Mechanistic insights into superionic thioarsenate argyrodite solid electrolytes <i>via</i> machine learning interatomic potentials
Machine learning interatomic potentials reveal that optimal anion disorder boosts Li-ion conductivity beyond 20 mS cm −1 in thioarsenate argyrodite solid electrolytes.
Authors
- Joon Hyung Shim (ORCID: https://orcid.org/0000-0002-3995-1968)
- K.-H. Park
- Kwangnam Kim (ORCID: https://orcid.org/0000-0003-1149-1733)
- Yong‐Heum Lee (ORCID: https://orcid.org/0000-0002-1241-525X)
- Moon Hyung Jang (ORCID: https://orcid.org/0000-0001-5601-8021)
- Seung‐Ho Yu (ORCID: https://orcid.org/0000-0003-4833-3181)
Institutions
- Lawrence Livermore National Laboratory (US)
- Korea University (KR)
- Korea Institute of Science and Technology (KR)
- Korea University of Science and Technology (KR)
Publication Details
- Journal
- Journal of Materials Chemistry A
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1039/d5ta05538e
- Primary Topic
- Machine Learning in Materials Science
- Type
- article
- Field-Weighted Citation Impact
- 0.00