has been estimated that 25% of cellular proteins are membrane proteins [\u003Ca href=\"#B90\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E90\u003C\u002Fa\u003E] that can be either transmembrane or positioned on the periphery [\u003Ca href=\"#B91\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E91\u003C\u002Fa\u003E]. Cellular membranes are one of the fundamental protective elements of the cell wherein the proteins are embedded within the lipid bilayer. Besides offering structural integrity, these proteins also have a functional role ranging from molecular transport, signal transduction, cell-cell recognition, attachment, and enzymatic activity. Molecular dynamics (MD) simulations have been used to understand the lipid-protein interactions, as well as the structure and dynamics as influenced by the proteins in the membranes [\u003Ca href=\"#B80\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E80\u003C\u002Fa\u003E]. Ion channels are an example of protein-lipid structures formed in the membranes, and they are directly or indirectly associated with cellular disorders indicative of certain diseases. Hence these ion channels are used as targets for drug discovery and therapy. AI techniques have proven to be of value in predicting the related genes, mutations, and the relationship to certain diseases. Taju et al. has used DL methods for the classification of ion transporters, and ion channels from membrane proteins, by training the deep neural networks using the position-specific scoring matrix profile as the input [\u003Ca href=\"#B92\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E92\u003C\u002Fa\u003E]. ML has been used to derive the feature vectors of ion channels including SVMProt, and k-skip-n-gram methods, 188-, and 400 dimensional features, respectively [\u003Ca href=\"#B93\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E93\u003C\u002Fa\u003E].\u003C\u002Fp\u003E\u003C\u002Fdiv\u003E\u003Cdiv class=\"section\" id=\"sec_12_2\" data-lvl=\"2\"\u003E\u003Ch3 class=\"heading section-title\"\u003E4.3 Structural proteomics\u003C\u002Fh3\u003E\u003Cp id=\"p49\"\u003EIn addition to its value for biomarker discovery, and validation (Section 4.1), and proteomic data integration from multiomics analysis (Section 4.2), AI also offers immense value in structural proteomics. This arises from the fact that proteins have 4 levels of structure, namely primary, secondary, tertiary, and quaternary. The complexity of the structure increases as the proteins assumes the tertiary, and quaternary structure, and associates with other molecules. A typical protein contains 200–400 amino acids (\u003Ca href=\"#F5\" class=\"ref-link\" data-ref-style=\"fig\"\u003EFigure 5\u003C\u002Fa\u003E) and typically folds into a three-dimensional shape. It has been estimated that the number of possible protein folds found in nature is anywhere from a few hundred [\u003Ca href=\"#B97\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E97\u003C\u002Fa\u003E] to approximately 2200 [\u003Ca href=\"#B98\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E98\u003C\u002Fa\u003E] different folds. Protein misfolding leading to aggregation of the prion protein is the cause of Creutzfeldt-Jakob disease (i.e., “mad cow disease” in animals) and of cystic fibrosis, most often caused by one missing amino acid (F508Δ) out of the &sim;1480 amino acids in the normal CFTR protein. Protein misfolding may also be the involved in diseases such as Alzheimer’s or Huntington’s disease. On the other hand, proteins such as antibodies can also be the cure for viral and bacterial infections.\u003C\u002Fp\u003E\u003Cfigure class=\"media-panel\" id=\"F5\"\u003E\u003Cdiv class=\"media\"\u003E\u003Cimg src=\"\u002F\u002Fcdnintech.com\u002Fmedia\u002Fchapter\u002F84631\u002F1722402682-88437392\u002Fmedia\u002FF5.png\" class=\"figure-link\" alt=\"\"\u003E\u003C\u002Fdiv\u003E\u003Cfigcaption class=\"caption\"\u003E\u003Ch4\u003EFigure 5.\u003C\u002Fh4\u003E\u003Cp\u003E\u003Cp id=\"p50\"\u003EDistribution of protein lengths in \u003Cem\u003E\u003Citalic xmlns:mml=\"http:\u002F\u002Fwww.w3.org\u002F1998\u002FMath\u002FMathML\" xmlns:xlink=\"http:\u002F\u002Fwww.w3.org\u002F1999\u002Fxlink\" xmlns:xsi=\"http:\u002F\u002Fwww.w3.org\u002F2001\u002FXMLSchema-instance\"\u003EEscherichia coli\u003C\u002Fitalic\u003E\u003C\u002Fem\u003E, budding yeast and human HeLa cells. (TOP) protein length is calculated in amino acids (AA), based on the coding sequences in the genome. (BOTTOM) distributions are drawn after weighting each gene with the protein copy number inferred from mass spectrometry proteomic studies [\u003Ca href=\"#B94\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E94\u003C\u002Fa\u003E], M9 + glucose [\u003Ca href=\"#B95\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E95\u003C\u002Fa\u003E, \u003Ca href=\"#B96\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E96\u003C\u002Fa\u003E]. Continuous lines are Gaussian kernel-density estimates for the distributions serving as a guide to the eye. (figure and figure legend from [\u003Ca href=\"#B11\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E11\u003C\u002Fa\u003E], \u003Ca href=\"http:\u002F\u002Fbook.bionumbers.org\u002Fhow-big-is-the-average-protein\u002F#:%E2%88%BC:text=A%20simple%20rule%20of%20thumb,proteins%20that%20make%20cells%20work\"\u003Ehttp:\u002F\u002Fbook.bionumbers.org\u002Fhow-big-is-the-average-protein\u002F#:&sim;:text=A%20simple%20rule%20of%20thumb,proteins%20that%20make%20cells%20work\u003C\u002Fa\u003E).