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class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2409.07836">arXiv:2409.07836</a> <span> [<a href="https://arxiv.org/pdf/2409.07836">pdf</a>, <a href="https://arxiv.org/format/2409.07836">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Human-Computer Interaction">cs.HC</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1007/978-3-031-71707-9_13">10.1007/978-3-031-71707-9_13 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Measuring the limit of perception of bond stiffness of interactive molecules in VR via a gamified psychophysics experiment </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Williams%2C+R+R">Rhoslyn Roebuck Williams</a>, <a href="/search/?searchtype=author&query=Barnoud%2C+J">Jonathan Barnoud</a>, <a href="/search/?searchtype=author&query=Toledo%2C+L">Luis Toledo</a>, <a href="/search/?searchtype=author&query=Holzapfel%2C+T">Till Holzapfel</a>, <a href="/search/?searchtype=author&query=Glowacki%2C+D+R">David R. Glowacki</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2409.07836v1-abstract-short" style="display: inline;"> Molecular dynamics (MD) simulations provide crucial insight into molecular interactions and biomolecular function. With interactive MD simulations in VR (iMD-VR), chemists can now interact with these molecular simulations in real-time. Our sense of touch is essential for exploring the properties of physical objects, but recreating this sensory experience for virtual objects poses challenges. Furth… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2409.07836v1-abstract-full').style.display = 'inline'; document.getElementById('2409.07836v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2409.07836v1-abstract-full" style="display: none;"> Molecular dynamics (MD) simulations provide crucial insight into molecular interactions and biomolecular function. With interactive MD simulations in VR (iMD-VR), chemists can now interact with these molecular simulations in real-time. Our sense of touch is essential for exploring the properties of physical objects, but recreating this sensory experience for virtual objects poses challenges. Furthermore, employing haptics in the context of molecular simulation is especially difficult since \textit{we do not know what molecules actually feel like}. In this paper, we build upon previous work that demonstrated how VR-users can distinguish properties of molecules without haptic feedback. We present the results of a gamified two-alternative forced choice (2AFC) psychophysics user study in which we quantify the threshold at which iMD-VR users can differentiate the stiffness of molecular bonds. Our preliminary analysis suggests that participants can sense differences between buckminsterfullerene molecules with different bond stiffness parameters and that this limit may fall within the chemically relevant range. Our results highlight how iMD-VR may facilitate a more embodied way of exploring complex and dynamic molecular systems, enabling chemists to sense the properties of molecules purely by interacting with them in VR. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2409.07836v1-abstract-full').style.display = 'none'; document.getElementById('2409.07836v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 12 September, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> September 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">9 pages, 2 figures, and was published in the proceedings of the International Conference on eXtended Reality 2024 (XR SALENTO 2024)</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2409.07189">arXiv:2409.07189</a> <span> [<a href="https://arxiv.org/pdf/2409.07189">pdf</a>, <a href="https://arxiv.org/format/2409.07189">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Artificial Intelligence">cs.AI</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Human-Computer Interaction">cs.HC</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Biomolecules">q-bio.BM</span> </div> </div> <p class="title is-5 mathjax"> A Perspective on AI-Guided Molecular Simulations in VR: Exploring Strategies for Imitation Learning in Hyperdimensional Molecular Systems </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Dhouioui%2C+M">Mohamed Dhouioui</a>, <a href="/search/?searchtype=author&query=Barnoud%2C+J">Jonathan Barnoud</a>, <a href="/search/?searchtype=author&query=Williams%2C+R+R">Rhoslyn Roebuck Williams</a>, <a href="/search/?searchtype=author&query=Stroud%2C+H+J">Harry J. Stroud</a>, <a href="/search/?searchtype=author&query=Bates%2C+P">Phil Bates</a>, <a href="/search/?searchtype=author&query=Glowacki%2C+D+R">David R. Glowacki</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2409.07189v1-abstract-short" style="display: inline;"> Molecular dynamics simulations are a crucial computational tool for researchers to understand and engineer molecular structure and function in areas such as drug discovery, protein engineering, and material design. Despite their utility, MD simulations are expensive, owing to the high dimensionality of molecular systems. Interactive molecular dynamics in virtual reality (iMD-VR) has recently been… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2409.07189v1-abstract-full').style.display = 'inline'; document.getElementById('2409.07189v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2409.07189v1-abstract-full" style="display: none;"> Molecular dynamics simulations are a crucial computational tool for researchers to understand and engineer molecular structure and function in areas such as drug discovery, protein engineering, and material design. Despite their utility, MD simulations are expensive, owing to the high dimensionality of molecular systems. Interactive molecular dynamics in virtual reality (iMD-VR) has recently been developed as a 'human-in-the-loop' strategy, which leverages high-performance computing to accelerate the researcher's ability to solve the hyperdimensional sampling problem. By providing an immersive 3D environment that enables visualization and manipulation of real-time molecular motion, iMD-VR enables researchers and students to efficiently and intuitively explore and navigate these complex, high-dimensional systems. iMD-VR platforms offer a unique opportunity to quickly generate rich datasets that capture human experts' spatial insight regarding molecular structure and function. This paper explores the possibility of employing user-generated iMD-VR datasets to train AI agents via imitation learning (IL). IL is an important technique in robotics that enables agents to mimic complex behaviors from expert demonstrations, thus circumventing the need for explicit programming or intricate reward design. We review the utilization of IL for manipulation tasks in robotics and discuss how iMD-VR recordings could be used to train IL models for solving specific molecular 'tasks'. We then investigate how such approaches could be applied to the data captured from iMD-VR recordings. Finally, we outline the future research directions and potential challenges of using AI agents to augment human expertise to efficiently navigate conformational spaces, highlighting how this approach could provide valuable insight across domains such as materials science, protein engineering, and computer-aided drug design. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2409.07189v1-abstract-full').style.display = 'none'; document.getElementById('2409.07189v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 11 September, 2024; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> September 2024. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">(Accepted for presentation at the First Workshop on "eXtended Reality \& Intelligent Agents" (XRIA24) @ ECAI24, Santiago De Compostela (Spain), 20 October 2024)</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2311.17925">arXiv:2311.17925</a> <span> [<a href="https://arxiv.org/pdf/2311.17925">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Chemical Physics">physics.chem-ph</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Biological Physics">physics.bio-ph</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1038/s41598-023-43523-x">10.1038/s41598-023-43523-x <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Free energy along drug-protein binding pathways interactively sampled in virtual reality </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Deeks%2C+H+M">Helen M. Deeks</a>, <a href="/search/?searchtype=author&query=Zinovjev%2C+K">Kirill Zinovjev</a>, <a href="/search/?searchtype=author&query=Barnoud%2C+J">Jonathan Barnoud</a>, <a href="/search/?searchtype=author&query=Mulholland%2C+A+J">Adrian J. Mulholland</a>, <a href="/search/?searchtype=author&query=van+der+Kamp%2C+M+W">Marc W. van der Kamp</a>, <a href="/search/?searchtype=author&query=Glowacki%2C+D+R">David R. Glowacki</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2311.17925v1-abstract-short" style="display: inline;"> We describe a two-step approach for combining interactive molecular dynamics in virtual reality (iMD-VR) with free energy (FE) calculation to explore the dynamics of biological processes at the molecular level. We refer to this combined approach as iMD-VR-FE. Stage one involves using a state-of-the-art iMD-VR framework to generate a diverse range of protein-ligand unbinding pathways, benefitting f… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2311.17925v1-abstract-full').style.display = 'inline'; document.getElementById('2311.17925v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2311.17925v1-abstract-full" style="display: none;"> We describe a two-step approach for combining interactive molecular dynamics in virtual reality (iMD-VR) with free energy (FE) calculation to explore the dynamics of biological processes at the molecular level. We refer to this combined approach as iMD-VR-FE. Stage one involves using a state-of-the-art iMD-VR framework to generate a diverse range of protein-ligand unbinding pathways, benefitting from the sophistication of human spatial and chemical intuition. Stage two involves using the iMD-VR-sampled pathways as initial guesses for defining a path-based reaction coordinate from which we can obtain a corresponding free energy profile using FE methods. To investigate the performance of the method, we apply iMD-VR-FE to investigate the unbinding of a benzamidine ligand from a trypsin protein. The binding free energy calculated using iMD-VR-FE is similar for each pathway, indicating internal consistency. Moreover, the resulting free energy profiles can distinguish energetic differences between pathways corresponding to various protein-ligand conformations (e.g., helping to identify pathways that are more favourable) and enable identification of metastable states along the pathways. The two-step iMD-VR-FE approach offers an intuitive way for researchers to test hypotheses for candidate pathways in biomolecular systems, quickly obtaining both qualitative and quantitative insight. