期刊
MATERIALS TODAY PHYSICS
卷 21, 期 -, 页码 -出版社
ELSEVIER
DOI: 10.1016/j.mtphys.2021.100463
关键词
Lithium superionic conductors; Machine learning interatomic potentials; PBE versus optB88 functionals; Non-Arrhenius behavior; Room temperature ionic conductivity
资金
- Nissan Motor Co., Ltd. [20202446]
- Nissan North AmericaInc. [20202446]
- US Department of Energy, Office of Science, Office of Basic Energy Sciences, Materials Sciences and Engineering Division [DE-AC02-05-CH11231]
- Extreme Science and Engineering Discovery Environment (XSEDE) [ACI-1548562]
This study presents a strategy using moment tensor potentials (MTP5) to improve the accuracy of predicting physical properties of lithium superionic conductors (LSCs), leading to more accurate predictions of ionic conductivities and activation energies. NPT MD simulations of three LSC5 revealed a transition between two quasi-linear Arrhenius regimes at relatively low temperatures, attributed to an increase in the number and diversity of diffusion pathways.
Lithium superionic conductors (LSCs) are of major importance as solid electrolytes for next-generation all-solid-state lithium-ion batteries. While ab initio molecular dynamics have been extensively applied to study these materials, there are often large discrepancies between predicted and experimentally measured ionic conductivities and activation energies due to the high temperatures and short time scales of such simulations. Here, we present a strategy to bridge this gap using moment tensor potentials (MTP5). We show that MTP5 trained on energies and forces computed using the van der Waals optB88 functional yield much more accurate lattice parameters, which in turn leads to accurate prediction of ionic conductivities and activation energies for the Li0.33La0.66TiO3, Li3YCl6 and Li7P3S11 LSC5. NPT MD simulations using the optB88 MTP5 also reveal that all three LSC5 undergo a transition between two quasi-linear Arrhenius regimes at relatively low temperatures. This transition can be traced to an increase in the number and diversity of diffusion pathways, in some cases with a change in the dimensionality of diffusion. This work presents not only an approach to develop high accuracy MTP5, but also outlines the diffusion characteristics for LSC5 which is otherwise inaccessible through ab initio computation. (C) 2021 Elsevier Ltd. All rights reserved.
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