材料科学
锂(药物)
阳极
石墨
剥离(纤维)
沉积(地质)
锂离子电池
离子
电池(电)
化学工程
纳米技术
电极
冶金
热力学
复合材料
有机化学
物理化学
物理
化学
功率(物理)
医学
古生物学
工程类
沉积物
生物
内分泌学
作者
Xudong Duan,Binqi Li,Jiani Li,Xiang Gao,Li Wang,Jun Xu
标识
DOI:10.1002/aenm.202203767
摘要
Abstract Metallic Lithium deposited on graphite particles is the major phenomenon responsible for the degradation of cell capacity, triggering of internal short circuit (ISC), and exacerbating thermal runaway (TR) in lithium‐ion batteries (LIBs). However, currently, no available physics‐based model can provide an accurate quantitative description of lithium‐plating behavior. Herein, this work establishes a mechanism model to characterize the Li deposition‐stripping process, especially the formation of dead Li and the reversibility of deposited Li. By the combination of the battery model and 3D particle model with the Li deposition‐stripping model, this work enables the quantitative prediction of Li deposition during charging–discharging cycles at various charging rates. Based on the revealed understanding of the Li deposition‐stripping process, a smart charging strategy with the optimization of the minimized Li‐deposition and expedited charging time is proposed. Furthermore, this work also quantifies the influence of anode heterogeneity on Li plating. The results highlight the promise of physics‐based mechanistic modeling for the quantification of the Li disposition‐stripping process and provide fundamental guidance on battery design and charging protocols for next‐generation long cycle life Li‐ion cells.
科研通智能强力驱动
Strongly Powered by AbleSci AI