\u003C\u002Fp\u003E\u003C\u002Fp\u003E\u003C\u002Ffigcaption\u003E\u003C\u002Ffigure\u003E\u003Cp id=\"p51\"\u003EMolecular modeling and molecular dynamics simulations have already played a large part in protein structure determination [\u003Ca href=\"#B99\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E99\u003C\u002Fa\u003E, \u003Ca href=\"#B100\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E100\u003C\u002Fa\u003E, \u003Ca href=\"#B101\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E101\u003C\u002Fa\u003E, \u003Ca href=\"#B102\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E102\u003C\u002Fa\u003E, \u003Ca href=\"#B103\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E103\u003C\u002Fa\u003E]. The breakthrough Alphafold [\u003Ca href=\"#B104\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E104\u003C\u002Fa\u003E, \u003Ca href=\"#B105\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E105\u003C\u002Fa\u003E] program will undoubtedly also play a large role in protein structure determination, although there are limitations on its applicability, particularly for dynamic systems and stems where there can be multiple states of a protein [\u003Ca href=\"#B106\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E106\u003C\u002Fa\u003E, \u003Ca href=\"#B107\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E107\u003C\u002Fa\u003E].\u003C\u002Fp\u003E\u003Cp id=\"p52\"\u003ECrosslinking has played a key role in protein structure determination, both for individual proteins and protein complexes. Crosslinks of different lengths, connecting specific amino acid residues, and can be used as a molecular ruler [\u003Ca href=\"#B108\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E108\u003C\u002Fa\u003E] to determine the distances between these residues in a folded protein. Crosslinks connecting residues that are too far apart in a structural model crosslinker can be used to “rule out” certain structures (pun intended). Because a mass spectrum is essentially a plot of intensity vs. mass, crosslinked peptides can be detected because they have higher molecular weights than unlinked residues. Crosslinkers have been specifically designed for use with MS-based research [\u003Ca href=\"#B109\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E109\u003C\u002Fa\u003E, \u003Ca href=\"#B110\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E110\u003C\u002Fa\u003E, \u003Ca href=\"#B111\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E111\u003C\u002Fa\u003E]. Features included in these crosslinkers include the use of stable isotopes to create unique and detectable signatures (patterns) in the mass spectrum that can be detected by software programs [\u003Ca href=\"#B110\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E110\u003C\u002Fa\u003E].\u003C\u002Fp\u003E\u003Cp id=\"p53\"\u003EIn addition to providing confirmation of MD results, MS-derived crosslinking data has been used as constraints in molecular dynamics simulations [\u003Ca href=\"#B112\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E112\u003C\u002Fa\u003E], with the result of reducing the conformational space and achieving the correct protein folding on practical time scales [\u003Ca href=\"#B113\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E113\u003C\u002Fa\u003E]. We have applied this approach to structural studies of prion monomers and β-oligomers [\u003Ca href=\"#B114\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E114\u003C\u002Fa\u003E], as well as native α-synuclein [\u003Ca href=\"#B115\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E115\u003C\u002Fa\u003E] and the “unstructured” Tau protein [\u003Ca href=\"#B116\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E116\u003C\u002Fa\u003E].\u003C\u002Fp\u003E\u003C\u002Fdiv\u003E\u003C\u002Fdiv\u003E\u003Cdiv class=\"section\" id=\"sec_14\" data-lvl=\"1\"\u003E\u003Ch2 class=\"heading main-title\"\u003E5. Challenges of artificial intelligence\u003C\u002Fh2\u003E\u003Cp id=\"p54\"\u003EApplying AI to proteomics is challenging for some reasons that are unique to proteomics [\u003Ca href=\"#B117\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E117\u003C\u002Fa\u003E] or medicine [\u003Ca href=\"#B118\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E118\u003C\u002Fa\u003E], and also for some reasons that are general [\u003Ca href=\"#B119\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E119\u003C\u002Fa\u003E]. The most important of these challenges are as follows. First, expertise in both AI and proteomics is required and this is rarely available in the same individual and thus requires interdisciplinary teamwork [\u003Ca href=\"#B120\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E120\u003C\u002Fa\u003E]. Second, data must generally be labeled or annotated by human experts to prepare the data for AI model training, which is a time-consuming and expensive activity that dominates the total cost of the project [\u003Ca href=\"#B121\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E121\u003C\u002Fa\u003E]. Third, models trained on readily available, small, or restricted datasets often fail to generalize to real-life datasets and thus do not deliver value [\u003Ca href=\"#B122\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E122\u003C\u002Fa\u003E]. Fourth, AI cannot be a “black box” and so either the model must be interpretable [\u003Ca href=\"#B123\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E123\u003C\u002Fa\u003E], or the model’s output explainable [\u003Ca href=\"#B124\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E124\u003C\u002Fa\u003E] to provide actionable insights to a human actor. Fifth, it is a misconception that AI is rapid and inexpensive because it is automated – in fact, doing responsible and sustainable AI requires a long-term investment in people and infrastructure.\u003C\u002Fp\u003E\u003Cp id=\"p55\"\u003EAnother challenge specific to proteomics, and biomarker discovery is the overfitting of the training data for ML and DL data [\u003Ca href=\"#B63\" class=\"ref-link\" data-ref-style=\"bibr\"\u003E63\u003C\u002Fa\u003E], where the model is biased towards the information in the training data, leaving out the information in new and unseen data. This could lead to differences in biomarkers identified in different patient cohorts. This challenge could be overcome by leveraging the largest training and testing data, followed by cross-validation on both the training, and unseen data.