电解质
碳酸乙烯酯
碳酸丙烯酯
分解
化学
阳极
化学分解
反应性(心理学)
密度泛函理论
锂(药物)
电池(电)
碳酸盐
化学工程
无机化学
化学物理
材料科学
物理化学
计算化学
热力学
电极
有机化学
物理
病理
功率(物理)
内分泌学
替代医学
工程类
医学
作者
Garvit Agarwal,Casey N. Brock,Karun K. Rao,Alexandr Fonari,Subodh Tiwari,J. L. Gavartin,H. Shaun Kwak,Karl Leswing,Mathew D. Halls
出处
期刊:Meeting abstracts
日期:2023-08-28
卷期号:MA2023-01 (7): 2889-2889
标识
DOI:10.1149/ma2023-0172889mtgabs
摘要
Solid electrolyte interphase (SEI) is a critical component of lithium ion batteries, yet is poorly characterized and not well understood. We use plane wave density functional theory simulations to perform a comprehensive study of the degradation reaction mechanisms of four electrolyte solvents and additives, ethylene carbonate (EC), propylene carbonate (PC), fluoroethylene carbonate (FEC), and vinylene carbonate (VC), at the Li (001) metal anode surface. The calculations provide fundamental insights into electrolyte decomposition and spontaneous SEI formation. Utilizing automated workflows implemented in the Schrödinger Materials Science Suite, we compute the adsorption energies and calculate the reaction energies for each decomposition pathway. Furthermore, we employ nudged elastic band calculations to compute the decomposition reaction barriers and provide mechanistic insights into the onset of SEI formation. We analyze trends in decomposition reaction energies and the relationships between the reaction energies and the activation barriers for the various electrolyte molecules as a function of applied bias potential. We find that the preferred decomposition pathways are different for the solvent molecules (EC and PC) than for the additives (FEC and VC). Calculations also suggest that applied bias reduces decomposition reaction barriers thus enhancing SEI formation. Such a comprehensive dataset of reaction energies and activation barriers provides useful benchmarks for the development and validation of reactive machine learned force fields for modeling advanced battery chemistries at a larger scale.
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