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2311.17925v1-abstract-full').style.display = 'none'; document.getElementById('2311.17925v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 21 November, 2023; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2023. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> Nat Sci Rep 13, 16665 (2023) </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2202.03953">arXiv:2202.03953</a> <span> [<a href="https://arxiv.org/pdf/2202.03953">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Biomolecules">q-bio.BM</span> </div> </div> <p class="title is-5 mathjax"> Interactivity: the missing link between virtual reality technology and drug discovery pipelines </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Walters%2C+R+K">Rebecca K. Walters</a>, <a href="/search/?searchtype=author&query=Gale%2C+E+M">Ella M. Gale</a>, <a href="/search/?searchtype=author&query=Barnoud%2C+J">Jonathan Barnoud</a>, <a href="/search/?searchtype=author&query=Glowacki%2C+D+R">David R. Glowacki</a>, <a href="/search/?searchtype=author&query=Mulholland%2C+A+J">Adrian J. Mulholland</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2202.03953v1-abstract-short" style="display: inline;"> The potential of virtual reality (VR) to contribute to drug design and development has been recognised for many years. Hardware and software developments now mean that this potential is beginning to be realised, and VR methods are being actively used in this sphere. A recent advance is to use VR not only to visualise and interact with molecular structures, but also to interact with molecular dynam… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2202.03953v1-abstract-full').style.display = 'inline'; document.getElementById('2202.03953v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2202.03953v1-abstract-full" style="display: none;"> The potential of virtual reality (VR) to contribute to drug design and development has been recognised for many years. Hardware and software developments now mean that this potential is beginning to be realised, and VR methods are being actively used in this sphere. A recent advance is to use VR not only to visualise and interact with molecular structures, but also to interact with molecular dynamics simulations of 'on the fly' (interactive molecular dynamics in VR, IMD-VR), which is useful not only for flexible docking but also to examine binding processes and conformational changes. iMD-VR has been shown to be useful for creating complexes of ligands bound to target proteins, e.g., recently applied to peptide inhibitors of the SARS-CoV-2 main protease. In this review, we use the term 'interactive VR' to refer to software where interactivity is an inherent part of the user VR experience e.g., in making structural modifications or interacting with a physically rigorous molecular dynamics (MD) simulation, as opposed to simply using VR controllers to rotate and translate the molecule for enhanced visualisation. Here, we describe these methods and their application to problems relevant to drug discovery, highlighting the possibilities that they offer in this arena. We suggest that the ease of viewing and manipulating molecular structures and dynamics, and the ability to modify structures on the fly (e.g., adding or deleting atoms) makes modern interactive VR a valuable tool to add to the armoury of drug development methods. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2202.03953v1-abstract-full').style.display = 'none'; document.getElementById('2202.03953v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 8 February, 2022; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> February 2022. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">19 pages, 3 figures</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2105.07796">arXiv:2105.07796</a> <span> [<a href="https://arxiv.org/pdf/2105.07796">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Human-Computer Interaction">cs.HC</span> </div> </div> <p class="title is-5 mathjax"> Dissolving yourself in connection to others: shared experiences of ego attenuation and connectedness during group VR experiences can be comparable to psychedelics </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Glowacki%2C+D+R">David R. Glowacki</a>, <a href="/search/?searchtype=author&query=Williams%2C+R+R">Rhoslyn Roebuck Williams</a>, <a href="/search/?searchtype=author&query=Maynard%2C+O+M">Olivia M. Maynard</a>, <a href="/search/?searchtype=author&query=Pike%2C+J+E">James E. Pike</a>, <a href="/search/?searchtype=author&query=Freire%2C+R">Rachel Freire</a>, <a href="/search/?searchtype=author&query=Wonnacott%2C+M+D">Mark D. Wonnacott</a>, <a href="/search/?searchtype=author&query=Chatziapostolou%2C+M">Mike Chatziapostolou</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2105.07796v1-abstract-short" style="display: inline;"> With a growing body of research highlighting the therapeutic potential of experiential phenomenology which diminishes egoic identity and increases one's sense of connectedness, there is significant interest in how to elicit such 'self-transcendent experiences' (STEs) in laboratory contexts. Psychedelic drugs (YDs) have proven particularly effective in this respect, producing subjective phenomenolo… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2105.07796v1-abstract-full').style.display = 'inline'; document.getElementById('2105.07796v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2105.07796v1-abstract-full" style="display: none;"> With a growing body of research highlighting the therapeutic potential of experiential phenomenology which diminishes egoic identity and increases one's sense of connectedness, there is significant interest in how to elicit such 'self-transcendent experiences' (STEs) in laboratory contexts. Psychedelic drugs (YDs) have proven particularly effective in this respect, producing subjective phenomenology which reliably elicits intense STEs. With virtual reality (VR) emerging as a powerful tool for constructing new perceptual environments, we describe a VR framework called 'Isness-distributed' (Isness-D) which harnesses the unique affordances of distributed multi-person VR to blur conventional self-other boundaries. Within Isness-D, groups of participants co-habit a shared virtual space, collectively experiencing their bodies as luminous energetic essences with diffuse spatial boundaries. It enables moments of 'energetic coalescence', a new class of embodied phenomenological intersubjective experience where bodies can fluidly merge, enabling participants to have an experience of including multiple others within their self-representation. To evaluate Isness-D, we adopted a citizen science approach, coordinating an international network of Isness-D 'nodes'. We analyzed the results (N = 58) using 4 different self-report scales previously applied to analyze subjective YD phenomenology (the inclusion of community in self scale, ego-dissolution inventory, communitas scale, and the MEQ30 mystical experience questionnaire). Despite the complexities associated with a distributed experiment like this, the Isness-D scores on all 4 scales were statistically indistinguishable from recently published YD studies, demonstrating that distributed VR can be used to design intersubjective STEs where people dissolve their sense of self in the connection to others. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2105.07796v1-abstract-full').style.display = 'none'; document.getElementById('2105.07796v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 17 May, 2021; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> May 2021. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2105.03078">arXiv:2105.03078</a> <span> [<a href="https://arxiv.org/pdf/2105.03078">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Chemical Physics">physics.chem-ph</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Computational Physics">physics.comp-ph</span> </div> </div> <p class="title is-5 mathjax"> AutoMeKin2021: An open-source program for automated reaction discovery </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Mart%C3%ADnez-N%C3%BA%C3%B1ez%2C+E">Emilio Mart铆nez-N煤帽ez</a>, <a href="/search/?searchtype=author&query=Barnes%2C+G+L">George L. Barnes</a>, <a href="/search/?searchtype=author&query=Glowacki%2C+D+R">David R. Glowacki</a>, <a href="/search/?searchtype=author&query=Kopec%2C+S">Sabine Kopec</a>, <a href="/search/?searchtype=author&query=Pel%C3%A1ez%2C+D">Daniel Pel谩ez</a>, <a href="/search/?searchtype=author&query=Rodr%C3%ADguez%2C+A">Aurelio Rodr铆guez</a>, <a href="/search/?searchtype=author&query=Rodr%C3%ADguez-Fern%C3%A1ndez%2C+R">Roberto Rodr铆guez-Fern谩ndez</a>, <a href="/search/?searchtype=author&query=Shannon%2C+R+J">Robin J. Shannon</a>, <a href="/search/?searchtype=author&query=Stewart%2C+J+J+P">James J. P. Stewart</a>, <a href="/search/?searchtype=author&query=Tahoces%2C+P+G">Pablo G. Tahoces</a>, <a href="/search/?searchtype=author&query=Vazquez%2C+S+A">Saulo A. Vazquez</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2105.03078v1-abstract-short" style="display: inline;"> AutoMeKin2021 is an updated version of tsscds2018, a program for the automated discovery of reaction mechanisms (J. Comput. Chem. 2018, 39, 1922-1930). This release features a number of new capabilities: rare-event molecular dynamics simulations to enhance reaction discovery, extension of the original search algorithm to study van der Waals complexes, use of chemical knowledge, a new search algori… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2105.03078v1-abstract-full').style.display = 'inline'; document.getElementById('2105.03078v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2105.03078v1-abstract-full" style="display: none;"> AutoMeKin2021 is an updated version of tsscds2018, a program for the automated discovery of reaction mechanisms (J. Comput. Chem. 2018, 39, 1922-1930). This release features a number of new capabilities: rare-event molecular dynamics simulations to enhance reaction discovery, extension of the original search algorithm to study van der Waals complexes, use of chemical knowledge, a new search algorithm based on bond-order time series analysis, statistics of the chemical reaction networks, a web application to submit jobs, and other features. The source code, manual, installation instructions and the website link are available at: https://rxnkin.usc.es/index.php/AutoMeKin <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2105.03078v1-abstract-full').style.display = 'none'; document.getElementById('2105.03078v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 7 May, 2021; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> May 2021. