npj Computational Materials

<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:prism="http://prismstandard.org/namespaces/basic/2.0/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:content="http://purl.org/rss/1.0/modules/content/" xmlns="http://purl.org/rss/1.0/" xmlns:admin="http://webns.net/mvcb/"> <channel rdf:about="http://feeds.nature.com/npjcompumats/rss/current"> <title>npj Computational Materials</title> <description>Open for Submissions Publishing high-quality research on computational approaches for designing materials. npj Computational Materials is a fully open-access journal that aims to applying computational techniques for the design of new materials, and for enhancing our understanding of existing ones. npj Computational Materials covers topics including, but not limited to, the application and development of existing and emerging theoretical and simulation approaches for the study of materials, structure and property prediction of new materials, experimental works that serve to validate, support and extend computational findings, and high-throughput techniques for large data set generation and materials data mining. In addition to original research, the journal welcomes critical Reviews, and thought-provoking Perspectives and Comment articles.</description> <link>http://feeds.nature.com/npjcompumats/rss/current</link> <admin:generatorAgent rdf:resource="https://www.nature.com/"/> <admin:errorReportsTo rdf:resource="mailto:feedback@nature.com"/> <dc:publisher>Nature Publishing Group</dc:publisher> <dc:language>en</dc:language> <dc:rights>漏 2024 Macmillan Publishers Limited, part of Springer Nature. All rights reserved.</dc:rights> <prism:publicationName>npj Computational Materials</prism:publicationName> <prism:copyright>漏 2024 Macmillan Publishers Limited, part of Springer Nature. All rights reserved.</prism:copyright> <prism:rightsAgent>permissions@nature.com</prism:rightsAgent> <image rdf:resource="https://www.nature.com/uploads/product/npjcompumats/rss.png"/> <items> <rdf:Seq> <rdf:li rdf:resource="https://www.nature.com/articles/s41524-024-01456-7"/> <rdf:li rdf:resource="https://www.nature.com/articles/s41524-024-01447-8"/> <rdf:li rdf:resource="https://www.nature.com/articles/s41524-024-01452-x"/> <rdf:li rdf:resource="https://www.nature.com/articles/s41524-024-01372-w"/> <rdf:li rdf:resource="https://www.nature.com/articles/s41524-024-01450-z"/> <rdf:li rdf:resource="https://www.nature.com/articles/s41524-024-01388-2"/> <rdf:li rdf:resource="https://www.nature.com/articles/s41524-024-01440-1"/> <rdf:li rdf:resource="https://www.nature.com/articles/s41524-024-01449-6"/> </rdf:Seq> </items> </channel> <image rdf:about="https://www.nature.com/uploads/product/npjcompumats/rss.png"> <title>npj Computational Materials</title> <url>https://www.nature.com/uploads/product/npjcompumats/rss.png</url> <link>http://feeds.nature.com/npjcompumats/rss/current</link> </image> <item rdf:about="https://www.nature.com/articles/s41524-024-01456-7"> <title><![CDATA[Neural network potential for dislocation plasticity in ceramics]]></title> <link>https://www.nature.com/articles/s41524-024-01456-7</link> <content:encoded> <![CDATA[npj Computational Materials, Published online: 22 November 2024; <a href="https://www.nature.com/articles/s41524-024-01456-7">doi:10.1038/s41524-024-01456-7</a>Neural network potential for dislocation plasticity in ceramics]]></content:encoded> <dc:title><![CDATA[Neural network potential for dislocation plasticity in ceramics]]></dc:title> <dc:creator>Shihao Zhang</dc:creator><dc:creator>Yan Li</dc:creator><dc:creator>Shuntaro Suzuki</dc:creator><dc:creator>Atsutomo Nakamura</dc:creator><dc:creator>Shigenobu Ogata</dc:creator> <dc:identifier>doi:10.1038/s41524-024-01456-7</dc:identifier> <dc:source>npj Computational Materials, Published online: 2024-11-22; | doi:10.1038/s41524-024-01456-7</dc:source> <dc:date>2024-11-22</dc:date> <prism:publicationName>npj Computational Materials</prism:publicationName> <prism:doi>10.1038/s41524-024-01456-7</prism:doi> <prism:url>https://www.nature.com/articles/s41524-024-01456-7</prism:url> </item> <item rdf:about="https://www.nature.com/articles/s41524-024-01447-8"> <title><![CDATA[Thermodynamics of solids including anharmonicity through quasiparticle theory]]></title> <link>https://www.nature.com/articles/s41524-024-01447-8</link> <content:encoded> <![CDATA[npj