\u003C\u002Fp\u003E\u003Cp id=\"p56\"\u003EAI is not a specific technology but rather an umbrella term for many different methods. The overriding idea is the creation of a mathematical summary of empirical data that can be used to interpolate and extrapolate beyond the empirical data to make predictions about new situations. The dividing line between AI and related disciplines, such as statistics, can get blurred.\u003C\u002Fp\u003E\u003C\u002Fdiv\u003E\u003Cdiv class=\"section\" id=\"sec_15\" data-lvl=\"1\"\u003E\u003Ch2 class=\"heading main-title\"\u003E6. Conclusion and future outlook\u003C\u002Fh2\u003E\u003Cp id=\"p57\"\u003EAI represents a powerful toolbox that represents substantial value for proteomics and life-sciences in general. There are many applications already, as we have seen, and many more will arise in the near future. These are necessarily inter-disciplinary efforts that require experts from both AI and the domain. Notwithstanding the above mentioned challenges, the work for AI is dominated by preparing a suitable, large, clean, representative, and significant dataset. This will make AI’s promise more accessible to those who already have large amounts of data and the experts to prepare such data for analysis.\u003C\u002Fp\u003E\u003Cp id=\"p58\"\u003EThe value of AI lies in automation and in making processes accessible in the first place through its speed and automation. The most promising such direction is personalized medicine. If a single individual’s proteome could be inferred from a blood sample in an instant, the troublesome proteins or the absent proteins could be identified, and suitable strategies developed for producing counter-agents or the missing links, this could produce a treatment specific to that person as opposed to giving everyone with some condition the same mass-produced treatment and hoping for the best.\u003C\u002Fp\u003E\u003C\u002Fdiv\u003E\n","keywords":"proteomics, mass-spectrometry, artificial intelligence, pattern recognition, diagnosis","chapterPDFUrl":"https:\u002F\u002Fcdn.intechopen.com\u002Fpdfs\u002F84631.pdf","chapterXML":"https:\u002F\u002Fmts.intechopen.com\u002Fsource\u002Fxml\u002F84631.xml","webChapterXML":"s3:\u002F\u002Fintech-chapter-xmls\u002Fxmls-chapter\u002F84631\u002F1720599422-1929542960\u002F","downloadPdfUrl":"\u002Fchapter\u002Fpdf-download\u002F84631","previewPdfUrl":"\u002Fchapter\u002Fpdf-preview\u002F84631","cdnMediaBaseUrl":"s3:\u002F\u002Fintech-cdn\u002Fmedia\u002Fchapter\u002F84631\u002F1722402682-88437392\u002F","totalDownloads":192,"totalViews":38,"totalCrossrefCites":0,"totalDimensionsCites":1,"dateSubmitted":"September 30th 2022","dateReviewed":"October 3rd 2022","datePrePublished":"November 3rd 2022","datePublished":"July 31st 2024","dateFinished":"November 3rd 2022","readingETA":"0","abstract":"Multiomic analysis comprises genomics, proteomics, and metabolomics leads to meaningful insights but necessitates sifting through voluminous amounts of complex data. Proteomics in particular focuses on the end product of gene expression – i.e., proteins. The mass spectrometric approach has proven to be a workhorse for the qualitative and quantitative study of protein interactions as well as post-translational modifications (PTMs). A key component of mass spectrometry (MS) is spectral data analysis, which is complex and has many challenges as it involves identifying patterns across a multitude of spectra in combination with the meta-data related to the origin of the spectrum. Artificial Intelligence (AI) along with Machine Learning (ML), and Deep Learning (DL) algorithms have gained more attention lately for analyzing the complex spectral data to identify patterns and to create networks of value for biomarker discovery. In this chapter, we discuss the nature of MS proteomic data, the relevant AI methods, and demonstrate their applicability. We also show that AI can successfully identify biomarkers and aid in the diagnosis, prognosis, and treatment of specific diseases.","reviewType":"peer-reviewed","bibtexUrl":"\u002Fchapter\u002Fbibtex\u002F84631","risUrl":"\u002Fchapter\u002Fris\u002F84631","signatures":"Patrick Bangert, Nandha Kumar Balasubramaniam, Carol E. Parker and Christoph H. Borchers","isPublished":true,"isOnlineFirst":false,"isDeactivated":0,"noAds":0,"subseries":null,"book":{"id":"14229","type":"book","title":"Bioinformatics and Medical Informatics Annual Volume 2024","subtitle":null,"fullTitle":"Bioinformatics and Medical Informatics Annual Volume 2024","slug":"bioinformatics-and-medical-informatics-annual-volume-2024","isPublished":true,"publishedDate":"July 31st 2024","bookSignature":"Slawomir Wilczynski","coverURL":"https:\u002F\u002Fcdn.intechopen.com\u002Fbooks\u002Fimages_new\u002F14229.jpg","cdnCoverURL":"https:\u002F\u002Fcdnintech.com\u002Fbooks\u002F14229\u002F1721637962-1022817547\u002Fcover.jpg","cdnCoverURL300":"https:\u002F\u002Fcdnintech.com\u002Fbooks\u002F14229\u002F1721637962-1022817547\u002Fcover-300.jpg","cdnWebCoverURL":"https:\u002F\u002Fcdnintech.com\u002Fbooks\u002F14229\u002F1721637903-1431020901\u002Fweb-cover.jpg","cdnWebCoverURL300":"https:\u002F\u002Fcdnintech.com\u002Fbooks\u002F14229\u002F1721637903-1431020901\u002Fweb-cover-300.jpg","cdnCoverWithTextURL":"https:\u002F\u002Fcdnintech.com\u002Fbooks\u002F14229\u002F1722500403-508663298\u002Fcover-text.jpg","cdnCoverWithTextURL300":"https:\u002F\u002Fcdnintech.com\u002Fbooks\u002F14229\u002F1722500403-508663298\u002Fcover-text-300.jpg","licenceType":"CC BY 4.0","editedByType":"Edited by","isbn":"978-0-85014-034-7","printIsbn":"978-0-85014-033-0","pdfIsbn":"978-0-85014-035-4","isAvailableForWebshopOrdering":true,"isDeactivated":false,"kuFlag":false,"noAdsSub":0,"editors":[{"id":"351533","title":"Associate Prof.","name":"Slawomir","middleName":null,"surname":"Wilczynski","slug":"slawomir-wilczynski","fullName":"Slawomir Wilczynski"}],"productType":{"id":"5","title":"Annual Volume","chapterContentType":"chapter","authoredCaption":"Authored by"}},"authors":[{"id":"482133","title":"Dr.","name":"Patrick","middleName":null,"surname":"Bangert","fullName":"Patrick Bangert","slug":"patrick-bangert","email":"p.bangert@samsung.com","position":null,"cdnProfilePictureURL":"\u002F\u002Fcdnintech.com\u002Fweb\u002Ffrontend\u002Fwww\u002Fassets\u002F45.123\u002Fauthor.svg","institution":null},{"id":"491116","title":"Dr.","name":"Nandha Kumar","middleName":null,"surname":"Balasubramaniam","fullName":"Nandha Kumar Balasubramaniam","slug":"nandha-kumar-balasubramaniam","email":"nandha.balasubramaniam@oracle.com","position":null,"cdnProfilePictureURL":"\u002F\u002Fcdnintech.com\u002Fweb\u002Ffrontend\u002Fwww\u002Fassets\u002F45.123\u002Fauthor.svg","institution":null},{"id":"491117","title":"Dr.","name":"Christoph H.","middleName":null,"surname":"Borchers","fullName":"Christoph H. Borchers","slug":"christoph-h.