Department of Chemistry, The University of Hong Kong, Pokfulam Road, Hong Kong SAR 999077, China.
Hong Kong Quantum AI Lab Limited, Hong Kong SAR 999077, China.
J Chem Theory Comput. 2023 Mar 14;19(5):1381-1387. doi: 10.1021/acs.jctc.2c01115. Epub 2023 Feb 22.
All-solid-state lithium-ion batteries have been a promising solution for next-generation energy storage due to their safety and potentially high energy density. In this work, we developed a density-functional tight-binding (DFTB) parameter set for modeling solid-state lithium batteries, focusing on the band alignment at electrolyte/electrode interfaces. Despite DFTB being widely applied in the simulation of large-scale systems, parametrization is usually done for single materials, and less attention is paid to band alignment among multiple materials. Band offsets at the electrolyte/electrode interfaces are key quantities determining the performance. Here, an automated global optimization method based on DFTB confinement potentials of all elements is developed, while the band offsets between electrodes and electrolytes are introduced as constraints during the optimization. The parameter set is applied to model an all-solid-state Li/LiPON/LiCoO battery, and its electronic structure shows a good agreement with that from density-functional theory (DFT) calculations.
全固态锂离子电池因其安全性和潜在的高能量密度而成为下一代储能的有前途的解决方案。在这项工作中,我们开发了一种用于模拟固态锂电池的密度泛函紧束缚(DFTB)参数集,重点是电解质/电极界面的能带对准。尽管 DFTB 广泛应用于大规模系统的模拟,但参数化通常是针对单一材料进行的,而对多种材料之间的能带对准关注较少。电解质/电极界面的能带偏移是决定性能的关键量。在这里,开发了一种基于 DFTB 所有元素限制势的自动全局优化方法,而在优化过程中,电极和电解质之间的能带偏移被引入作为约束条件。该参数集应用于模拟全固态 Li/LiPON/LiCoO 电池,其电子结构与密度泛函理论(DFT)计算结果吻合较好。