Deep potential generation scheme and simulation protocol for the Li10GeP2S12-type superionic conductors

Huang, Jianxing; Zhang, Linfeng; Wang, Han; Zhao, Jinbao; Cheng, Jun; E, Weinan

doi:10.1063/5.0041849

Deep potential generation scheme and simulation protocol for the Li₁₀GeP₂S₁₂-type superionic conductors

Journal Article · Mon Mar 01 00:00:00 EST 2021 · Journal of Chemical Physics

DOI:https://doi.org/10.1063/5.0041849· OSTI ID:1853189

^[1]; ^[2]; ^[3]; Zhao, Jinbao ^[4]; ^[4]; E, Weinan ^[2]

Xiamen University (China); Xiamen Univ., Xiamen (China)
Princeton Univ., NJ (United States)
Institute of Applied Physics and Computational Mathematics, Beijing (China)
Xiamen University (China)

We report solid-state electrolyte materials with superior lithium ionic conductivities are vital to the next-generation Li-ion batteries. Molecular dynamics could provide atomic scale information to understand the diffusion process of Li-ion in these superionic conductor materials. Here, we implement the deep potential generator to set up an efficient protocol to automatically generate interatomic potentials for Li₁₀GeP₂S₁₂-type solid-state electrolyte materials (Li₁₀GeP₂S₁₂, Li₁₀SiP₂S₁₂, and Li₁₀SnP₂S₁₂). The reliability and accuracy of the fast interatomic potentials are validated. With the potentials, we extend the simulation of the diffusion process to a wide temperature range (300 K–1000 K) and systems with large size (~1000 atoms). Important technical aspects such as the statistical error and size effect are carefully investigated, and benchmark tests including the effect of density functional, thermal expansion, and configurational disorder are performed. The computed data that consider these factors agree well with the experimental results, and we find that the three structures show different behaviors with respect to configurational disorder. Our work paves the way for further research on computation screening of solid-state electrolyte materials.

View Accepted Manuscript (DOE)

Research Organization:: Princeton Univ., NJ (United States)

Sponsoring Organization:: Beijing Academy of Artificial Intelligence (BAAI); National Key Research and Development Program of China; National Natural Science Foundation of China; National Science Foundation of China; Office of Naval Research; USDOE Office of Science (SC)

Grant/Contract Number:: SC0019394

OSTI ID:: 1853189

Journal Information:: Journal of Chemical Physics, Journal Name: Journal of Chemical Physics Journal Issue: 9 Vol. 154; ISSN 0021-9606

Publisher:: American Institute of Physics (AIP)Copyright Statement

Country of Publication:: United States

Language:: English

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Deep potential generation scheme and simulation protocol for the Li10GeP2S12-type superionic conductors

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Deep potential generation scheme and simulation protocol for the Li₁₀GeP₂S₁₂-type superionic conductors