-borchers","email":"christoph.borchers@mcgill.ca","position":null,"cdnProfilePictureURL":"\u002F\u002Fcdnintech.com\u002Fweb\u002Ffrontend\u002Fwww\u002Fassets\u002F45.123\u002Fauthor.svg","institution":{"name":"McGill University","institutionURL":null,"country":{"name":"Canada"}}},{"id":"501131","title":"Dr.","name":"Carol E.","middleName":null,"surname":"Parker","fullName":"Carol E. Parker","slug":"carol-e.-parker","email":"ceparker.editing@gmail.com","position":null,"cdnProfilePictureURL":"\u002F\u002Fcdnintech.com\u002Fweb\u002Ffrontend\u002Fwww\u002Fassets\u002F45.123\u002Fauthor.svg","institution":null}],"sections":[{"id":"sec_1","title":"1. Introduction","level":"1"},{"id":"sec_2","title":"2. Introduction to artificial intelligence","level":"1"},{"id":"sec_3","title":"3. Protein identification","level":"1"},{"id":"sec_3_2","title":"3.1 Protein and peptide mass spectra","level":"2"},{"id":"sec_4_2","title":"3.2 Peptide mass fingerprinting","level":"2"},{"id":"sec_5_2","title":"3.3 Sequence-tag approach","level":"2"},{"id":"sec_6_2","title":"3.4 Fingerprinting by AI","level":"2"},{"id":"sec_7_2","title":"3.5 Temporal evolution of spectra","level":"2"},{"id":"sec_8_2","title":"3.6 Analysis of mass spectra","level":"2"},{"id":"sec_10","title":"4. Applications","level":"1"},{"id":"sec_10_2","title":"4.1 Biomarker discovery and validation","level":"2"},{"id":"sec_11_2","title":"4.2 Multiomics and proteomic data integration","level":"2"},{"id":"sec_12_2","title":"4.3 Structural proteomics","level":"2"},{"id":"sec_14","title":"5. Challenges of artificial intelligence","level":"1"},{"id":"sec_15","title":"6. 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Machine Learning and Data Science in the Oil and Gas Industry: Best Practices, Tools, and Case Studies. Amsterdam, The Netherlands: Elsevier Inc.; Nov 2021;\u003Cbold\u003E1\u003C\u002Fbold\u003E:748968\u003C\u002Fmixed-citation\u003E\u003C\u002Fref\u003E"},{"id":"B120","body":"\u003Cref id=\"B120\"\u003E\u003Cmixed-citation publication-type=\"other\"\u003EBangert P. The Necessity for Collaboration Between Data Scientists and Domain Experts the SPE Symposium: Artificial Intelligence - Towards a Resilient and Efficient Energy Industry, Virtual. Amsterdam, The Netherlands: Elsevier; 2021:SPE-208634-MS. DOI: 10.2118\u002F208634-MS\u003C\u002Fmixed-citation\u003E\u003C\u002Fref\u003E"},{"id":"B121","body":"\u003Cref id=\"B121\"\u003E\u003Cmixed-citation publication-type=\"journal\"\u003EBangert P, Moon H, Woo JO, Didari S, Hao H. Active learning performance in labeling radiology images is 90% effective. Frontiers in radiology. 2021. Available from: \u003Cext-link ext-link-type=\"uri\" xlink:href=\"https:\u002F\u002Fwww.frontiersin.org\u002Farticles\u002F10.3389\u002Ffradi.2021.748968\u002Ffull\"\u003Ehttps:\u002F\u002Fwww.frontiersin.org\u002Farticles\u002F10.3389\u002Ffradi.2021.748968\u002Ffull\u003C\u002Fext-link\u003E\u003C\u002Fmixed-citation\u003E\u003C\u002Fref\u003E"},{"id":"B122","body":"\u003Cref id=\"B122\"\u003E\u003Cmixed-citation publication-type=\"journal\"\u003EKleppe A, Skrede OJ, De Raedt S, Liestøl K, Kerr DJ, Danielsen HE. Designing deep learning studies in cancer diagnostics. Nature Reviews. Cancer. 2021;\u003Cbold\u003E21\u003C\u002Fbold\u003E:199-211\u003C\u002Fmixed-citation\u003E\u003C\u002Fref\u003E"},{"id":"B123","body":"\u003Cref id=\"B123\"\u003E\u003Cmixed-citation publication-type=\"journal\"\u003ERudin C. Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead. Nature machine intelligence. 2019;\u003Cbold\u003E1\u003C\u002Fbold\u003E:206-215\u003C\u002Fmixed-citation\u003E\u003C\u002Fref\u003E"},{"id":"B124","body":"\u003Cref id=\"B124\"\u003E\u003Cmixed-citation publication-type=\"journal\"\u003ELinardatos P, Papastefanopoulos V, Kotsiantis S. Explainable AI: A review of machine learning interpretability methods. Entropy. 2020;\u003Cbold\u003E23\u003C\u002Fbold\u003E:18\u003C\u002Fmixed-citation\u003E\u003C\u002Fref\u003E"}],"footnotes":[],"contributors":[{"corresp":"yes","contributorFullName":"Patrick Bangert","address":"p.bangert@samsung.com","affiliation":"\u003Cul class=\"list\"\u003E\u003Cli\u003ESamsung SDS, San Jose, California, USA\u003C\u002Fli\u003E\u003C\u002Ful\u003E"},{"corresp":"yes","contributorFullName":"Nandha Kumar Balasubramaniam","address":"ceekpeace@gmail.com","affiliation":"\u003Cul class=\"list\"\u003E\u003Cli\u003EOracle, Redwood City, CA, USA\u003C\u002Fli\u003E\u003C\u002Ful\u003E"},{"corresp":null,"contributorFullName":"Carol E. Parker","address":null,"affiliation":"\u003Cul class=\"list\"\u003E\u003Cli\u003ESegal Cancer Proteomics Centre, Lady Davis Institute for Medical Research, Jewish General Hospital, McGill University, Montreal, Quebec, Canada\u003C\u002Fli\u003E\u003C\u002Ful\u003E"},{"corresp":null,"contributorFullName":"Christoph H. 