Machine Learning for Atomistic Simulation V: Vibrational, Transport, and Magnetic Properties

Presentations

• Machine learning methods for finite-temperature full-quantum simulations: Predictive modelling of condensed phases and interfaces

  ORAL · Invited

  March 19, 2025, 2:30 PM – March 19, 2025, 3:06 PM

  Publication: [1] Kaur, H., Della Pia, F., Batatia, I., Advincula, X. R., Shi, B. X., Lan, J., Csányi, G., Michaelides, A., & Kapil, V. (2024). Data-efficient fine-tuning of foundational models for first-principles quality sublimation enthalpies. https://doi.org/10.48550/ARXIV.2405.20217
  
  [2] Kapil, V., Kovács, D. P., Csányi, G., & Michaelides, A. (2023). First-principles spectroscopy of aqueous interfaces using machine-learned electronic and quantum nuclear effects. Faraday Discussions, 10.1039.D3FD00113J. https://doi.org/10.1039/D3FD00113J
  
  [3] Musil, F., Zaporozhets, I., Noé, F., Clementi, C., & Kapil, V. (2022). Quantum dynamics using path integral coarse-graining. The Journal of Chemical Physics, 157(18), 181102. https://doi.org/10.1063/5.0120386
  
  [4] Kapil, V., Schran, C., Zen, A., Chen, J., Pickard, C. J., & Michaelides, A. (2022). The first-principles phase diagram of monolayer nanoconfined water. Nature, 609(7927), 512–516. https://doi.org/10.1038/s41586-022-05036-x
  
  [5] Ravindra, P., Advincula, X. R., Schran, C., Michaelides, A., & Kapil, V. (2024). Quasi-one-dimensional hydrogen bonding in nanoconfined ice. Nature Communications, 15(1), 7301. https://doi.org/10.1038/s41467-024-51124-z
  
  [6] Ravindra, P., Advincula, X. R., Shi, B. X., Coles, S. W., Michaelides, A., & Kapil, V. (2024). Nuclear quantum effects induce superionic proton transport in nanoconfined water. arXiv. https://doi.org/10.48550/ARXIV.2410.03272

  Presenters

  • Venkat Kapil

    University College London

  Authors

  • Venkat Kapil

    University College London

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• Nuclear Quantum Effects on the Melting Properties of First-Principles Water Models

  ORAL

  March 19, 2025, 3:06 PM – March 19, 2025, 3:18 PM

  Presenters

  • Yifan Li

    Princeton University

  Authors

  • Yifan Li

    Princeton University

  • Bingjia Yang

    Princeton University

  • Chunyi Zhang

    Princeton University

  • Pinchen Xie

    Lawrence Berkeley National Lab, Princeton University

  • Yixiao Chen

    Princeton University

  • Pablo Miguel Piaggi

    Princeton University

  • Roberto Car

    Princeton University

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• Thermal Conductivity Predictions with Foundation Atomistic Models

  ORAL

  March 19, 2025, 3:18 PM – March 19, 2025, 3:30 PM

  Publication: Póta, B., Ahlawat, P., Csányi, G., & Simoncelli, M. (2024). Thermal Conductivity Predictions with Foundation Atomistic Models. arXiv preprint arXiv:2408.00755.

  Presenters

  • Balazs Pota

    Theory of Condensed Matter Group, Cavendish Laboratory, University of Cambridge

  Authors

  • Balazs Pota

    Theory of Condensed Matter Group, Cavendish Laboratory, University of Cambridge

  • Paramvir Ahlawat

    Theory of Condensed Matter Group, Cavendish Laboratory, University of Cambridge

  • Gabor Csanyi

    Engineering Laboratory, University of Cambridge, Applied Mechanics Group, Mechanics, Materials and Design, Department of Engineering, University of Cambridge

  • Michele Simoncelli

    Theory of Condensed Matter Group, Cavendish Laboratory, University of Cambridge, Univ of Cambridge, TCM group, Cavendish Laboratory, University of Cambridge

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• Accuracy of Phonon Dispersion Calculations via Machine Learning Potentials

  ORAL

  March 19, 2025, 3:30 PM – March 19, 2025, 3:42 PM

  Presenters

  • Jaesuk Park

    University of Texas at Austin

  Authors

  • Jaesuk Park

    University of Texas at Austin

  • Feliciano Giustino

    University of Texas at Austin

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• Model expressiveness and data sampling effects on phonon uncertainty quantification in machine-learning interatomic potentials

  ORAL

  March 19, 2025, 3:42 PM – March 19, 2025, 3:54 PM

  Presenters

  • Young-Jae Choi

    University of Illinois at Urbana-Champaign

  Authors

  • Young-Jae Choi

    University of Illinois at Urbana-Champaign

  • Lucas K Wagner

    University of Illinois at Urbana-Champaign

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• Dynamically training machine learning based force-fields for strongly anharmonic materials