Computational Materials, Published online: 22 November 2024; <a href="https://www.nature.com/articles/s41524-024-01447-8">doi:10.1038/s41524-024-01447-8</a>Thermodynamics of solids including anharmonicity through quasiparticle theory]]></content:encoded> <dc:title><![CDATA[Thermodynamics of solids including anharmonicity through quasiparticle theory]]></dc:title> <dc:creator>Ernesto J. Blancas</dc:creator><dc:creator>脕lvaro Lobato</dc:creator><dc:creator>Fernando Izquierdo-Ruiz</dc:creator><dc:creator>Antonio M. M谩rquez</dc:creator><dc:creator>J. Manuel Recio</dc:creator><dc:creator>Pinku Nath</dc:creator><dc:creator>Jos茅 J. Plata</dc:creator><dc:creator>Alberto Otero-de-la-Roza</dc:creator> <dc:identifier>doi:10.1038/s41524-024-01447-8</dc:identifier> <dc:source>npj Computational Materials, Published online: 2024-11-22; | doi:10.1038/s41524-024-01447-8</dc:source> <dc:date>2024-11-22</dc:date> <prism:publicationName>npj Computational Materials</prism:publicationName> <prism:doi>10.1038/s41524-024-01447-8</prism:doi> <prism:url>https://www.nature.com/articles/s41524-024-01447-8</prism:url> </item> <item rdf:about="https://www.nature.com/articles/s41524-024-01452-x"> <title><![CDATA[Exhaustive search for novel multicomponent alloys with brute force and machine learning]]></title> <link>https://www.nature.com/articles/s41524-024-01452-x</link> <content:encoded> <![CDATA[npj Computational Materials, Published online: 22 November 2024; <a href="https://www.nature.com/articles/s41524-024-01452-x">doi:10.1038/s41524-024-01452-x</a>Exhaustive search for novel multicomponent alloys with brute force and machine learning]]></content:encoded> <dc:title><![CDATA[Exhaustive search for novel multicomponent alloys with brute force and machine learning]]></dc:title> <dc:creator>Viktoriia Zinkovich</dc:creator><dc:creator>Vadim Sotskov</dc:creator><dc:creator>Alexander Shapeev</dc:creator><dc:creator>Evgeny Podryabinkin</dc:creator> <dc:identifier>doi:10.1038/s41524-024-01452-x</dc:identifier> <dc:source>npj Computational Materials, Published online: 2024-11-22; | doi:10.1038/s41524-024-01452-x</dc:source> <dc:date>2024-11-22</dc:date> <prism:publicationName>npj Computational Materials</prism:publicationName> <prism:doi>10.1038/s41524-024-01452-x</prism:doi> <prism:url>https://www.nature.com/articles/s41524-024-01452-x</prism:url> </item> <item rdf:about="https://www.nature.com/articles/s41524-024-01372-w"> <title><![CDATA[A Ring2Vec description method enables accurate predictions of molecular properties in organic solar cells]]></title> <link>https://www.nature.com/articles/s41524-024-01372-w</link> <content:encoded> <![CDATA[npj Computational Materials, Published online: 22 November 2024; <a href="https://www.nature.com/articles/s41524-024-01372-w">doi:10.1038/s41524-024-01372-w</a>A Ring2Vec description method enables accurate predictions of molecular properties in organic solar cells]]></content:encoded> <dc:title><![CDATA[A Ring2Vec description method enables accurate predictions of molecular properties in organic solar cells]]></dc:title> <dc:creator>Ting Zhang</dc:creator><dc:creator>Kangzhong Wang</dc:creator><dc:creator>Kunlei Jing</dc:creator><dc:creator>Gang Li</dc:creator><dc:creator>Qing Li</dc:creator><dc:creator>Chen Zhang</dc:creator><dc:creator>He Yan</dc:creator> <dc:identifier>doi:10.1038/s41524-024-01372-w</dc:identifier> <dc:source>npj Computational Materials, Published online: 2024-11-22; | doi:10.1038/s41524-024-01372-w</dc:source> <dc:date>2024-11-22</dc:date> <prism:publicationName>npj Computational Materials</prism:publicationName> <prism:doi>10.1038/s41524-024-01372-w</prism:doi> <prism:url>https://www.nature.com/articles/s41524-024-01372-w</prism:url> </item> <item rdf:about="https://www.nature.com/articles/s41524-024-01450-z"> <title><![CDATA[Dielectric tensor prediction for inorganic materials using latent information from preferred potential]]></title> <link>https://www.nature.com/articles/s41524-024-01450-z</link> <content:encoded> <![CDATA[npj Computational Materials, Published online: 21 November 2024; <a href="https://www.nature.com/articles/s41524-024-01450-z">doi:10.1038/s41524-024-01450-z</a>Dielectric tensor prediction for inorganic materials using latent information from preferred potential]]></content:encoded> <dc:title><![CDATA[Dielectric tensor prediction for inorganic