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Aridity poses a threat to the environment and the economy, and to security, development, food security, and social life around the world. The causes of increased aridity are complex and are thought to be both natural and man-made. The causes of drought include such factors as climate change, population growth, soil erosion, inappropriate irrigation, poor farming methods, soil, water, and groundwater contamination, urbanization, deforestation, improper water management, and desertification of arid and semi-arid zones. This book contains valuable scientific studies on such aspects of aridity as surface and groundwater management, land use, and agricultural applications. Case studies from different geographies and planets are included.","editors":[{"id":"170083","title":"Associate Prof.","name":"Murat","surname":"Eyvaz","slug":"murat-eyvaz","fullName":"Murat Eyvaz"}],"equalEditorOne":null,"equalEditorTwo":null,"equalEditorThree":null,"productType":{"id":"1","title":"Edited Volume"}},{"id":"11934","type":"book","slug":"clean-energy-technologies-hydrogen-and-gasification-processes","isPublished":true,"title":"Clean Energy Technologies","subtitle":"Hydrogen and Gasification Processes","coverURL":"https:\u002F\u002Fcdn.intechopen.com\u002Fbooks\u002Fimages_new\u002F11934.jpg","abstract":"Increasing urbanization, population growth, and climate change require responsible consumption of all resources, primarily energy. Worldwide energy efficiency applications, renewable energy, and related technologies will be the driving force in the energy sector. It is envisaged that large amounts of carbon emissions can be prevented by changing the electricity production and consumption habits of societies and transforming them into renewable energy and related technologies in energy systems. This book presents valuable scientific studies on clean energy technologies and analyzes hydrogen production processes in detail.","editors":[{"id":"170083","title":"Associate Prof.","name":"Murat","surname":"Eyvaz","slug":"murat-eyvaz","fullName":"Murat Eyvaz"}],"equalEditorOne":null,"equalEditorTwo":null,"equalEditorThree":null,"productType":{"id":"1","title":"Edited Volume"}},{"id":"11131","type":"book","slug":"drought-impacts-and-management","isPublished":true,"title":"Drought","subtitle":"Impacts and Management","coverURL":"https:\u002F\u002Fcdn.intechopen.com\u002Fbooks\u002Fimages_new\u002F11131.jpg","abstract":"The deterioration of the balance between precipitation and evaporation and the long duration of this situation is known as drought. Drought adversely affects many environmental components such as soil processes, vegetation growth, wildlife, water quality, and aquatic ecosystems. While drought has unfavorable impacts on both surface and groundwater resources, hydrological regimes can also be affected by it, changing the chemistry of surface waters and the runoff pathway, which can negatively influence water quality. Today one out of every three people is faced with the drought and water shortage risk, thus water scarcity and water stress. This book presents studies on the various forms and severity of the drought that can occur in almost every region of the world as well as their causes and impacts. It analyzes in detail the complex drought phenomenon, which has a significant impact on water resources, agriculture, energy production, human health, and forest fires.","editors":[{"id":"170083","title":"Associate Prof.","name":"Murat","surname":"Eyvaz","slug":"murat-eyvaz","fullName":"Murat Eyvaz"}],"equalEditorOne":null,"equalEditorTwo":null,"equalEditorThree":null,"productType":{"id":"1","title":"Edited Volume"}},{"id":"10976","type":"book","slug":"water-conservation-inevitable-strategy","isPublished":true,"title":"Water Conservation","subtitle":"Inevitable Strategy","coverURL":"https:\u002F\u002Fcdn.intechopen.com\u002Fbooks\u002Fimages_new\u002F10976.jpg","abstract":"To conserve water, one of the most valuable and vital resources in the world, management and public strategies, processes to reduce water consumption in industrial\u002Fcommercial applications, and methods such as smart irrigation systems have been proposed. Local authorities have focused on infrastructure operations to prevent water losses and flow measurements have begun to be followed more closely. The use of greywater for partial recycling of water for household purposes and rainwater harvesting systems are being encouraged. In addition, there is more research on water conservation, its smart use, and recycling of used water being conducted. This book presents valuable scientific research on water and land management, groundwater management, and water\u002Fwastewater treatment applications for the conservation of water.","editors":[{"id":"170083","title":"Associate Prof.","name":"Murat","surname":"Eyvaz","slug":"murat-eyvaz","fullName":"Murat Eyvaz"}],"equalEditorOne":null,"equalEditorTwo":null,"equalEditorThree":null,"productType":{"id":"1","title":"Edited Volume"}},{"id":"8178","type":"book","slug":"water-chemistry","isPublished":true,"title":"Water Chemistry","subtitle":null,"coverURL":"https:\u002F\u002Fcdn.intechopen.com\u002Fbooks\u002Fimages_new\u002F8178.jpg","abstract":"Water, which plays an important role in every aspect of our daily lives, is the most valuable natural resource we have on this planet. Drinking, bathing, cooking, regeneration, cleaning, production, energy, and many other uses of water originate from some of its versatile, useful, basic, and unique features. The access, purification, and reuse of water on our planet, which is of course not endless and not available for direct use, is directly related to the water chemistry that explores its inimitable properties. This book includes research on water chemistry-related applications in environmental management and sustainable environmental issues such as water and wastewater treatment, water quality management, and other similar topics. The book consists of three sections, namely, water treatment, wastewater treatment, and water splitting, respectively, and includes 11 chapters. In these chapters, water-wastewater remediation methods, nanomaterials in water treatment, and water splitting processes are comprehensively reviewed in terms of water chemistry.The editors would like to record their sincere thanks to the authors for their