High-throughput computational screening for solid-state Li-ion conductors

We present a computational screening of experimental structural repositories for fast Li-ion conductors, with the goal of finding new candidate materials for application as solid-state electrolytes in next-generation batteries. We start from ~1400 unique Li-containing materials, of which ~900 are insulators at the level of density-functional theory. For those, we calculate the diffusion coefficient in a highly automated fashion, using extensive molecular dynamics simulations on a potential energy surface (the recently published pinball model) fitted on first-principles forces. The ~130 most promising candidates are studied with full first-principles molecular dynamics, first at high temperature and then more extensively for the 78 most promising candidates. The results of the first-principles simulations of the candidate solid-state electrolytes found are discussed in detail.

本研究针对实验结构数据库开展快锂离子导体的计算筛选，旨在发掘可应用于下一代电池固态电解质的新型候选材料。本研究初始数据集包含约1400种独特的含锂材料，其中约900种在密度泛函理论（Density-Functional Theory, DFT）框架下表现为绝缘体。针对上述绝缘体材料，我们采用基于第一性原理作用力拟合得到的势能面——即近期发布的弹球模型（pinball model）——开展大规模分子动力学模拟，以高度自动化的流程计算其锂离子扩散系数。我们对其中约130种最具潜力的候选材料开展全第一性原理分子动力学模拟：首先在高温条件下进行初步测试，随后针对其中78种最优候选材料展开更为全面的模拟研究。本研究将对筛选得到的候选固态电解质的第一性原理模拟结果进行详细讨论。