文献类型：期刊文献

英文题名：Quantification and modeling framework of mechanical-electrochemical degradation in Ni-Rich layered cathode

作者：Yao, Zhiheng[1];Chen, Ying[1];Luan, Weiling[1];Chen, Haofeng[1]

机构：[1]East China Univ Sci & Technol, Sch Mech & Power Engn, Key Lab Adv Battery Syst & Safety CPCIF, Shanghai 200237, Peoples R China

年份：2025

卷号：540

外文期刊名：ELECTROCHIMICA ACTA

收录：;EI(收录号：20253419025592);WOS:【SCI-EXPANDED(收录号:WOS:001642391100001)】；

基金：The authors gratefully acknowledge the support from the National Natural Science Foundation of China (52375144 and 52205153), Shanghai Pujiang Programme (23PJD019) during the course of this work.

语种：英文

外文关键词：Lithium-ion battery; Ni-rich cathode; Crack; Mechanical degradation; Machine learning

摘要：With the growing demand for high-energy density lithium-ion batteries (LIBs) in electric transportation, nickelrich layered oxide materials (NRLOs) have emerged as promising cathode candidate. Among these materials, LiNixCoyMn1- x-yO2 (NCM) delivers high energy density, effectively addressing range anxiety. However, fast charging and extended cycling exacerbate the mechanical degradation of cathode materials, leading to performance loss and reduced lifespan. Accurate quantification of mechanical degradation and its effect on battery performance is critical for optimizing lithium-ion batteries. This study systematically investigates the evolution of mechanical degradation in LiNi0.8Co0.1Mn0.1O2 (NCM811) cathode materials. A quantitative framework is developed that integrates high-resolution crack characterization, machine-learning assisted image analysis and a damage prediction model to establish the relationship between microstructural evolution and electrochemical performance. Crack characteristics, including density, width, length, and perimeter, are quantitatively analyzed under varied cycling conditions. Among these features, crack density is adopted as the primary degradation metric in a modified fatigue model. This model accurately captures damage evolution and spatially maps damage propagation from particle core to surface at higher C-rates. The established framework provides an interpretable and scalable pathway to link microstructural evolution to electrochemical performance, offering valuable insights for optimizing cathode design and predicting battery life.