  ORAL

  March 19, 2025, 3:54 PM – March 19, 2025, 4:06 PM

  Presenters

  • Martin Callsen

    Academia Sinica

  Authors

  • Martin Callsen

    Academia Sinica

  • Tai-Ting Lee

    Academia Sinica

  • Mei-Yin Chou

    Academia Sinica

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• Oral: Prediction of Thermal Conductivity in CALF-20 with First-Principles Accuracy via Machine Learning Interatomic Potentials

  ORAL

  March 19, 2025, 4:06 PM – March 19, 2025, 4:18 PM

  Publication: Submitted to Communications Materials

  Presenters

  • Soham Mandal

    Indian Institute of Science Bangalore

  Authors

  • Soham Mandal

    Indian Institute of Science Bangalore

  • Prabal K Maiti

    Indian Institute of Science, Bangalore, Indian Institute of Science, Indian Institute of Science Bangalore

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• Charge density wave order in twisted niobium diselenide: a machine-learning interatomic approach

  ORAL

  March 19, 2025, 4:18 PM – March 19, 2025, 4:30 PM

  Presenters

  • Norma Rivano

    Harvard

  Authors

  • Norma Rivano

    Harvard

  • Zachary AH Goodwin

    University of Oxford, Harvard University

  • Francesco Libbi

    Harvard University

  • Chuin Wei Tan

    Harvard University

  • Boris Kozinsky

    Harvard University

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• Efficient Modelling of Anharmonicity and Quantum Effects in PdCuH$_2$ with Machine Learning Potentials

  ORAL

  March 19, 2025, 4:30 PM – March 19, 2025, 4:42 PM

  Publication: F. Belli, E. Zurek. Efficient Modelling of Anharmonicity and Quantum Effects in PdCuH2 with Machine Learning Potentials. arXiv preprint: arXiv:2406.13178

  Presenters

  • Francesco Belli

    State Univ of NY - Buffalo

  Authors

  • Francesco Belli

    State Univ of NY - Buffalo

  • Eva D Zurek

    State Univ of NY - Buffalo

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• A universal force field for molecular and electron dynamics

  ORAL

  March 19, 2025, 4:42 PM – March 19, 2025, 4:54 PM

  Presenters

  • Anthony Mannino

    Stony Brook University (SUNY)

  Authors

  • Anthony Mannino

    Stony Brook University (SUNY)

  • Isidro Losada Lopez

    Univ Autonoma de Madrid

  • Simon Divilov

    Duke University

  • Eduardo Hernandez

    Consejo Superior de Investigaciones Científicas

  • Javier Junquera

    Universidad de Cantabria

  • Marivi Fernandez-Serra

    Stony Brook University

  • Jose M Soler

    Univ Autonoma de Madrid

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• Abstract Withdrawn

  ORAL Withdrawn

  March 19, 2025, 4:54 PM – March 19, 2025, 5:06 PM

  View abstract →

• Effect of Local Water Uptake on Proton Transport in Covalent Organic Framework revealed by Machine-Learning Potentials

  ORAL

  March 19, 2025, 5:06 PM – March 19, 2025, 5:18 PM

  Publication: S. Minami et al., Chemistry of Materials, 2024, 36, 19, 9535-9546, DOI: 10.1021/acs.chemmater.4c01351

  Presenters

  • Saori Minami

    Toyota Central R&D Labs, Inc.

  Authors

  • Saori Minami

    Toyota Central R&D Labs, Inc.

  • Masane Kin

    DENSO CORPORATION

  • Kazuki Takahashi

    DENSO CORPORATION

  • Takashi Sato

    DENSO CORPORATION

  • Ryosuke Jinnouchi

    Toyota Central R&D Labs, Inc.

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• Revealing the fundamental proton transport mechanism in solid acid compounds through machine learning molecular dynamics

  ORAL

  March 19, 2025, 5:18 PM – March 19, 2025, 5:30 PM

  Presenters

  • Menghang Wang

    Harvard University

  Authors

  • Menghang Wang

    Harvard University

  • Jingxuan Ding

    Harvard University

  • Grace Xiong

    Northwestern University

  • Ni Zhan

    Princeton University

  • Cameron John Owen

    Harvard University

  • Albert Musaelian

    Harvard University

  • Yu Xie

    Harvard University

  • Nicola Molinari

    Robert Bosch LLC

  • Ryan P Adams

    Princeton University

  • Sossina M Haile

    Northwestern University

  • Boris Kozinsky

    Harvard University

  View abstract →