contributions.","editors":[{"id":"170083","title":"Associate Prof.","name":"Murat","surname":"Eyvaz","slug":"murat-eyvaz","fullName":"Murat Eyvaz"}],"equalEditorOne":null,"equalEditorTwo":null,"equalEditorThree":null,"productType":{"id":"1","title":"Edited Volume"}},{"id":"7693","type":"book","slug":"green-chemistry-applications","isPublished":true,"title":"Green Chemistry Applications","subtitle":null,"coverURL":"https:\u002F\u002Fcdn.intechopen.com\u002Fbooks\u002Fimages_new\u002F7693.jpg","abstract":"Green chemistry is defined as the use of a dozen principles that reduce or eliminate hazardous materials in the design, manufacture, and use of chemical products. Today, it is understood that focusing on precautions to reduce or eliminate existing pollution sources is more effective than looking for a cleaning path after exiting. This book presents the principles of green chemistry for clean production in light of the latest technological developments and increasing environmental awareness. Chapters cover such topics as synthesis and applications of nanomaterials for energy and environmental applications, climate process, alternative green energy sources, and removal of emerging pollutants from water.","editors":[{"id":"170083","title":"Associate Prof.","name":"Murat","surname":"Eyvaz","slug":"murat-eyvaz","fullName":"Murat Eyvaz"}],"equalEditorOne":null,"equalEditorTwo":null,"equalEditorThree":null,"productType":{"id":"1","title":"Edited Volume"}},{"id":"8804","type":"book","slug":"water-and-wastewater-treatment","isPublished":true,"title":"Water and Wastewater Treatment","subtitle":null,"coverURL":"https:\u002F\u002Fcdn.intechopen.com\u002Fbooks\u002Fimages_new\u002F8804.jpg","abstract":"The use of water, one of the most valuable and vital resources in the world, should respond to growing needs, and used water should not have negative effects on the environment. Research on the reduction of used water and wastewater quantities, post-use treatment, or reuse\u002Frecovery methods is increasing day by day. These studies focus on finding the most appropriate method from both technical and economic perspectives. In this book, emerging technologies and materials used in the treatment, reuse, or recovery of various kinds of water and wastewaters are examined. The book consists of valuable scientific research specifically including desalination and use of renewable energy, nanomaterials, biosorbents, photocatalytic treatment, as well as riverbank filtration and wetlands. The editor would like to record his sincere thanks to the authors for their contributions.","editors":[{"id":"170083","title":"Associate Prof.","name":"Murat","surname":"Eyvaz","slug":"murat-eyvaz","fullName":"Murat Eyvaz"}],"equalEditorOne":null,"equalEditorTwo":null,"equalEditorThree":null,"productType":{"id":"1","title":"Edited Volume"}}],"chaptersAuthored":[{"id":"46863","title":"Preventing of Cathode Passivation\u002FDeposition in Electrochemical Treatment Methods – A Case Study on Winery Wastewater with Electrocoagulation","slug":"preventing-of-cathode-passivation-deposition-in-electrochemical-treatment-methods-a-case-study-on-wi","abstract":null,"signatures":"Murat Eyvaz, Ercan Gürbulak, Serdar Kara and Ebubekir Yüksel","isPublished":true,"isOnlineFirst":false,"isDeactivated":0,"authors":[{"id":"170083","title":"Associate Prof.","name":"Murat","surname":"Eyvaz","fullName":"Murat Eyvaz","slug":"murat-eyvaz","email":"murateyvaz@gmail.com"},{"id":"170084","title":"Dr.","name":"Ercan","surname":"Gürbulak","fullName":"Ercan Gürbulak","slug":"ercan-gurbulak","email":"egurbulak@gmail.com"},{"id":"170085","title":"Dr.","name":"Ebubekir","surname":"Yüksel","fullName":"Ebubekir Yüksel","slug":"ebubekir-yuksel","email":"yuksel@gyte.edu.tr"},{"id":"170086","title":"Dr.","name":"Serdar","surname":"Kara","fullName":"Serdar Kara","slug":"serdar-kara","email":"kara@gyte.edu.tr"}],"book":{"id":"3859","title":"Modern Electrochemical Methods in Nano, Surface and Corrosion Science","slug":"modern-electrochemical-methods-in-nano-surface-and-corrosion-science","productType":{"id":"1","title":"Edited Volume"}}},{"id":"51191","title":"A Review of State-of-the-Art Technologies in Dye-Containing Wastewater Treatment – The Textile Industry Case","slug":"a-review-of-state-of-the-art-technologies-in-dye-containing-wastewater-treatment-the-textile-industr","abstract":"Recently, new single or hybrid\u002Fcombined processes have attracted much attention for treatment of textile and dyeing wastewaters. These processes which may be termed as “state of the art technologies” are membrane separation processes, ultrasonic, photochemical and electrochemical processes. Although the conventional methods still have been tried with some new materials such as, new adsorbents or coagulants, employing the new generation methods such as, electrocagulation-electrooxidation, sonooxidation or photo oxidation are gaining in popularity when the treatment of textile wastewaters is discussed. The purpose of the book chapter is to bring an overview on the new treatment methods for textile wastewaters, one of the most important source of environmental pollution. Despite the fact that there is no uniform standard currently, many countries have legalized some strict discharging standards and scientists and researchers face new technologies including electrical, sonic, magnetic, optical and thermal methods. Although many researches on treatment of synthetic or real wastewaters with various methods are available, very few researches have been carried out on the cutting-edge technologies. Moreover, there are a lot of review article or book chapters on textile wastewater treatment processes individually based on each conventional process such as coagulation, adsorption, chemical oxidation, and biological decolorization. Therefore, in this part of the book, following major and minor titles are stated truly on the aforementioned new technologies. Besides, these parts are not only about cutting-edge technologies, but also related with conventional