电解质
离子
扩散
化学物理
快离子导体
离子电导率
离子键合
材料科学
锂(药物)
原子扩散
从头算
化学
热力学
物理化学
结晶学
物理
电极
医学
内分泌学
有机化学
作者
Changlin Qi,Yuwei Zhou,Xiaoze Yuan,Qing Peng,Yong Yang,Yongwang Li,Xiaodong Wen
出处
期刊:Materials
[Multidisciplinary Digital Publishing Institute]
日期:2024-04-15
卷期号:17 (8): 1810-1810
被引量:1
摘要
The solid electrolyte Li10GeP2S12 (LGPS) plays a crucial role in the development of all-solid-state batteries and has been widely studied both experimentally and theoretically. The properties of solid electrolytes, such as thermodynamic stability, conductivity, band gap, and more, are closely related to their ground-state structures. However, the presence of site-disordered co-occupancy of Ge/P and defective fractional occupancy of lithium ions results in an exceptionally large number of possible atomic configurations (structures). Currently, the electrostatic energy criterion is widely used to screen favorable candidates and reduce computational costs in first-principles calculations. In this study, we employ the machine learning- and active-learning-based LAsou method, in combination with first-principles calculations, to efficiently predict the most stable configuration of LGPS as reported in the literature. Then, we investigate the diffusion properties of Li ions within the temperature range of 500–900 K using ab initio molecular dynamics. The results demonstrate that the atomic configurations with different skeletons and Li ion distributions significantly affect the Li ions’ diffusion. Moreover, the results also suggest that the LAsou method is valuable for refining experimental crystal structures, accelerating theoretical calculations, and facilitating the design of new solid electrolyte materials in the future.
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