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Machine Learning for Atomistic Simulation II: Electronic Structure and Long-Range Charge Interactions

FOCUS · MAR-C50 · ID: 3104614

Presentations

  • Deep learning density functional theory and beyond

    ORAL · Invited

    –

    Publication: [1] H. Li, et al. Nature Computational Science 2, 367 (2022) arXiv: 2104.03786<br>[2] X. Gong, et al. Nature Communications 14, 2848 (2023)<br>[3] H. Li, et al. Nature Computational Science 3, 321 (2023)<br>[4] H. Li, et al. Physical Review Letters 132, 096401 (2024)<br>[5] Y. Li, et al. Physical Review Letters 133, 076401 (2024)<br>[6] Z. Tang, et al. Nature Communications 15, 8815 (2024)<br>[7] X. Gong, et al. Nature Computational Science 4, 752 (2024)<br>[8] Z Yuan, et al. Quantum Frontiers 3, 8 (2024)<br>[9] Y Wang, et al. Science Bulletin 69, 2514 (2024)<br>[10] Y Wang, et al. arXiv:2401.17015<br>[11] H. Li, et al. Materials Genome Engineering Advances e16 (2023)<br>[12] H. Li, et al. Physics, 53, 442 (2024)

    Presenters

    • Yong Xu

      Tsinghua University

    Authors

    • Yong Xu

      Tsinghua University

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  • Teaching oxidation states to neural networks

    ORAL

    –

    Presenters

    • Cristiano Malica

      University of Bremen

    Authors

    • Cristiano Malica

      University of Bremen

    • Nicola Marzari

      Ecole Polytechnique Federale de Lausanne, École Polytechnique Fédérale de Lausanne (EPFL), Ecole Polytechnique Federale de Lausanne (EPFL), Paul Scherrer Institut (PSI)

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  • Predicting first-principles Hubbard parameters with equivariant deep learning

    ORAL

    –

    Publication: M. Uhrin et al., arXiV:2406.02457 (2024)<br>A. Zadoks et al, planned

    Presenters

    • Austin Zadoks

      Ecole Polytechnique Federale de Lausanne

    Authors

    • Austin Zadoks

      Ecole Polytechnique Federale de Lausanne

    • Martin Uhrin

      Universite Grenoble Alpes

    • Luca Binci

      University of California, Berkeley, Lawrence Berkeley National Laboratory

    • Lorenzo Bastonero

      University of Bremen

    • Cristiano Malica

      University of Bremen

    • Iurii Timrov

      Paul Scherrer Institut, Paul Scherrer Institute

    • Nicola Marzari

      Ecole Polytechnique Federale de Lausanne, École Polytechnique Fédérale de Lausanne (EPFL), Ecole Polytechnique Federale de Lausanne (EPFL), Paul Scherrer Institut (PSI)

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  • Unsupervised Learning of Individual Kohn-Sham States: Interpretable Representations and Consequences for Downstream Predictions of Many-Body Effects

    ORAL

    –

    Publication: [1] B. Hou, et al, "Unsupervised Learning of Individual Kohn-Sham States: Interpretable Representations and Consequences for Downstream Predictions of Many-Body Effects" arXiv, 2404.14601, 2024 (https://arxiv.org/abs/2404.14601)<br>[2] B. Hou, et al, "Unsupervised Representation Learning of Kohn-Sham States and Consequences for Downstream Predictions of Many-Body Effects", Nature Communications (accepted) 2024: <br>

    Presenters

    • Bowen Hou

      Yale University

    Authors

    • Bowen Hou

      Yale University

    • Jinyuan Wu

      Yale University

    • Diana Y Qiu

      Yale University

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  • Machine Learning Framework for Predicting Strain-Induced Electronic and Optoelectronic Properties of Heterostructure TMDCs

    ORAL

    –

    Presenters

    • Arnab Neogi

      Los Alamos National Laboratory

    Authors

    • Arnab Neogi

      Los Alamos National Laboratory

    • Christopher A Lane

      Los Alamos National Lab, Los Alamos National Laboratory, Los Alamos National Laboratory (LANL)

    • Sergei Tretiak

      Los Alamos National Laboratory (LANL)

    • Jian-Xin Zhu

      Los Alamos National Laboratory (LANL), Los Alamos National Laboratory

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  • Computation Aid for Moire Material Electronic Structure Using Targeted Trained Graph Neural Networks

    ORAL

    –

    Publication: Planned paper: Moire Material Electronic Structure Study Aid With Targeted Trained Graph Neural Networks

    Presenters

    • Jonas Valenzuela Teran

      Department of Physics & Astronomy, Texas A&M University

    Authors

    • Jonas Valenzuela Teran

      Department of Physics & Astronomy, Texas A&M University

    • Bin Yang

      Department of Physics & Astronomy, Texas A&M University

    • Winfried Teizer

      Department of Physics & Astronomy and Department of Materials Science and Engineering, Texas A&M University

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  • Radical AI — Accelerating Materials R&amp;D

    ORAL

    –

    Publication: S. Falletta, A. Cepellotti, A. Johansson, C. W. Tan, A. Musaelian, C. J. Owen, B. Kozinsky, arXiv:2403.17207 (2024)

    Presenters

    • Stefano Falletta

      Harvard University, Harvard

    Authors

    • Stefano Falletta

      Harvard University, Harvard

    • Andrea Cepellotti

      Harvard University

    • Andres Johansson

      Harvard University

    • Chuin Wei Tan

      Harvard University

    • Marc L Descoteaux

      Harvard University

    • Albert Musaelian

      Harvard University

    • Cameron John Owen

      Harvard University

    • Boris Kozinsky

      Harvard University

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  • Machine learning small polaron dynamics

    ORAL

    –

    Publication: Birschitzky, V. C., Leoni, L., Reticcioli, M. & Franchini, C. Machine Learning Small Polaron Dynamics 2024. arXiv: 2409.16179 [cond-mat.mtrl-sci]. https://arxiv.org/abs/2409.16179

    Presenters

    • Luca Leoni

      University of Bologna

    Authors

    • Luca Leoni

      University of Bologna

    • Viktor C Birschitzky

      University of Vienna

    • Michele Reticcioli

      University of Vienna

    • Cesare Franchini

      University of Vienna

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