methods and their new applications in colored wastewater treatment area briefly.","signatures":"Serkan Arslan, Murat Eyvaz, Ercan Gürbulak and Ebubekir Yüksel","isPublished":true,"isOnlineFirst":false,"isDeactivated":0,"authors":[{"id":"170083","title":"Associate Prof.","name":"Murat","surname":"Eyvaz","fullName":"Murat Eyvaz","slug":"murat-eyvaz","email":"murateyvaz@gmail.com"},{"id":"176699","title":"Dr.","name":"Ercan","surname":"Gürbulak","fullName":"Ercan Gürbulak","slug":"ercan-gurbulak","email":"egurbulak@gtu.edu.tr"},{"id":"176700","title":"MSc.","name":"Serkan","surname":"Arslan","fullName":"Serkan Arslan","slug":"serkan-arslan","email":"arslan_kan@gmx.de"},{"id":"176701","title":"Prof.","name":"Ebubekir","surname":"Yüksel","fullName":"Ebubekir Yüksel","slug":"ebubekir-yuksel","email":"yuksel@gtu.edu.tr"}],"book":{"id":"5086","title":"Textile Wastewater Treatment","slug":"textile-wastewater-treatment","productType":{"id":"1","title":"Edited Volume"}}},{"id":"55837","title":"Textile Materials in Liquid Filtration Practices: Current Status and Perspectives in Water and Wastewater Treatment","slug":"textile-materials-in-liquid-filtration-practices-current-status-and-perspectives-in-water-and-wastew","abstract":"Filtration is considered the keystone of water and wastewater treatment and is used for various purposes, such as sludge dewatering and concentrating any solution. Moreover, as an advanced filtration technology, membranes can remove materials ranging from large visible particles to molecular and ionic chemical species. Proper selection of filter media\u002Fmembrane material in filtration processes is often the most important consideration for assuring efficient separation. Filter media can be classified by their materials of construction, such as cotton, wool, linen, glass fiber, porous carbon, metals, and rayons. Recently, new polymeric materials have been used both individually and\u002For blended in filtration processes for the treatment of waters and wastewaters. The purpose of this chapter is to bring an overview on the textile-originated filter materials in filtration applications from conventional filtration to advanced membrane processes. Although many researches on filter media are available, very few researches have been carried out on the cutting-edge technologies about using filter materials on filtration processes from classical to advanced membrane processes. Therefore, in this part of the book, following major and minor titles are stated truly on the aforementioned new technologies and linked with conventional methods in water and wastewater treatment applications.","signatures":"Murat Eyvaz, Serkan Arslan, Ercan Gürbulak and Ebubekir Yüksel","isPublished":true,"isOnlineFirst":false,"isDeactivated":0,"authors":[{"id":"170083","title":"Associate Prof.","name":"Murat","surname":"Eyvaz","fullName":"Murat Eyvaz","slug":"murat-eyvaz","email":"murateyvaz@gmail.com"},{"id":"170084","title":"Dr.","name":"Ercan","surname":"Gürbulak","fullName":"Ercan Gürbulak","slug":"ercan-gurbulak","email":"egurbulak@gmail.com"},{"id":"176700","title":"MSc.","name":"Serkan","surname":"Arslan","fullName":"Serkan Arslan","slug":"serkan-arslan","email":"arslan_kan@gmx.de"},{"id":"176701","title":"Prof.","name":"Ebubekir","surname":"Yüksel","fullName":"Ebubekir Yüksel","slug":"ebubekir-yuksel","email":"yuksel@gtu.edu.tr"}],"book":{"id":"5921","title":"Textiles for Advanced Applications","slug":"textiles-for-advanced-applications","productType":{"id":"1","title":"Edited Volume"}}},{"id":"59495","title":"Forward Osmosis Membranes – A Review: Part I","slug":"forward-osmosis-membranes-a-review-part-i","abstract":"Forward osmosis (FO) is a technical term describing the natural phenomenon of osmosis: the transport of water molecules across a semi-permeable membrane. The osmotic pressure difference is the driving force of water transport, as opposed to pressure-driven membrane processes. A concentrated draw solution (DS) with osmotic pressure draws water molecules from the feed solution (FS) through a semi-permeable membrane to the DS. The diluted DS is then reconcentrated to recycle the draw solutes as well as to produce purified water. As a major disadvantage, nature of FO membranes (asymmetrical structure) causes international concentration polarization (ICP) which promotes the decrease in water flux. Therefore, the number of studies related to improving both active and support layers of FO membranes is increasing in the applications. The purpose of the chapter is to bring an overview on the FO membrane manufacturing, characterizing and application area at laboratory or full scales. This chapter is published in two parts. In the first part, which appears here, the overview of membrane technologies and the definition of forward osmosis process are stated. The manufacturing methods of support and active layers forming FO membranes are described with common and\u002For new modification procedures.","signatures":"Murat Eyvaz, Serkan Arslan, Derya İmer, Ebubekir Yüksel and İsmail\nKoyuncu","isPublished":true,"isOnlineFirst":false,"isDeactivated":0,"authors":[{"id":"170083","title":"Associate Prof.","name":"Murat","surname":"Eyvaz","fullName":"Murat Eyvaz","slug":"murat-eyvaz","email":"murateyvaz@gmail.com"},{"id":"176700","title":"MSc.","name":"Serkan","surname":"Arslan","fullName":"Serkan Arslan","slug":"serkan-arslan","email":"arslan_kan@gmx.de"},{"id":"176701","title":"Prof.","name":"Ebubekir","surname":"Yüksel","fullName":"Ebubekir Yüksel","slug":"ebubekir-yuksel","email":"yuksel@gtu.edu.tr"},{"id":"209388","title":"Prof.","name":"İsmail","surname":"Koyuncu","fullName":"İsmail Koyuncu","slug":"ismail-koyuncu","email":"koyuncu@itu.edu.tr"},{"id":"210203","title":"Prof.","name":"Derya","surname":"İmer","fullName":"Derya İmer","slug":"derya-imer","email":"imerd@itu.edu.tr"}],"book":{"id":"6199","title":"Osmotically Driven Membrane Processes","slug":"osmotically-driven-membrane-processes-approach-development-and-current-status","productType":{"id":"1","title":"Edited