Qi Changlin, Zhou Yuwei, Yuan Xiaoze, Peng Qing, Yang Yong, Li Yongwang, Wen Xiaodong
State Key Laboratory of Coal Conversion, Institute of Coal Chemistry, Chinese Academy of Sciences, Taiyuan 030001, China.
University of Chinese Academy of Sciences, No. 19A Yuquan Road, Beijing 100049, China.
Materials (Basel). 2024 Apr 15;17(8):1810. doi: 10.3390/ma17081810.
The solid electrolyte LiGePS (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.
固体电解质LiGePS（LGPS）在全固态电池的发展中起着至关重要的作用，并且已经在实验和理论方面得到了广泛研究。固体电解质的性质，如热力学稳定性、电导率、带隙等，与其基态结构密切相关。然而，Ge/P的位点无序共占据以及锂离子的缺陷分数占据导致了大量可能的原子构型（结构）。目前，静电能准则在第一性原理计算中被广泛用于筛选有利的候选构型并降低计算成本。在本研究中，我们采用基于机器学习和主动学习的LAsou方法，并结合第一性原理计算，来高效预测文献中报道的LGPS最稳定构型。然后，我们使用从头算分子动力学研究了500 - 900 K温度范围内锂离子的扩散性质。结果表明，具有不同骨架和锂离子分布的原子构型对锂离子的扩散有显著影响。此外，结果还表明LAsou方法对于完善实验晶体结构、加速理论计算以及促进未来新型固体电解质材料的设计具有重要价值。