materials using latent information from preferred potential]]></dc:title> <dc:creator>Zetian Mao</dc:creator><dc:creator>WenWen Li</dc:creator><dc:creator>Jethro Tan</dc:creator> <dc:identifier>doi:10.1038/s41524-024-01450-z</dc:identifier> <dc:source>npj Computational Materials, Published online: 2024-11-21; | doi:10.1038/s41524-024-01450-z</dc:source> <dc:date>2024-11-21</dc:date> <prism:publicationName>npj Computational Materials</prism:publicationName> <prism:doi>10.1038/s41524-024-01450-z</prism:doi> <prism:url>https://www.nature.com/articles/s41524-024-01450-z</prism:url> </item> <item rdf:about="https://www.nature.com/articles/s41524-024-01388-2"> <title><![CDATA[Automated optimization and uncertainty quantification of convergence parameters in plane wave density functional theory calculations]]></title> <link>https://www.nature.com/articles/s41524-024-01388-2</link> <content:encoded> <![CDATA[npj Computational Materials, Published online: 19 November 2024; <a href="https://www.nature.com/articles/s41524-024-01388-2">doi:10.1038/s41524-024-01388-2</a>Automated optimization and uncertainty quantification of convergence parameters in plane wave density functional theory calculations]]></content:encoded> <dc:title><![CDATA[Automated optimization and uncertainty quantification of convergence parameters in plane wave density functional theory calculations]]></dc:title> <dc:creator>Jan Janssen</dc:creator><dc:creator>Edgar Makarov</dc:creator><dc:creator>Tilmann Hickel</dc:creator><dc:creator>Alexander V. Shapeev</dc:creator><dc:creator>J枚rg Neugebauer</dc:creator> <dc:identifier>doi:10.1038/s41524-024-01388-2</dc:identifier> <dc:source>npj Computational Materials, Published online: 2024-11-19; | doi:10.1038/s41524-024-01388-2</dc:source> <dc:date>2024-11-19</dc:date> <prism:publicationName>npj Computational Materials</prism:publicationName> <prism:doi>10.1038/s41524-024-01388-2</prism:doi> <prism:url>https://www.nature.com/articles/s41524-024-01388-2</prism:url> </item> <item rdf:about="https://www.nature.com/articles/s41524-024-01440-1"> <title><![CDATA[Understanding chiral charge-density wave by frozen chiral phonon]]></title> <link>https://www.nature.com/articles/s41524-024-01440-1</link> <content:encoded> <![CDATA[npj Computational Materials, Published online: 19 November 2024; <a href="https://www.nature.com/articles/s41524-024-01440-1">doi:10.1038/s41524-024-01440-1</a>Understanding chiral charge-density wave by frozen chiral phonon]]></content:encoded> <dc:title><![CDATA[Understanding chiral charge-density wave by frozen chiral phonon]]></dc:title> <dc:creator>Shuai Zhang</dc:creator><dc:creator>Kaifa Luo</dc:creator><dc:creator>Tiantian Zhang</dc:creator> <dc:identifier>doi:10.1038/s41524-024-01440-1</dc:identifier> <dc:source>npj Computational Materials, Published online: 2024-11-19; | doi:10.1038/s41524-024-01440-1</dc:source> <dc:date>2024-11-19</dc:date> <prism:publicationName>npj Computational Materials</prism:publicationName> <prism:doi>10.1038/s41524-024-01440-1</prism:doi> <prism:url>https://www.nature.com/articles/s41524-024-01440-1</prism:url> </item> <item rdf:about="https://www.nature.com/articles/s41524-024-01449-6"> <title><![CDATA[Large language models design sequence-defined macromolecules via evolutionary optimization]]></title> <link>https://www.nature.com/articles/s41524-024-01449-6</link> <content:encoded> <![CDATA[npj Computational Materials, Published online: 18 November 2024; <a href="https://www.nature.com/articles/s41524-024-01449-6">doi:10.1038/s41524-024-01449-6</a>Large language models design sequence-defined macromolecules via evolutionary optimization]]></content:encoded> <dc:title><![CDATA[Large language models design sequence-defined macromolecules via evolutionary optimization]]></dc:title> <dc:creator>Wesley F. Reinhart</dc:creator><dc:creator>Antonia Statt</dc:creator> <dc:identifier>doi:10.1038/s41524-024-01449-6</dc:identifier> <dc:source>npj Computational Materials, Published online: 2024-11-18; | doi:10.1038/s41524-024-01449-6</dc:source> <dc:date>2024-11-18</dc:date> <prism:publicationName>npj Computational Materials</prism:publicationName> <prism:doi>10.1038/s41524-024-01449-6</prism:doi> <prism:url>https://www.nature.com/articles/s41524-024-01449-6</prism:url> </item> </rdf:RDF>

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npj Computational Materials