Volume"}}},{"id":"59534","title":"Forward Osmosis Membranes – A Review: Part II","slug":"forward-osmosis-membranes-a-review-part-ii","abstract":"Forward osmosis (FO) is a technical term describing the natural phenomenon of osmosis: the transport of water molecules across a semipermeable membrane by osmotic pressure from a feed solution (FS) to a draw solution (DS). The diluted DS is then reconcentrated to recycle the draw solutes as well as to produce puriﬁed water. As the driving force is only the osmotic pressure difference between two solutions, meaning that there is no need to apply an external energy, this results in low fouling propensity of membrane and minimization of irreversible cake forming, which are the main problems controverted by membrane applications, especially in biological treatment systems (e.g., FO membrane bioreactor (FO-MBR)). The purpose of the book chapter is to bring an overview on the FO membrane manufacturing, characterizing and application area at laboratory or full scales. This book chapter is published in two parts. In the second part, which appears here, characterization of mass transport in FO membranes, fouling mechanisms and foulants on FO membranes in naturally asymmetric structure and application areas of FO membranes in the literature are mentioned. Cutting-edge technologies on FO studies are comprehensively reviewed and following major and minor titles are stated truly on the new technologies.","signatures":"Murat Eyvaz, Serkan Arslan, Derya İmer, Ebubekir Yüksel and İsmail\nKoyuncu","isPublished":true,"isOnlineFirst":false,"isDeactivated":0,"authors":[{"id":"170083","title":"Associate Prof.","name":"Murat","surname":"Eyvaz","fullName":"Murat Eyvaz","slug":"murat-eyvaz","email":"murateyvaz@gmail.com"},{"id":"176700","title":"MSc.","name":"Serkan","surname":"Arslan","fullName":"Serkan Arslan","slug":"serkan-arslan","email":"arslan_kan@gmx.de"},{"id":"176701","title":"Prof.","name":"Ebubekir","surname":"Yüksel","fullName":"Ebubekir Yüksel","slug":"ebubekir-yuksel","email":"yuksel@gtu.edu.tr"},{"id":"209388","title":"Prof.","name":"İsmail","surname":"Koyuncu","fullName":"İsmail Koyuncu","slug":"ismail-koyuncu","email":"koyuncu@itu.edu.tr"},{"id":"210203","title":"Prof.","name":"Derya","surname":"İmer","fullName":"Derya İmer","slug":"derya-imer","email":"imerd@itu.edu.tr"}],"book":{"id":"6199","title":"Osmotically Driven Membrane Processes","slug":"osmotically-driven-membrane-processes-approach-development-and-current-status","productType":{"id":"1","title":"Edited Volume"}}},{"id":"84702","title":"Introductory Chapter: Hydrogen Energy","slug":"introductory-chapter-hydrogen-energy","abstract":null,"signatures":"Ahmed Albahnasawi and Murat Eyvaz","isPublished":true,"isOnlineFirst":false,"isDeactivated":0,"authors":[{"id":"170083","title":"Associate Prof.","name":"Murat","surname":"Eyvaz","fullName":"Murat Eyvaz","slug":"murat-eyvaz","email":"murateyvaz@gmail.com"},{"id":"438009","title":"Dr.","name":"Ahmed","surname":"Albahnasawi","fullName":"Ahmed Albahnasawi","slug":"ahmed-albahnasawi","email":"albahnasawi@gtu.edu.tr"}],"book":{"id":"11934","title":"Clean Energy Technologies","slug":"clean-energy-technologies-hydrogen-and-gasification-processes","productType":{"id":"1","title":"Edited Volume"}}},{"id":"84791","title":"Introductory Chapter: Arid Environment","slug":"introductory-chapter-arid-environment","abstract":null,"signatures":"Murat Eyvaz and Ahmed Albahnasawi","isPublished":true,"isOnlineFirst":false,"isDeactivated":0,"authors":[{"id":"170083","title":"Associate Prof.","name":"Murat","surname":"Eyvaz","fullName":"Murat Eyvaz","slug":"murat-eyvaz","email":"murateyvaz@gmail.com"},{"id":"323629","title":"Dr.","name":"Ahmed","surname":"Albahnasawi","fullName":"Ahmed Albahnasawi","slug":"ahmed-albahnasawi","email":"ahmedalbahnasawi@gmail.com"}],"book":{"id":"11840","title":"Arid Environment","slug":"arid-environment-perspectives-challenges-and-management","productType":{"id":"1","title":"Edited Volume"}}},{"id":"86904","title":"Introductory Chapter: Wetlands – Characteristics, Functions, and Values","slug":"introductory-chapter-wetlands-characteristics-functions-and-values","abstract":null,"signatures":"Murat Eyvaz and Ahmed Albahnasawi","isPublished":true,"isOnlineFirst":false,"isDeactivated":0,"authors":[{"id":"170083","title":"Associate Prof.","name":"Murat","surname":"Eyvaz","fullName":"Murat Eyvaz","slug":"murat-eyvaz","email":"murateyvaz@gmail.com"},{"id":"323629","title":"Dr.","name":"Ahmed","surname":"Albahnasawi","fullName":"Ahmed Albahnasawi","slug":"ahmed-albahnasawi","email":"ahmedalbahnasawi@gmail.com"}],"book":{"id":"12180","title":"Wetlands","slug":"wetlands-new-perspectives","productType":{"id":"1","title":"Edited Volume"}}},{"id":"87312","title":"Introductory Chapter: Air Pollution – Understanding Its Causes, Effects, and Solutions","slug":"introductory-chapter-air-pollution-understanding-its-causes-effects-and-solutions","abstract":null,"signatures":"Murat Eyvaz, Ahmed Albahnasawi and Motasem Y. D. Alazaiza","isPublished":true,"isOnlineFirst":false,"isDeactivated":0,"authors":[{"id":"170083","title":"Associate Prof.","name":"Murat","surname":"Eyvaz","fullName":"Murat Eyvaz","slug":"murat-eyvaz","email":"murateyvaz@gmail.com"},{"id":"323629","title":"Dr.","name":"Ahmed","surname":"Albahnasawi","fullName":"Ahmed Albahnasawi","slug":"ahmed-albahnasawi","email":"ahmedalbahnasawi@gmail.com"},{"id":"510953","title":"Dr.","name":"Motasem Y. D.","surname":"Alazaiza","fullName":"Motasem Y. D. Alazaiza","slug":"motasem-y.-d.-alazaiza","email":"myazaiza@gmail.com"}],"book":{"id":"12221","title":"Air Pollution","slug":"air-pollution-latest-status-and-current-developments","productType":{"id":"1","title":"Edited Volume"}}},{"id":"1184350","title":"Introductory Chapter: Hydrology – Tracing the Past, Understanding the Present, Shaping the Future","slug":null,"abstract":"\n","signatures":"Ahmed Albahnasawi, Motasem Y.D. 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