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">25 pages, 9 figures and 2 tables</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2104.02389">arXiv:2104.02389</a> <span> [<a href="https://arxiv.org/pdf/2104.02389">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Chemical Physics">physics.chem-ph</span> </div> </div> <p class="title is-5 mathjax"> ChemDyME: Kinetically Steered, Automated Mechanism Generation Through Combined Molecular Dynamics and Master Equation Calculations </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Shannon%2C+R+J">Robin J. Shannon</a>, <a href="/search/?searchtype=author&query=Nunez%2C+E+M">Emilio Martinez Nunez</a>, <a href="/search/?searchtype=author&query=Shalashilin%2C+D+V">Dmitrii V. Shalashilin</a>, <a href="/search/?searchtype=author&query=Glowacki%2C+D+R">David R. Glowacki</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2104.02389v1-abstract-short" style="display: inline;"> In many scientific fields, there is an interest in understanding the way in which complex chemical networks evolve. The chemical networks which researchers focus upon, have become increasingly complex and this has motivated the development of automated methods for exploring chemical reactivity or conformational change in a black box manner, harnessing modern computing resources to automate mechani… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2104.02389v1-abstract-full').style.display = 'inline'; document.getElementById('2104.02389v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2104.02389v1-abstract-full" style="display: none;"> In many scientific fields, there is an interest in understanding the way in which complex chemical networks evolve. The chemical networks which researchers focus upon, have become increasingly complex and this has motivated the development of automated methods for exploring chemical reactivity or conformational change in a black box manner, harnessing modern computing resources to automate mechanism discovery. In this work we present a new approach to automated mechanism generation implemented which couples molecular dynamics and statistical rate theory to automatically find kinetically important reactions and then solve the time evolution of the species in the evolving network. Key to this ChemDyME approach is the novel concept of kinetic convergence whereby the search for new reactions is constrained to those species which are kinetically favorable at the conditions of interest. We demonstrate the capability of the new approach for two systems, a well-studied combustion system, and a multiple oxygen addition system relevant to atmospheric aerosol formation. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2104.02389v1-abstract-full').style.display = 'none'; document.getElementById('2104.02389v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 6 April, 2021; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> April 2021. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2101.10796">arXiv:2101.10796</a> <span> [<a href="https://arxiv.org/pdf/2101.10796">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Chemical Physics">physics.chem-ph</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1021/acs.jpca.1c01260">10.1021/acs.jpca.1c01260 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Nonadiabatic kinetics in the intermediate coupling regime: comparing molecular dynamics to an energy grained master equation </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Shchepanovska%2C+D">Darya Shchepanovska</a>, <a href="/search/?searchtype=author&query=Shannon%2C+R+J">Robin J. Shannon</a>, <a href="/search/?searchtype=author&query=Curchod%2C+B+F+E">Basile F. E. Curchod</a>, <a href="/search/?searchtype=author&query=Glowacki%2C+D+R">David R. Glowacki</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2101.10796v1-abstract-short" style="display: inline;"> Here we outline and test an extension of the energy grained master equation (EGME) for treating nonadiabatic (NA) hopping between different potential energy surfaces, which enables us to model the competition between stepwise collisional relaxation and kinetic processes which transfer population between different potential energy surfaces of the same spin symmetry. By incorporating Zhu-Nakamura th… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2101.10796v1-abstract-full').style.display = 'inline'; document.getElementById('2101.10796v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2101.10796v1-abstract-full" style="display: none;"> Here we outline and test an extension of the energy grained master equation (EGME) for treating nonadiabatic (NA) hopping between different potential energy surfaces, which enables us to model the competition between stepwise collisional relaxation and kinetic processes which transfer population between different potential energy surfaces of the same spin symmetry. By incorporating Zhu-Nakamura theory into the EGME, we are able to treat nonadiabatic passages beyond the simple Landau-Zener approximation, along with corresponding treatments of zero-point energy and tunnelling probability. To evaluate this NA-EGME approach, we carried out detailed studies of the UV photodynamics of the volatile organic compound C6-hydroperoxyaldehyde (C6-HPALD) using on-the-fly ab initio molecular dynamics and trajectory surface hopping. For this multi-chromophore molecule, we show that the EGME is able to quantitatively capture important aspects of the dynamics, including kinetic timescales, and diabatic trapping. Such an approach provides a promising and efficient strategy for treating the long-time dynamics of photo-excited molecules in regimes which are difficult to capture using atomistic on-the-fly molecular dynamics. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2101.10796v1-abstract-full').style.display = 'none'; document.getElementById('2101.10796v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 26 January, 2021; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> January 2021. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2008.05994">arXiv:2008.05994</a> <span> [<a href="https://arxiv.org/pdf/2008.05994">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Computational Physics">physics.comp-ph</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Machine Learning">cs.LG</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1371/journal.pone.0253612">10.1371/journal.pone.0253612 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> A community-powered search of machine learning strategy space to find NMR property prediction models </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Bratholm%2C+L+A">Lars A. Bratholm</a>, <a href="/search/?searchtype=author&query=Gerrard%2C+W">Will Gerrard</a>, <a href="/search/?searchtype=author&query=Anderson%2C+B">Brandon Anderson</a>, <a href="/search/?searchtype=author&query=Bai%2C+S">Shaojie Bai</a>, <a href="/search/?searchtype=author&query=Choi%2C+S">Sunghwan Choi</a>, <a href="/search/?searchtype=author&query=Dang%2C+L">Lam Dang</a>, <a href="/search/?searchtype=author&query=Hanchar%2C+P">Pavel Hanchar</a>, <a href="/search/?searchtype=author&query=Howard%2C+A">Addison Howard</a>, <a href="/search/?searchtype=author&query=Huard%2C+G">Guillaume Huard</a>, <a href="/search/?searchtype=author&query=Kim%2C+S">Sanghoon Kim</a>, <a href="/search/?searchtype=author&query=Kolter%2C+Z">Zico Kolter</a>, <a href="/search/?searchtype=author&query=Kondor%2C+R">Risi Kondor</a>, <a href="/search/?searchtype=author&query=Kornbluth%2C+M">Mordechai Kornbluth</a>, <a href="/search/?searchtype=author&query=Lee%2C+Y">Youhan Lee</a>, <a href="/search/?searchtype=author&query=Lee%2C+Y">Youngsoo Lee</a>, <a href="/search/?searchtype=author&query=Mailoa%2C+J+P">Jonathan P. Mailoa</a>, <a href="/search/?searchtype=author&query=Nguyen%2C+T+T">Thanh Tu Nguyen</a>, <a href="/search/?searchtype=author&query=Popovic%2C+M">Milos Popovic</a>, <a href="/search/?searchtype=author&query=Rakocevic%2C+G">Goran Rakocevic</a>, <a href="/search/?searchtype=author&query=Reade%2C+W">Walter Reade</a>, <a href="/search/?searchtype=author&query=Song%2C+W">Wonho Song</a>, <a href="/search/?searchtype=author&query=Stojanovic%2C+L">Luka Stojanovic</a>, <a href="/search/?searchtype=author&query=Thiede%2C+E+H">Erik H. Thiede</a>, <a href="/search/?searchtype=author&query=Tijanic%2C+N">Nebojsa Tijanic</a>, <a href="/search/?searchtype=author&query=Torrubia%2C+A">Andres Torrubia</a> , et al. (4 additional authors not shown) </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2008.05994v1-abstract-short" style="display: inline;"> The rise of machine learning (ML) has created an explosion in the potential strategies for using data to make scientific predictions. For physical scientists wishing to apply ML strategies to a particular domain, it can be difficult to assess in advance what strategy to adopt within a vast space of possibilities. Here we outline the results of an online community-powered effort to swarm search the… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2008.05994v1-abstract-full').style.display = 'inline'; document.getElementById('2008.05994v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2008.05994v1-abstract-full" style="display: none;"> The rise of machine learning (ML) has created an explosion in the potential strategies for using data to make scientific predictions. For physical scientists wishing to apply ML strategies to a particular domain, it can be difficult to assess in advance what strategy to adopt within a vast space of possibilities. Here we outline the results of an online community-powered effort to swarm search the space of ML strategies and develop algorithms for predicting atomic-pairwise nuclear magnetic resonance (NMR) properties in molecules. Using an open-source dataset, we worked with Kaggle to design and host a 3-month competition which received 47,800 ML model predictions from 2,700 teams in 84 countries. Within 3 weeks, the Kaggle community produced models with comparable accuracy to our best previously published "in-house" efforts. A meta-ensemble model constructed as a linear combination of the top predictions has a prediction accuracy which exceeds that of any individual model, 7-19x better than our previous state-of-the-art. The results highlight the potential of transformer architectures for predicting quantum mechanical (QM) molecular properties. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2008.05994v1-abstract-full').style.display = 'none'; document.getElementById('2008.05994v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 13 August, 2020; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> August 2020. