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Emerging Trends in Molecular Dynamics Simulations and Machine Learning III

FOCUS · N49 · ID: 47208

Presentations

  • Modeling Earth's interior from atomic to global scale

    ORAL · Invited

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    Publication: 1) R. M. Wentzcovitch et al., DOI: 10.1073/pnas.081215010<br>2) G. Shephard et al., DOI: 10.1038/s41467-021-26115-z

    Presenters

    • Renata M Wentzcovitch

      Columbia Univ, Columbia University

    Authors

    • Renata M Wentzcovitch

      Columbia Univ, Columbia University

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  • Large-scale dynamics simulations of complex liquid electrolytes with NequIP equivariant machine learning models.

    ORAL

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    Publication: [1] Batzner, S., Musaelian, A., Sun, L., Geiger, M., Mailoa, J.P., Kornbluth, M., Molinari, N., Smidt, T.E. and Kozinsky, B., 2021. Se (3)-equivariant graph neural networks for data-efficient and accurate interatomic potentials. arXiv preprint arXiv:2101.03164.<br>[2] Molinari, N., Mailoa, J.P. and Kozinsky, B., 2019. General trend of a negative Li effective charge in ionic liquid electrolytes. The journal of physical chemistry letters, 10(10), pp.2313-2319.

    Presenters

    • Nicola Molinari

      Harvard University, Robert Bosch LLC Research and Technology Center North America; Harvard University

    Authors

    • Nicola Molinari

      Harvard University, Robert Bosch LLC Research and Technology Center North America; Harvard University

    • Albert Musaelian

      Harvard University

    • Simon L Batzner

      Harvard University

    • Boris Kozinsky

      Harvard University

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  • Application of Machine Learning to the Development of Ti Interatomic Potentials

    ORAL

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    Publication: N/A

    Presenters

    • Sean J O'Connor

      Honeywell FM&T

    Authors

    • Sean J O'Connor

      Honeywell FM&T

    • Volker Eyert

      Materials Design, Inc

    • Jörg-Rüdiger Hill

      Materials Design, Inc

    • David Reith

      Materials Design, Inc

    • Erich Wimmer

      Materials Design, Inc

    • Patrick R Thomas

      Honeywell FM&T, Department of Energy's Kansas City National Security Campus Managed by Honeywell FM&T

    • Ben Sikora

      Honeywell FM&T, Department of Energy's Kansas City National Security Campus Managed by Honeywell FM&T

    • Paul Rulis

      University of Missouri - Kansas City

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  • Machine Learned Interatomic Potential Development for W-ZrC

    ORAL

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    Presenters

    • Ember L Sikorski

      Sandia National Laboratories

    Authors

    • Ember L Sikorski

      Sandia National Laboratories

    • Julien Tranchida

      CEA Cadarache, CEA

    • Mary Alice Cusentino

      Sandia National Laboratories

    • Mitchell A Wood

      Sandia National Laboratories

    • Aidan P Thompson

      Sandia National Laboratories

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  • Generative Coarse-Graining

    ORAL

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    Presenters

    • Wujie Wang

      Massachusetts Institute of Technology MI

    Authors

    • Wujie Wang

      Massachusetts Institute of Technology MI

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  • Dynamical strengthening of covalent and non-covalent molecular interactions by nuclear quantum effects at finite temperature

    ORAL

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    Publication: - H.E. Sauceda, M. Gastegger, S. Chmiela, K.-R. Müller, A. Tkatchenko "Molecular force fields with gradient-domain machine learning (GDML): Comparison and synergies with classical force fields" Journal of Chemical Physics 153 (12), 124109 (2020)<br>- H.E. Sauceda, V. Vassilev-Galindo, S. Chmiela, K.-R. Müller, A. Tkatchenko "Dynamical strengthening of covalent and non-covalent molecular interactions by nuclear quantum effects at finite temperature" Nature Communications 12 (1), 1-10 (2021)<br>- H.E. Sauceda, L.E. Gálvez-González, S. Chmiela, L.O. Paz-Borbón, K.-R. Müller, A. Tkatchenko "BIGDML: Towards Exact Machine Learning Force Fields for Materials" arXiv:2106.04229 (2021)

    Presenters

    • Huziel E Sauceda

      Technical University of Berlin

    Authors

    • Huziel E Sauceda

      Technical University of Berlin

    • Valentin Vassilev Galindo

      University of Luxembourg Limpertsberg

    • Stefan Chmiela

      Tech Univ Berlin

    • Klaus-Robert Müller

      Technical University of Berlin

    • Alexandre Tkatchenko

      University of Luxembourg Limpertsberg

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  • Quantum paraelectricity and structural phase transitions of SrTiO<sub>3</sub> by on-the-fly machine-learned interatomic potentials

    ORAL

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    Presenters

    • Carla Verdi

      Univ of Vienna, University of Vienna

    Authors

    • Carla Verdi

      Univ of Vienna, University of Vienna

    • Luigi Ranalli

      Univ of Vienna

    • Cesare Franchini

      University of Vienna, Univ of Vienna, Univ of Vienna, Univ of Bologna, Universita' di Bologna & University of Vienna, University of Vienna, A-1090 Vienna, Austria, Alma Mater Studiorum–Università di Bologna, Bologna, 40127, Italy

    • Georg Kresse

      Univ of Vienna, University of Vienna

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