电解质
化学物理
扩散
离子
离子键合
阿累尼乌斯方程
锂(药物)
大气温度范围
化学
热力学
材料科学
物理化学
活化能
物理
有机化学
电极
医学
内分泌学
作者
Zhongheng Fu,Xiang Chen,Nan Yao,Xin Shen,Xia‐Xia Ma,Shuai Feng,Shuhao Wang,Rui Zhang,Linfeng Zhang,Qiang Zhang
标识
DOI:10.1016/j.jechem.2022.01.018
摘要
Solid-state batteries have received increasing attention in scientific and industrial communities, which benefits from the intrinsically safe solid electrolytes (SEs). Although much effort has been devoted to designing SEs with high ionic conductivities, it is extremely difficult to fully understand the ionic diffusion mechanisms in SEs through conventional experimental and theoretical methods. Herein, the temperature-dependent concerted diffusion mechanism of ions in SEs is explored through machine-learning molecular dynamics, taking Li10GeP2S12 as a prototype. Weaker diffusion anisotropy, more disordered Li distributions, and shorter residence time are observed at a higher temperature. Arrhenius-type temperature dependence is maintained within a wide temperature range, which is attributed to the linear temperature dependence of jump frequencies of various concerted diffusion modes. These results provide a theoretical framework to understand the ionic diffusion mechanisms in SEs and deepen the understanding of the chemical origin of temperature-dependent concerted diffusions in SEs.
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