Bulletin of the American Physical Society
APS March Meeting 2022
Volume 67, Number 3
Monday–Friday, March 14–18, 2022; Chicago
Session N49: Emerging Trends in Molecular Dynamics Simulations and Machine Learning III
11:30 AM–2:18 PM,
Wednesday, March 16, 2022
Room: McCormick Place W-471B
Sponsoring
Units:
DCOMP GDS DSOFT DPOLY
Chair: Aravind Krishnamoorthy, University of Southern California
Abstract: N49.00002 : Molecular Dynamics Simulations of Solid Electrolytes with NequIP Equivariant Machine Learning Models
12:06 PM–12:18 PM
Withdrawn
Presenter:
Juan F Gomez
(Harvard University)
Authors:
Juan F Gomez
(Harvard University)
Liwen Wan
(Lawrence Livermore National Lab)
Simon L Batzner
(Harvard University)
Albert Musaelian
(Harvard University)
Brandon Wood
(Lawrence Berkeley National Laboratory)
Boris Kozinsky
(Harvard University)
Collaborations:
MIR at SEAS, Quantum Simulations Group at Lawrence Livermore National Lab
In this work, we examine the applicability of machine-learned interatomic potentials to studying ionic diffusion dynamics in bulk and interfaces. We make use of a state of the art equivariant graph neural network (NequIP) model to learn the interatomic interactions for the garnet (Li7La3Zr2O12) LLZO solid electrolyte with internal grain boundaries and the interface between LLZO and LiCoO2 (LCO) cathode. The training data is composed of energies and forces derived from ab-initio molecular dynamics (AIMD).
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