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2007.02824">arXiv:2007.02824</a> <span> [<a href="https://arxiv.org/pdf/2007.02824">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Chemical Physics">physics.chem-ph</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1063/5.0015950">10.1063/5.0015950 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Training atomic neural networks using fragment-based data generated in virtual reality </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Amabilino%2C+S">Silvia Amabilino</a>, <a href="/search/?searchtype=author&query=Bratholm%2C+L+A">Lars A. Bratholm</a>, <a href="/search/?searchtype=author&query=Bennie%2C+S+J">Simon J. Bennie</a>, <a href="/search/?searchtype=author&query=O%27Connor%2C+M+B">Michael B. O'Connor</a>, <a href="/search/?searchtype=author&query=Glowacki%2C+D+R">David R. Glowacki</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2007.02824v1-abstract-short" style="display: inline;"> The ability to understand and engineer molecular structures relies on having accurate descriptions of the energy as a function of atomic coordinates. Here we outline a new paradigm for deriving energy functions of hyperdimensional molecular systems, which involves generating data for low-dimensional systems in virtual reality (VR) to then efficiently train atomic neural networks (ANNs). This gener… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2007.02824v1-abstract-full').style.display = 'inline'; document.getElementById('2007.02824v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2007.02824v1-abstract-full" style="display: none;"> The ability to understand and engineer molecular structures relies on having accurate descriptions of the energy as a function of atomic coordinates. Here we outline a new paradigm for deriving energy functions of hyperdimensional molecular systems, which involves generating data for low-dimensional systems in virtual reality (VR) to then efficiently train atomic neural networks (ANNs). This generates high quality data for specific areas of interest within the hyperdimensional space that characterizes a molecule's potential energy surface (PES). We demonstrate the utility of this approach by gathering data within VR to train ANNs on chemical reactions involving fewer than 8 heavy atoms. This strategy enables us to predict the energies of much higher-dimensional systems, e.g. containing nearly 100 atoms. Training on datasets containing only 15K geometries, this approach generates mean absolute errors around 2 kcal/mol. This represents one of the first times that an ANN-PES for a large reactive radical has been generated using such a small dataset. Our results suggest VR enables the intelligent curation of high-quality data, which accelerates the learning process. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2007.02824v1-abstract-full').style.display = 'none'; document.getElementById('2007.02824v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 30 May, 2020; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> July 2020. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2005.03503">arXiv:2005.03503</a> <span> [<a href="https://arxiv.org/pdf/2005.03503">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Human-Computer Interaction">cs.HC</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1145/3334480.3383026">10.1145/3334480.3383026 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Subtle Sensing: Detecting Differences in the Flexibility of Virtually Simulated Molecular Objects </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Williams%2C+R+R">Rhoslyn Roebuck Williams</a>, <a href="/search/?searchtype=author&query=Varcoe%2C+X">Xan Varcoe</a>, <a href="/search/?searchtype=author&query=Glowacki%2C+B+R">Becca R. Glowacki</a>, <a href="/search/?searchtype=author&query=Gale%2C+E+M">Ella M. Gale</a>, <a href="/search/?searchtype=author&query=Jamieson-Binnie%2C+A">Alexander Jamieson-Binnie</a>, <a href="/search/?searchtype=author&query=Glowacki%2C+D+R">David R. Glowacki</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2005.03503v1-abstract-short" style="display: inline;"> During VR demos we have performed over last few years, many participants (in the absence of any haptic feedback) have commented on their perceived ability to 'feel' differences between simulated molecular objects. The mechanisms for such 'feeling' are not entirely clear: observing from outside VR, one can see that there is nothing physical for participants to 'feel'. Here we outline exploratory us… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2005.03503v1-abstract-full').style.display = 'inline'; document.getElementById('2005.03503v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2005.03503v1-abstract-full" style="display: none;"> During VR demos we have performed over last few years, many participants (in the absence of any haptic feedback) have commented on their perceived ability to 'feel' differences between simulated molecular objects. The mechanisms for such 'feeling' are not entirely clear: observing from outside VR, one can see that there is nothing physical for participants to 'feel'. Here we outline exploratory user studies designed to evaluate the extent to which participants can distinguish quantitative differences in the flexibility of VR-simulated molecular objects. The results suggest that an individual's capacity to detect differences in molecular flexibility is enhanced when they can interact with and manipulate the molecules, as opposed to merely observing the same interaction. Building on these results, we intend to carry out further studies investigating humans' ability to sense quantitative properties of VR simulations without haptic technology. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2005.03503v1-abstract-full').style.display = 'none'; document.getElementById('2005.03503v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 7 May, 2020; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> May 2020. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> CHI '20: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/2002.00940">arXiv:2002.00940</a> <span> [<a href="https://arxiv.org/pdf/2002.00940">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Human-Computer Interaction">cs.HC</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1145/3313831.3376649">10.1145/3313831.3376649 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Isness: Using Multi-Person VR to Design Peak Mystical-Type Experiences Comparable to Psychedelics </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Glowacki%2C+D+R">David R. Glowacki</a>, <a href="/search/?searchtype=author&query=Wonnacott%2C+M+D">Mark D. Wonnacott</a>, <a href="/search/?searchtype=author&query=Freire%2C+R">Rachel Freire</a>, <a href="/search/?searchtype=author&query=Glowacki%2C+B+R">Becca R. Glowacki</a>, <a href="/search/?searchtype=author&query=Gale%2C+E+M">Ella M. Gale</a>, <a href="/search/?searchtype=author&query=Pike%2C+J+E">James E. Pike</a>, <a href="/search/?searchtype=author&query=de+Haan%2C+T">Tiu de Haan</a>, <a href="/search/?searchtype=author&query=Chatziapostolou%2C+M">Mike Chatziapostolou</a>, <a href="/search/?searchtype=author&query=Metatla%2C+O">Oussama Metatla</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="2002.00940v2-abstract-short" style="display: inline;"> Studies combining psychotherapy with psychedelic drugs (PsiDs) have demonstrated positive outcomes that are often associated with PsiDs' ability to induce 'mystical-type' experiences (MTEs) - i.e., subjective experiences whose characteristics include a sense of connectedness, transcendence, and ineffability. We suggest that both PsiDs and virtual reality can be situated on a broader spectrum of ps… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2002.00940v2-abstract-full').style.display = 'inline'; document.getElementById('2002.00940v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="2002.00940v2-abstract-full" style="display: none;"> Studies combining psychotherapy with psychedelic drugs (PsiDs) have demonstrated positive outcomes that are often associated with PsiDs' ability to induce 'mystical-type' experiences (MTEs) - i.e., subjective experiences whose characteristics include a sense of connectedness, transcendence, and ineffability. We suggest that both PsiDs and virtual reality can be situated on a broader spectrum of psychedelic technologies. To test this hypothesis, we used concepts, methods, and analysis strategies from PsiD research to design and evaluate 'Isness', a multi-person VR journey where participants experience the collective emergence, fluctuation, and dissipation of their bodies as energetic essences. A study (N=57) analyzing participant responses to a commonly used PsiD experience questionnaire (MEQ30) indicates that Isness participants had MTEs comparable to those reported in double-blind clinical studies after high doses of psilocybin & LSD. Within a supportive setting and conceptual framework, VR phenomenology can create the conditions for MTEs from which participants derive insight and meaning. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('2002.00940v2-abstract-full').style.display = 'none'; document.getElementById('2002.00940v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 5 May, 2020; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 3 February, 2020; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> February 2020. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> CHI 2020: Proceedings of the 2020 CHI Conference on Human Factors in Computing Systems </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1910.01349">arXiv:1910.01349</a> <span> [<a href="https://arxiv.org/pdf/1910.01349">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Chemical Physics">physics.chem-ph</span> </div> </div> <p class="title is-5 mathjax"> Enhancing automated reaction discovery with boxed molecular dynamics in energy space </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Jara-Toro%2C+R+A">Rafael A. Jara-Toro</a>, <a href="/search/?searchtype=author&query=Pino%2C+G+A">Gustavo A. Pino</a>, <a href="/search/?searchtype=author&query=Glowacki%2C+D+R">David R. Glowacki</a>, <a href="/search/?searchtype=author&query=Shannon%2C+R+J">Robin J. Shannon</a>, <a href="/search/?searchtype=author&query=Martinez-Nunez%2C+E">Emilio Martinez-Nunez</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="1910.01349v2-abstract-short" style="display: inline;"> The rare event acceleration method BXDE is interfaced in the present work with the automated reaction discovery method AutoMeKin. To test the efficiency of the combined AutoMeKin-BXDE procedure, the ozonolysis of a-pinene is studied in comparison with standard AutoMeKin. AutoMeKin-BXDE locates intermediates and transition states that are more densely connected with each other and approximately 50… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1910.01349v2-abstract-full').style.display = 'inline'; document.getElementById('1910.01349v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1910.01349v2-abstract-full" style="display: none;"> The rare event acceleration method BXDE is interfaced in the present work with the automated reaction discovery method AutoMeKin. To test the efficiency of the combined AutoMeKin-BXDE procedure, the ozonolysis of a-pinene is studied in comparison with standard AutoMeKin. AutoMeKin-BXDE locates intermediates and transition states that are more densely connected with each other and approximately 50 kcal/mol more stable than those found with standard AutoMeKin. Other than the different density of edges between the nodes, both networks are scale-free and display small-world properties, mimicking the network of organic chemistry. Finally, while AutoMeKin-BXDE finds more transition states than those previously reported for O3 + a-pinene, the standard procedure fails to locate some of the previously published reaction pathways using the same simulation time of 2.5 ns. In summary, the mixed procedure is very promising and clearly outperforms the standard simulation algorithms implemented in AutoMeKin. BXDE will be available in the next release of AutoMekin. