Atomic insight into Li<sup>+</sup> ion transport in amorphous electrolytes Li<sub><i>x</i></sub>AlO<sub><i>y</i></sub>Cl<sub>3+<i>x</i>−2<i>y</i></sub> (0.5 ≤ <i>x</i> ≤ 1.5, 0.25 ≤ <i>y</i> ≤ 0.75)
We use ab initio molecular dynamics (AIMD) and machine learning interatomic potential based molecular dynamics (MLIP-based MD) simulations to explore the structure and ion transport characteristics of amorphous Li–Al–O–Cl solid-state electrolytes.
Authors
- Qifan Yang (ORCID: https://orcid.org/0000-0002-1688-3712)
- Ruijuan Xiao (ORCID: https://orcid.org/0000-0003-0930-9576)
- Jingchen Lian
- Feng Xu (ORCID: https://orcid.org/0000-0001-7727-0488)
- Hongmin Li (ORCID: https://orcid.org/0009-0009-7380-0029)
- Xiao Fu (ORCID: https://orcid.org/0000-0001-9005-6881)
- Xuhe Gong
- Liqi Wang
Institutions
- Chinese Academy of Sciences (CN)
- Institute of Physics (CN)
- University of Chinese Academy of Sciences (CN)
- Beihang University (CN)
Publication Details
- Journal
- Journal of Materials Chemistry A
- Published
- 2024-11-27
- DOI
- https://doi.org/10.1039/d4ta06234e
- Citations
- 3
- Primary Topic
- Advanced Battery Materials and Technologies
- Type
- article
- Field-Weighted Citation Impact
- 0.63
Funders
- National Natural Science Foundation of China
- Chinese Academy of Sciences
- Oak Ridge Institute for Science and Education