电解质
法拉第效率
轨道能级差
阳极
锂(药物)
金属锂
材料科学
数量结构-活动关系
金属
化学
无机化学
化学物理
化学工程
物理化学
有机化学
分子
立体化学
电极
内分泌学
工程类
医学
作者
Zheng Zhao,Xinyan Liu,Xue‐Qiang Zhang,Shu‐Yu Sun,Jialin Li,Yanan Wang,Nan Yao,Dongping Zhan,Wenjun Feng,Hong‐Jie Peng,Jiang‐Kui Hu,Jia‐Qi Huang,Qiang Zhang
出处
期刊:Angewandte Chemie
[Wiley]
日期:2025-05-21
卷期号:64 (30): e202507387-e202507387
被引量:10
标识
DOI:10.1002/anie.202507387
摘要
Abstract Coulombic efficiency (CE) is a quantifiable indicator for the reversibility of lithium metal anodes in high‐energy‐density batteries. However, the quantitative relationship between CE and electrolyte properties has yet to be established, impeding rational electrolyte design. Herein, an interpretable model for estimating CE based on data‐driven insights of electrolyte properties is proposed. Hydrogen‐bond acceptor basicity ( β ) and the energy level gap between the lowest unoccupied and the highest occupied molecular orbital (HOMO‐LUMO gap) of solvents are identified as the top two parameters impacting CE by machine learning. β and HOMO‐LUMO gap of solvents govern anode interphase chemistry. A regression model is further proposed to estimate the CE based on β and HOMO‐LUMO gap. Using the new solvent screened by above regression model, the lithium metal anode in the pouch cell with an energy density of 418 Wh kg −1 achieves the highest CE of 99.2%, which is much larger than previous CE ranging from 70%–98.5%. This work provides a reliable interpretable quantitative model for rational electrolyte design.
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