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1910.01349v2-abstract-full').style.display = 'none'; document.getElementById('1910.01349v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 4 October, 2019; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 3 October, 2019; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> October 2019. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">10 pages, 4 figures, 2 schemes</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1908.08501">arXiv:1908.08501</a> <span> [<a href="https://arxiv.org/pdf/1908.08501">pdf</a>, <a href="https://arxiv.org/format/1908.08501">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Chemical Physics">physics.chem-ph</span> </div> </div> <p class="title is-5 mathjax"> IMPRESSION -- Prediction of NMR Parameters for 3-dimensional chemical structures using Machine Learning with near quantum chemical accuracy </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Gerrard%2C+W">Will Gerrard</a>, <a href="/search/?searchtype=author&query=Bratholm%2C+L+A">Lars Andersen Bratholm</a>, <a href="/search/?searchtype=author&query=Packer%2C+M">Martin Packer</a>, <a href="/search/?searchtype=author&query=Mulholland%2C+A+J">Adrian J. Mulholland</a>, <a href="/search/?searchtype=author&query=Glowacki%2C+D+R">David R. Glowacki</a>, <a href="/search/?searchtype=author&query=Butts%2C+C+P">Craig P. Butts</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="1908.08501v2-abstract-short" style="display: inline;"> The IMPRESSION (Intelligent Machine PREdiction of Shift and Scalar Information Of Nuclei) machine learning system provides an efficient and accurate route to the prediction of NMR parameters from 3-dimensional chemical structures. Here we demonstrate that machine learning predictions, trained on quantum chemical computed values for NMR parameters, are essentially as accurate but computationally mu… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1908.08501v2-abstract-full').style.display = 'inline'; document.getElementById('1908.08501v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1908.08501v2-abstract-full" style="display: none;"> The IMPRESSION (Intelligent Machine PREdiction of Shift and Scalar Information Of Nuclei) machine learning system provides an efficient and accurate route to the prediction of NMR parameters from 3-dimensional chemical structures. Here we demonstrate that machine learning predictions, trained on quantum chemical computed values for NMR parameters, are essentially as accurate but computationally much more efficient (tens of milliseconds per molecule) than quantum chemical calculations (hours/days per molecule). Training the machine learning systems on quantum chemical, rather than experimental, data circumvents the need for existence of large, structurally diverse, error-free experimental databases and makes IMPRESSION applicable to solving 3-dimensional problems such as molecular conformation and isomerism <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1908.08501v2-abstract-full').style.display = 'none'; document.getElementById('1908.08501v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 29 October, 2019; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 22 August, 2019; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> August 2019. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1908.07395">arXiv:1908.07395</a> <span> [<a href="https://arxiv.org/pdf/1908.07395">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Biological Physics">physics.bio-ph</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Computational Physics">physics.comp-ph</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Biomolecules">q-bio.BM</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1371/journal.pone.0228461">10.1371/journal.pone.0228461 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Interactive molecular dynamics in virtual reality for accurate flexible protein-ligand docking </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Deeks%2C+H+M">Helen M. Deeks</a>, <a href="/search/?searchtype=author&query=Walters%2C+R+K">Rebecca K. Walters</a>, <a href="/search/?searchtype=author&query=Hare%2C+S+R">Stephanie R. Hare</a>, <a href="/search/?searchtype=author&query=O%27Connor%2C+M+B">Michael B. O'Connor</a>, <a href="/search/?searchtype=author&query=Mulholland%2C+A+J">Adrian J. Mulholland</a>, <a href="/search/?searchtype=author&query=Glowacki%2C+D+R">David R. Glowacki</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="1908.07395v2-abstract-short" style="display: inline;"> Simulating drug binding and unbinding is a challenge, as the rugged energy landscapes that separate bound and unbound states require extensive sampling that consumes significant computational resources. Here, we describe the use of interactive molecular dynamics in virtual reality (iMD-VR) as an accurate low-cost strategy for flexible protein-ligand docking. We outline an experimental protocol whi… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1908.07395v2-abstract-full').style.display = 'inline'; document.getElementById('1908.07395v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1908.07395v2-abstract-full" style="display: none;"> Simulating drug binding and unbinding is a challenge, as the rugged energy landscapes that separate bound and unbound states require extensive sampling that consumes significant computational resources. Here, we describe the use of interactive molecular dynamics in virtual reality (iMD-VR) as an accurate low-cost strategy for flexible protein-ligand docking. We outline an experimental protocol which enables expert iMD-VR users to guide ligands into and out of the binding pockets of trypsin, neuraminidase, and HIV-1 protease, and recreate their respective crystallographic protein-ligand binding poses within 5 - 10 minutes. Following a brief training phase, our studies shown that iMD-VR novices were able to generate unbinding and rebinding pathways on similar timescales as iMD-VR experts, with the majority able to recover binding poses within 2.15 Angstrom RMSD of the crystallographic binding pose. These results indicate that iMD-VR affords sufficient control for users to carry out the detailed atomic manipulations required to dock flexible ligands into dynamic enzyme active sites and recover crystallographic poses, offering an interesting new approach for simulating drug docking and generating binding hypotheses. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1908.07395v2-abstract-full').style.display = 'none'; document.getElementById('1908.07395v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 4 February, 2020; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 20 August, 2019; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> August 2019. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">PLOS ONE</span> </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1902.01827">arXiv:1902.01827</a> <span> [<a href="https://arxiv.org/pdf/1902.01827">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Chemical Physics">physics.chem-ph</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Human-Computer Interaction">cs.HC</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Biological Physics">physics.bio-ph</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Physics Education">physics.ed-ph</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1063/1.5092590">10.1063/1.5092590 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Interactive molecular dynamics in virtual reality from quantum chemistry to drug binding: An open-source multi-person framework </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=O%27Connor%2C+M">Michael O'Connor</a>, <a href="/search/?searchtype=author&query=Bennie%2C+S+J">Simon J. Bennie</a>, <a href="/search/?searchtype=author&query=Deeks%2C+H+M">Helen M. Deeks</a>, <a href="/search/?searchtype=author&query=Jamieson-Binnie%2C+A">Alexander Jamieson-Binnie</a>, <a href="/search/?searchtype=author&query=Jones%2C+A+J">Alex J. Jones</a>, <a href="/search/?searchtype=author&query=Shannon%2C+R+J">Robin J. Shannon</a>, <a href="/search/?searchtype=author&query=Walters%2C+R">Rebecca Walters</a>, <a href="/search/?searchtype=author&query=Mitchell%2C+T+J">Thomas J. Mitchell</a>, <a href="/search/?searchtype=author&query=Mulholland%2C+A+J">Adrian J. Mulholland</a>, <a href="/search/?searchtype=author&query=Glowacki%2C+D+R">David R. Glowacki</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="1902.01827v3-abstract-short" style="display: inline;"> As molecular scientists have made progress in their ability to engineer nano-scale molecular structure, we are facing new challenges in our ability to engineer molecular dynamics (MD) and flexibility. Dynamics at the molecular scale differs from the familiar mechanics of everyday objects, because it involves a complicated, highly correlated, and three-dimensional many-body dynamical choreography w… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1902.01827v3-abstract-full').style.display = 'inline'; document.getElementById('1902.01827v3-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1902.01827v3-abstract-full" style="display: none;"> As molecular scientists have made progress in their ability to engineer nano-scale molecular structure, we are facing new challenges in our ability to engineer molecular dynamics (MD) and flexibility. Dynamics at the molecular scale differs from the familiar mechanics of everyday objects, because it involves a complicated, highly correlated, and three-dimensional many-body dynamical choreography which is often non-intuitive even for highly trained researchers. We recently described how interactive molecular dynamics in virtual reality (iMD-VR) can help to meet this challenge, enabling researchers to manipulate real-time MD simulations of flexible structures in 3D. In this article, we outline efforts to extend immersive technologies to the molecular sciences, and we introduce 'Narupa', a flexible, open-source, multi-person iMD-VR software framework which enables groups of researchers to simultaneously cohabit real-time simulation environments to interactively visualize and manipulate the dynamics of molecular structures with atomic-level precision. We outline several application domains where iMD-VR is facilitating research, communication, and creative approaches within the molecular sciences, including training machines to learn reactive potential energy surfaces (PESs), biomolecular conformational sampling, protein-ligand binding, reaction discovery using 'on-the-fly' quantum chemistry, and transport dynamics in materials. We touch on iMD-VR's various cognitive and perceptual affordances, and how these provide research insight for molecular systems. By synergistically combining human spatial reasoning and design insight with computational automation, technologies like iMD-VR have the potential to improve our ability to understand, engineer, and communicate microscopic dynamical behavior, offering the potential to usher in a new paradigm for engineering molecules and nano-architectures. