Lattice Dynamics, Transport and Phonons with Machine-Learning Methods

Presentations

• Phonons at Scale: High-Throughput Lattice Dynamics for Data-Driven Materials Discovery

  ORAL · Invited

  March 19, 2026, 8:00 AM – March 19, 2026, 8:36 AM

  Presenters

  • Anubhav Jain

    • Lawrence Berkeley National Laboratory
    • LBNL

  Authors

  • Anubhav Jain

    • Lawrence Berkeley National Laboratory
    • LBNL

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• Unlocking Charge-Mediated Phase Transformation in Titanium: A Machine Learning Force Field and Phonon Free Energy Study

  ORAL

  March 19, 2026, 8:36 AM – March 19, 2026, 8:48 AM

  Presenters

  • SEUNGWOO YOO

    • Kyung Hee University - Seoul

  Authors

  • SEUNGWOO YOO

    • Kyung Hee University - Seoul

  • Young-Kyun Kwon

    • Kyung Hee University - Seoul

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• Unravelling the origins of sluggish atomic diffusion in Fe-Ni alloys: Ab initio calculations, atomistic simulations, and a theoretical analysis

  ORAL

  March 19, 2026, 8:48 AM – March 19, 2026, 9:00 AM

  Publication: arXiv:2508.19124.

  Presenters

  • Christopher D Woodgate

    • University of Bristol

  Authors

  • Christopher D Woodgate

    • University of Bristol

  • Adam M Fisher

    • University of Warwick

  • Vincent G Fletcher

    • University of Warwick

  • Xiaoyu Zhang

    • Northeastern University

  • George C Hadjipanayis

    • Northeastern University

  • Laura H Lewis

    • Northeastern University

  • Julie B Staunton

    • University of Warwick
    • Department of Physics, University of Warwick, Coventry, UK

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• Modeling Proton Transport in Platinum-based Fuel Cells using Machine-Learning Interatomic Potentials

  ORAL

  March 19, 2026, 9:00 AM – March 19, 2026, 9:12 AM

  Publication: https://doi.org/10.48550/arXiv.2505.01963

  Presenters

  • Sam Brown

    • New Mexico State University

  Authors

  • Sam Brown

    • New Mexico State University

  • Kameron Fazel

    • Rensselaer Polytechnic Institute

  • Jacob Clary

    • National Renewable Energy Laboratory

  • Pritom Bose

    • Rensselaer Polytechnic Institute

  • Amalie L Frischknecht

    • Sandia National Laboratories

  • Ravishankar Sundararaman

    • Rensselaer Polytechnic Institute

  • Derek W Vigil-Fowler

    • National Renewable Energy Laboratory (NREL)
    • National Renewable Energy Laboratory

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• Exploring phonon anharmonicity in harmonic materials with machine-learning based force-fields

  ORAL

  March 19, 2026, 9:12 AM – March 19, 2026, 9:24 AM

  Presenters

  • Martin Callsen

    • Academia Sinica

  Authors

  • Martin Callsen

    • Academia Sinica

  • Tai-Ting Lee

    • Academia Sinica

  • Mei-Yin Chou

    • Academia Sinica

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• On the Effect of Training Data on Machine Learning Phonon Dispersion

  ORAL

  March 19, 2026, 9:24 AM – March 19, 2026, 9:36 AM

  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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• Functional Dependence of Melting Behavior and Thermodynamic Properties of Silicon and their Application to Machine Learned Potentials

  ORAL

  March 19, 2026, 9:36 AM – March 19, 2026, 9:48 AM

  Publication: Sundberg, B.; Hamel, S.; Lordi, V.; Lindsey, R. "The High-Pressure Silicon Phase Diagram: Insights from Machine-Learning-Accelerated Density Functional Theory." Manuscript in preparation.

  Presenters

  • Thomas Sundberg

    • University of Michigan

  Authors

  • Thomas Sundberg

    • University of Michigan

  • Sebastien Hamel

    • Lawrence Livermore National Laboratory

  • Vincenzo Lordi

    • Lawrence Livermore National Laboratory

  • Rebecca K Lindsey

    • Lawrence Livermore National Laboratory
    • University of Michigan
    • University of Michigan, Ann Arbor

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• Machine Learning–Assisted Prediction of Anharmonicity-Corrected Vibrational Spectra

  ORAL

  March 19, 2026, 9:48 AM – March 19, 2026, 10:00 AM

  Presenters

  • Kushantha P Withanage

    • The University of Texas at El Paso

  Authors

  • Kushantha P Withanage

    • The University of Texas at El Paso

  • Jesus N Pedroza Montero

    • The University of Texas at El Paso

  • Fhokrul Fhokrul Islam

    • University of Texas at El Paso

  • Eric J Bylaska

    • PNNL/Chemical Physics Theory Team

  • Jenna A Bilbrey

    • PNNL
    • Pacific Northwest National Laboratory (PNNL)

  • Koblar A Jackson

    • Central Michigan University
    • Department of Physics, Central Michigan University, Mount Pleasant, Michigan 48859, USA

  • Mark R Pederson

    • University of Texas at El Paso

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• Machine-Learning-Based Study of Ionic Diffusion and Lattice Dynamics in K₂Se₂Te and Related K-Based Superionic Materials

  ORAL

  March 19, 2026, 10:00 AM – March 19, 2026, 10:12 AM

  Presenters

  • Hao-Jen You

    • Academia Sinica

  Authors

  • Hao-Jen You

    • Academia Sinica

  • Yi-Ting Chiang

    • Academia Sinica

  • Hsin Lin

    • Academia Sinica

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• Predicting Gas Loading Response in All-Silica MFI Zeolites Using ChIMES Machine-Learned Interatomic Potentials

  ORAL

  March 19, 2026, 10:12 AM – March 19, 2026, 10:24 AM

  Publication: Planned submission: Modeling Gas Adsorption and Framework Response in All-Silica MFI Zeolites with ChIMES Interatomic Potentials

  Presenters

  • Vallabh Vasudevan

    • University of Michigan

  Authors

  • Vallabh Vasudevan

    • University of Michigan

  • Sayed Ahmad Almohri

    • University of Michigan

  • Rebecca K Lindsey

    • Lawrence Livermore National Laboratory
    • University of Michigan
    • University of Michigan, Ann Arbor

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