Understanding interfacial evolution in solid-state batteries using machine learning force fields
POSTER
Abstract
* This work was performed under the auspices of the U.S. Department of Energy by Lawrence Livermore National Laboratory under contract number DEAC52-07NA27344. Authors acknowledge funding support from the Vehicle Technologies Office, Office of Energy Efficiency and Renewable Energy, U.S. Department of Energy and computational resource support from the Innovative and Novel Computational Impact on Theory and Experiment (INCITE) program.
Presenters
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Kwangnam Kim
Lawrence Livermore National Laboratory
Authors
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Kwangnam Kim
Lawrence Livermore National Laboratory
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Suyue Yuan
Lawrence Livermore National Laboratory
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Aniruddha M Dive
Lawrence Livermore National Laboratory
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Andrew Grieder
University of California, Santa Cruz
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Nicole Adelstein
San Francisco State University
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ShinYoung Kang
Lawrence Livermore Natl Lab
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Brandon Wood
Lawrence Livermore National Laboratory
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Liwen Wan
Lawrence Livermore National Laboratory