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1902.01827v3-abstract-full').style.display = 'none'; document.getElementById('1902.01827v3-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 1 May, 2019; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 5 February, 2019; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> February 2019. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1901.05417">arXiv:1901.05417</a> <span> [<a href="https://arxiv.org/pdf/1901.05417">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Chemical Physics">physics.chem-ph</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Emerging Technologies">cs.ET</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Computational Physics">physics.comp-ph</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1021/acs.jpca.9b01006">10.1021/acs.jpca.9b01006 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Training neural nets to learn reactive potential energy surfaces using interactive quantum chemistry in virtual reality </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Amabilino%2C+S">Silvia Amabilino</a>, <a href="/search/?searchtype=author&query=Bratholm%2C+L+A">Lars A. Bratholm</a>, <a href="/search/?searchtype=author&query=Bennie%2C+S+J">Simon J. Bennie</a>, <a href="/search/?searchtype=author&query=Vaucher%2C+A+C">Alain C. Vaucher</a>, <a href="/search/?searchtype=author&query=Reiher%2C+M">Markus Reiher</a>, <a href="/search/?searchtype=author&query=Glowacki%2C+D+R">David R. Glowacki</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="1901.05417v2-abstract-short" style="display: inline;"> Whilst the primary bottleneck to a number of computational workflows was not so long ago limited by processing power, the rise of machine learning technologies has resulted in a paradigm shift which places increasing value on issues related to data curation - i.e., data size, quality, bias, format, and coverage. Increasingly, data-related issues are equally as important as the algorithmic methods… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1901.05417v2-abstract-full').style.display = 'inline'; document.getElementById('1901.05417v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1901.05417v2-abstract-full" style="display: none;"> Whilst the primary bottleneck to a number of computational workflows was not so long ago limited by processing power, the rise of machine learning technologies has resulted in a paradigm shift which places increasing value on issues related to data curation - i.e., data size, quality, bias, format, and coverage. Increasingly, data-related issues are equally as important as the algorithmic methods used to process and learn from the data. Here we introduce an open source GPU-accelerated neural network (NN) framework for learning reactive potential energy surfaces (PESs), and investigate the use of real-time interactive ab initio molecular dynamics in virtual reality (iMD-VR) as a new strategy for rapidly sampling geometries along reaction pathways which can be used to train NNs to learn reactive PESs. Focussing on hydrogen abstraction reactions of CN radical with isopentane, we compare the performance of NNs trained using iMD-VR data versus NNs trained using a more traditional method, namely molecular dynamics (MD) constrained to sample a predefined grid of points along hydrogen abstraction reaction coordinates. Both the NN trained using iMD-VR data and the NN trained using the constrained MD data reproduce important qualitative features of the reactive PESs, such as a low and early barrier to abstraction. Quantitatively, learning is sensitive to the training dataset. Our results show that user-sampled structures obtained with the quantum chemical iMD-VR machinery enable better sampling in the vicinity of the minimum energy path (MEP). As a result, the NN trained on the iMD-VR data does very well predicting energies in the vicinity of the MEP, but less well predicting energies for 'off-path' structures. The NN trained on the constrained MD data does better in predicting energies for 'off-path' structures, given that it included a number of such structures in its training set. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1901.05417v2-abstract-full').style.display = 'none'; document.getElementById('1901.05417v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 22 January, 2019; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 16 January, 2019; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> January 2019. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> J. Phys. Chem. A 123 (2019) 4486-4499 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1901.03536">arXiv:1901.03536</a> <span> [<a href="https://arxiv.org/pdf/1901.03536">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Human-Computer Interaction">cs.HC</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Computers and Society">cs.CY</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Multimedia">cs.MM</span> </div> </div> <p class="title is-5 mathjax"> Somatic Practices for Understanding Real, Imagined, and Virtual Realities </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Thomas%2C+L+M">Lisa May Thomas</a>, <a href="/search/?searchtype=author&query=Deeks%2C+H+M">Helen M. Deeks</a>, <a href="/search/?searchtype=author&query=Jones%2C+A+J">Alex J. Jones</a>, <a href="/search/?searchtype=author&query=Metatla%2C+O">Oussama Metatla</a>, <a href="/search/?searchtype=author&query=Glowacki%2C+D+R">David R. Glowacki</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="1901.03536v1-abstract-short" style="display: inline;"> In most VR experiences, the visual sense dominates other modes of sensory input, encouraging non-visual senses to respond as if the visual were real. The simulated visual world thus becomes a sort of felt actuality, where the 'actual' physical body and environment can 'drop away', opening up possibilities for designing entirely new kinds of experience. Most VR experiences place visual sensory inpu… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1901.03536v1-abstract-full').style.display = 'inline'; document.getElementById('1901.03536v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1901.03536v1-abstract-full" style="display: none;"> In most VR experiences, the visual sense dominates other modes of sensory input, encouraging non-visual senses to respond as if the visual were real. The simulated visual world thus becomes a sort of felt actuality, where the 'actual' physical body and environment can 'drop away', opening up possibilities for designing entirely new kinds of experience. Most VR experiences place visual sensory input (of the simulated environment) in the perceptual foreground, and the physical body in the background. In what follows, we discuss methods for resolving the apparent tension which arises from VR's prioritization of visual perception. We specifically aim to understand how somatic techniques encouraging participants to 'attend to their attention' enable them to access more subtle aspects of sensory phenomena in a VR experience, bound neither by rigid definitions of vision-based virtuality nor body-based corporeality. During a series of workshops, we implemented experimental somatic-dance practices to better understand perceptual and imaginative subtleties that arise for participants whilst they are embedded in a multi-person VR framework. Our preliminary observations suggest that somatic methods can be used to design VR experiences which enable (i) a tactile quality or felt sense of phenomena in the virtual environment (VE), (ii) lingering impacts on participant imagination even after the VR headset is taken off, and (iii) an expansion of imaginative potential. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1901.03536v1-abstract-full').style.display = 'none'; document.getElementById('1901.03536v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 11 January, 2019; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> January 2019. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1901.03532">arXiv:1901.03532</a> <span> [<a href="https://arxiv.org/pdf/1901.03532">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Human-Computer Interaction">cs.HC</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Biological Physics">physics.bio-ph</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Chemical Physics">physics.chem-ph</span> </div> </div> <p class="title is-5 mathjax"> OMG-VR: Open-source Mudra Gloves for Manipulating Molecular Simulations in VR </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Freire%2C+R">Rachel Freire</a>, <a href="/search/?searchtype=author&query=Glowacki%2C+B+R">Becca Rose Glowacki</a>, <a href="/search/?searchtype=author&query=Williams%2C+R+R">Rhoslyn Roebuck Williams</a>, <a href="/search/?searchtype=author&query=Wonnacott%2C+M">Mark Wonnacott</a>, <a href="/search/?searchtype=author&query=Jamieson-Binnie%2C+A">Alexander Jamieson-Binnie</a>, <a href="/search/?searchtype=author&query=Glowacki%2C+D+R">David R. Glowacki</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="1901.03532v2-abstract-short" style="display: inline;"> As VR finds increasing application in scientific research domains like nanotechnology and biochemistry, we are beginning to better understand the domains in which it brings the most benefit, as well as the gestures and form factors that are most useful for specific applications. Here we describe Open-source Mudra Gloves for Virtual Reality (OMG-VR): etextile gloves designed to facilitate research… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1901.03532v2-abstract-full').style.display = 'inline'; document.getElementById('1901.03532v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1901.03532v2-abstract-full" style="display: none;"> As VR finds increasing application in scientific research domains like nanotechnology and biochemistry, we are beginning to better understand the domains in which it brings the most benefit, as well as the gestures and form factors that are most useful for specific applications. Here we describe Open-source Mudra Gloves for Virtual Reality (OMG-VR): etextile gloves designed to facilitate research scientists and students carrying out detailed and complex manipulation of simulated 3d molecular objects in VR. The OMG-VR is designed to sense when a user pinches together their thumb and index finger, or thumb and middle finger, forming a "mudra" position. Tests show that they provide good positional tracking of the point at which a pinch takes place, require no calibration, and are sufficiently accurate and robust to enable scientists to accomplish a range of tasks that involve complex spatial manipulation of molecules. The open source design offers a promising alternative to existing controllers and more costly commercial VR data gloves. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1901.03532v2-abstract-full').style.display = 'none'; document.getElementById('1901.03532v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 5 May, 2020; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 11 January, 2019; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> January 2019. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1811.10956">arXiv:1811.10956</a> <span> [<a href="https://arxiv.org/pdf/1811.10956">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Chemical Physics">physics.chem-ph</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1021/acs.jpca.8b12006">10.1021/acs.jpca.8b12006 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Anharmonic molecular mechanics: Ab initio based Morse parameterisations for the popular MM3 force field </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Shannon%2C+R+J">R. J. Shannon</a>, <a href="/search/?searchtype=author&query=Hornung%2C+B">B. Hornung</a>, <a href="/search/?searchtype=author&query=Tew%2C+D+P">D. P. Tew</a>, <a href="/search/?searchtype=author&query=Glowacki%2C+D+R">D. R. Glowacki</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="1811.10956v2-abstract-short" style="display: inline;"> Methodologies for creating reactive potential energy surfaces from molecular mechanics force-fields are becoming increasingly popular. To date, molecular mechanics force-fields use harmonic expressions to treat bonding stretches, which is a poor approximation in reactive molecular dynamics simulations since bonds are displaced significantly from their equilibrium positions. For such applications t… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1811.10956v2-abstract-full').style.display = 'inline'; document.getElementById('1811.10956v2-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1811.10956v2-abstract-full" style="display: none;"> Methodologies for creating reactive potential energy surfaces from molecular mechanics force-fields are becoming increasingly popular. To date, molecular mechanics force-fields use harmonic expressions to treat bonding stretches, which is a poor approximation in reactive molecular dynamics simulations since bonds are displaced significantly from their equilibrium positions. For such applications there is need for a better treatment of anharmonicity. In this contribution Morse bonding potentials have been extensively parameterised for the atom types in the MM3 force field of Allinger and co-workers using high level CCSD(T)(F12*) energies. To our knowledge this is the first instance of a large-scale paramerization of Morse potentials in a popular force field. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1811.10956v2-abstract-full').style.display = 'none'; document.getElementById('1811.10956v2-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 21 May, 2019; <span class="has-text-black-bis has-text-weight-semibold">v1</span> submitted 27 November, 2018; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2018. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> J. Phys. Chem. A 2019, 123, 13, 2991-2999 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1811.10351">arXiv:1811.10351</a> <span> [<a href="https://arxiv.org/pdf/1811.10351">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Chemical Physics">physics.chem-ph</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1021/acs.jctc.8b00515">10.1021/acs.jctc.8b00515 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Adaptively accelerating reactive molecular dynamics using boxed molecular dynamics in energy space </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Shannon%2C+R+J">Robin J Shannon</a>, <a href="/search/?searchtype=author&query=Amabilino%2C+S">Silvia Amabilino</a>, <a href="/search/?searchtype=author&query=OConnor%2C+M">Mike OConnor</a>, <a href="/search/?searchtype=author&query=Shalishilin%2C+D+V">Dmitrii V Shalishilin</a>, <a href="/search/?searchtype=author&query=Glowacki%2C+D+R">David R Glowacki</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="1811.10351v1-abstract-short" style="display: inline;"> The problem of observing rare events is pervasive among the molecular dynamics community and an array of different types of methods are commonly used to accelerate these long timescale processes. Typically, rare event acceleration methods require an a priori specification of the event to be accelerated. In recent work, we have demonstrated the application of boxed molecular dynamics to energy spac… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1811.10351v1-abstract-full').style.display = 'inline'; document.getElementById('1811.10351v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1811.10351v1-abstract-full" style="display: none;"> The problem of observing rare events is pervasive among the molecular dynamics community and an array of different types of methods are commonly used to accelerate these long timescale processes. Typically, rare event acceleration methods require an a priori specification of the event to be accelerated. In recent work, we have demonstrated the application of boxed molecular dynamics to energy space, as a way to accelerate rare events in the stochastic chemical master equation. Here we build upon this work and apply the boxed molecular dynamics algorithm to the energy space of a molecule in classical trajectory simulations. Through this new BXD in energy (BXDE) approach we demonstrate that generic rare events (in this case chemical reactions) may be accelerated by multiple orders of magnitude compared to unbiased simulations. Furthermore, we show that the ratios of products formed from the BXDE simulations are similar to those formed in unbiased simulations at the same temperature. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1811.10351v1-abstract-full').style.display = 'none'; document.getElementById('1811.10351v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 26 November, 2018; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2018. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> J. Chem. Theory Comput. 2018, 14, 9, 4541 4552 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1811.10324">arXiv:1811.10324</a> <span> [<a href="https://arxiv.org/pdf/1811.10324">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Chemical Physics">physics.chem-ph</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1021/acs.jpca.7b12521">10.1021/acs.jpca.7b12521 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> A simple Boxed Molecular Kinetics approach to accelerate rare events in the stochastic kinetic master equation </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Shannon%2C+R+J">Robin J Shannon</a>, <a href="/search/?searchtype=author&query=Glowacki%2C+D+R">David R Glowacki</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="1811.10324v1-abstract-short" style="display: inline;"> The chemical master equation is a powerful theoretical tool for analysing the kinetics of complex multi-well potential energy surfaces in a wide range of different domains of chemical kinetics spanning combustion, atmospheric chemistry, gas surface chemistry, solution phase chemistry, and biochemistry. There are two well-established methodologies for solving the chemical master equation: a stochas… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1811.10324v1-abstract-full').style.display = 'inline'; document.getElementById('1811.10324v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1811.10324v1-abstract-full" style="display: none;"> The chemical master equation is a powerful theoretical tool for analysing the kinetics of complex multi-well potential energy surfaces in a wide range of different domains of chemical kinetics spanning combustion, atmospheric chemistry, gas surface chemistry, solution phase chemistry, and biochemistry. There are two well-established methodologies for solving the chemical master equation: a stochastic kinetic Monte Carlo approach and a matrix-based approach. In principle, the results yielded by both approaches are identical; the decision of which approach is better suited to a particular study depends on the details of the specific system under investigation. In this article, we present a rigorous method for accelerating stochastic approaches by several orders of magnitude, along with a method for unbiasing the accelerated results to recover the true value. The approach we take in this paper is inspired by the so-called boxed molecular dynamics (BXD) method, which has previously only been applied to accelerate rare events in molecular dynamics simulations. Here we extend BXD to design a simple algorithmic strategy for accelerating rare events in stochastic kinetic simulations. Tests on a number of systems show that the results obtained using the BXD rare event strategy are in good agreement with unbiased results. To carry out these tests, we have implemented a kinetic Monte Carlo approach in MESMER, which is a cross platform, open-source, and freely available master equation solver. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1811.10324v1-abstract-full').style.display = 'none'; document.getElementById('1811.10324v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 26 November, 2018; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> November 2018. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> J. Phys. Chem. A 2018, 122, 1531 1541 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1803.05805">arXiv:1803.05805</a> <span> [<a href="https://arxiv.org/pdf/1803.05805">pdf</a>, <a href="https://arxiv.org/format/1803.05805">other</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Human-Computer Interaction">cs.HC</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Biological Physics">physics.bio-ph</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Computational Physics">physics.comp-ph</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Other Quantitative Biology">q-bio.OT</span> </div> </div> <p class="title is-5 mathjax"> Sonifying stochastic walks on biomolecular energy landscapes </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Arbon%2C+R+E">Robert E. Arbon</a>, <a href="/search/?searchtype=author&query=Jones%2C+A+J">Alex J. Jones</a>, <a href="/search/?searchtype=author&query=Bratholm%2C+L+A">Lars A. Bratholm</a>, <a href="/search/?searchtype=author&query=Mitchell%2C+T">Tom Mitchell</a>, <a href="/search/?searchtype=author&query=Glowacki%2C+D+R">David R. Glowacki</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="1803.05805v1-abstract-short" style="display: inline;"> Translating the complex, multi-dimensional data from simulations of biomolecules to intuitive knowledge is a major challenge in computational chemistry and biology. The so-called "free energy landscape" is amongst the most fundamental concepts used by scientists to understand both static and dynamic properties of biomolecular systems. In this paper we use Markov models to design a strategy for map… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1803.05805v1-abstract-full').style.display = 'inline'; document.getElementById('1803.05805v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1803.05805v1-abstract-full" style="display: none;"> Translating the complex, multi-dimensional data from simulations of biomolecules to intuitive knowledge is a major challenge in computational chemistry and biology. The so-called "free energy landscape" is amongst the most fundamental concepts used by scientists to understand both static and dynamic properties of biomolecular systems. In this paper we use Markov models to design a strategy for mapping features of this landscape to sonic parameters, for use in conjunction with visual display techniques such as structural animations and free energy diagrams. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1803.05805v1-abstract-full').style.display = 'none'; document.getElementById('1803.05805v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 15 March, 2018; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> March 2018. </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1801.02884">arXiv:1801.02884</a> <span> [<a href="https://arxiv.org/pdf/1801.02884">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Chemical Physics">physics.chem-ph</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Human-Computer Interaction">cs.HC</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Biological Physics">physics.bio-ph</span> <span class="tag is-small is-grey tooltip is-tooltip-top" data-tooltip="Physics Education">physics.ed-ph</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1126/sciadv.aat2731">10.1126/sciadv.aat2731 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> Sampling molecular conformations and dynamics in a multi-user virtual reality framework </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Connor%2C+M+O">Michael O Connor</a>, <a href="/search/?searchtype=author&query=Deeks%2C+H+M">Helen M. Deeks</a>, <a href="/search/?searchtype=author&query=Dawn%2C+E">Edward Dawn</a>, <a href="/search/?searchtype=author&query=Metatla%2C+O">Oussama Metatla</a>, <a href="/search/?searchtype=author&query=Roudaut%2C+A">Anne Roudaut</a>, <a href="/search/?searchtype=author&query=Sutton%2C+M">Matthew Sutton</a>, <a href="/search/?searchtype=author&query=Glowacki%2C+B+R">Becca Rose Glowacki</a>, <a href="/search/?searchtype=author&query=Sage%2C+R">Rebecca Sage</a>, <a href="/search/?searchtype=author&query=Tew%2C+P">Philip Tew</a>, <a href="/search/?searchtype=author&query=Wonnacott%2C+M">Mark Wonnacott</a>, <a href="/search/?searchtype=author&query=Bates%2C+P">Phil Bates</a>, <a href="/search/?searchtype=author&query=Mulholland%2C+A+J">Adrian J. Mulholland</a>, <a href="/search/?searchtype=author&query=Glowacki%2C+D+R">David R. Glowacki</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="1801.02884v1-abstract-short" style="display: inline;"> We describe a framework for interactive molecular dynamics in a multiuser virtual reality environment, combining rigorous cloud-mounted physical atomistic simulation with commodity virtual reality hardware, which we have made accessible to readers (see isci.itch.io/nsb-imd). It allows users to visualize and sample, with atomic-level precision, the structures and dynamics of complex molecular struc… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1801.02884v1-abstract-full').style.display = 'inline'; document.getElementById('1801.02884v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1801.02884v1-abstract-full" style="display: none;"> We describe a framework for interactive molecular dynamics in a multiuser virtual reality environment, combining rigorous cloud-mounted physical atomistic simulation with commodity virtual reality hardware, which we have made accessible to readers (see isci.itch.io/nsb-imd). It allows users to visualize and sample, with atomic-level precision, the structures and dynamics of complex molecular structures 'on the fly', and to interact with other users in the same virtual environment. A series of controlled studies, wherein participants were tasked with a range of molecular manipulation goals (threading methane through a nanotube, changing helical screw-sense, and tying a protein knot), quantitatively demonstrate that users within the interactive VR environment can complete sophisticated molecular modelling tasks more quickly than they can using conventional interfaces, especially for molecular pathways and structural transitions whose conformational choreographies are intrinsically 3d. This framework should accelerate progress in nanoscale molecular engineering areas such as drug development, synthetic biology, and catalyst design. More broadly, our findings highlight VR's potential in scientific domains where 3d dynamics matter, spanning research and education. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1801.02884v1-abstract-full').style.display = 'none'; document.getElementById('1801.02884v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 9 January, 2018; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> January 2018. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">5 pages, 3 figures, 19 pages Supporting Info</span> </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Journal ref:</span> Science Advances, Jun 2018: Vol. 4, no. 6, eaat2731 </p> </li> <li class="arxiv-result"> <div class="is-marginless"> <p class="list-title is-inline-block"><a href="https://arxiv.org/abs/1412.4180">arXiv:1412.4180</a> <span> [<a href="https://arxiv.org/pdf/1412.4180">pdf</a>] </span> </p> <div class="tags is-inline-block"> <span class="tag is-small is-link tooltip is-tooltip-top" data-tooltip="Chemical Physics">physics.chem-ph</span> </div> <div class="is-inline-block" style="margin-left: 0.5rem"> <div class="tags has-addons"> <span class="tag is-dark is-size-7">doi</span> <span class="tag is-light is-size-7"><a class="" href="https://doi.org/10.1063/1.4926996">10.1063/1.4926996 <i class="fa fa-external-link" aria-hidden="true"></i></a></span> </div> </div> </div> <p class="title is-5 mathjax"> A parallel multistate framework for atomistic non-equilibrium reaction dynamics of solutes in strongly interacting organic solvents </p> <p class="authors"> <span class="search-hit">Authors:</span> <a href="/search/?searchtype=author&query=Glowacki%2C+D+R">David R. Glowacki</a>, <a href="/search/?searchtype=author&query=Orr-Ewing%2C+A+J">Andrew J. Orr-Ewing</a>, <a href="/search/?searchtype=author&query=Harvey%2C+J+N">Jeremy N. Harvey</a> </p> <p class="abstract mathjax"> <span class="has-text-black-bis has-text-weight-semibold">Abstract</span>: <span class="abstract-short has-text-grey-dark mathjax" id="1412.4180v1-abstract-short" style="display: inline;"> We describe a parallel linear-scaling computational framework developed to implement arbitrarily large multi-state empirical valence bond (MS-EVB) calculations within CHARMM. Forces are obtained using the Hellman-Feynmann relationship, giving continuous gradients, and excellent energy conservation. Utilizing multi-dimensional Gaussian coupling elements fit to CCSD(T)-F12 electronic structure theor… <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1412.4180v1-abstract-full').style.display = 'inline'; document.getElementById('1412.4180v1-abstract-short').style.display = 'none';">▽ More</a> </span> <span class="abstract-full has-text-grey-dark mathjax" id="1412.4180v1-abstract-full" style="display: none;"> We describe a parallel linear-scaling computational framework developed to implement arbitrarily large multi-state empirical valence bond (MS-EVB) calculations within CHARMM. Forces are obtained using the Hellman-Feynmann relationship, giving continuous gradients, and excellent energy conservation. Utilizing multi-dimensional Gaussian coupling elements fit to CCSD(T)-F12 electronic structure theory, we built a 64-state MS-EVB model designed to study the F + CD3CN -> DF + CD2CN reaction in CD3CN solvent. This approach allows us to build a reactive potential energy surface (PES) whose balanced accuracy and efficiency considerably surpass what we could achieve otherwise. We use our PES to run MD simulations, and examine a range of transient observables which follow in the wake of reaction, including transient spectra of the DF vibrational band, time dependent profiles of vibrationally excited DF in CD3CN solvent, and relaxation rates for energy flow from DF into the solvent, all of which agree well with experimental observations. Immediately following deuterium abstraction, the nascent DF is in a non-equilibrium regime in two different respects: (1) it is highly excited, with ~23 kcal mol-1 localized in the stretch; and (2) not yet Hydrogen bonded to the CD3CN solvent, its microsolvation environment is intermediate between the non-interacting gas-phase limit and the solution-phase equilibrium limit. Vibrational relaxation of the nascent DF results in a spectral blue shift, while relaxation of its microsolvation environment results in a red shift. These two competing effects result in a post-reaction relaxation profile distinct from that observed when DF vibration excitation occurs within an equilibrium microsolvation environment. The parallel software framework presented in this paper should be more broadly applicable to a range of complex reactive systems. <a class="is-size-7" style="white-space: nowrap;" onclick="document.getElementById('1412.4180v1-abstract-full').style.display = 'none'; document.getElementById('1412.4180v1-abstract-short').style.display = 'inline';">△ Less</a> </span> </p> <p class="is-size-7"><span class="has-text-black-bis has-text-weight-semibold">Submitted</span> 12 December, 2014; <span class="has-text-black-bis has-text-weight-semibold">originally announced</span> December 2014. </p> <p class="comments is-size-7"> <span class="has-text-black-bis has-text-weight-semibold">Comments:</span> <span class="has-text-grey-dark mathjax">58 pages and 29 Figures</span> </p> </li> </ol> <div class="is-hidden-tablet">  <span class="help" style="display: inline-block;"><a href="https://github.com/arXiv/arxiv-search/releases">Search v0.5.6 released 2020-02-24</a>  </span> </div> </div> </main> 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