化学
电解质
电化学
锂(药物)
降级(电信)
溶解
阴极
亚稳态
分解
反应性(心理学)
化学工程
化学稳定性
化学分解
密度泛函理论
化学物理
工作(物理)
成核
理论(学习稳定性)
不稳定性
聚类分析
吸附
纳米技术
分子
作者
Jun Pan,Abdullah Bin Faheem,Bixian Zhong,Yifan Xu,Leonardo Cancellara,Pei Zhao,Evgeny Senokos,Okkyun Seo,Jian Yang,Dongshuang Wu,Haobo Li,Fuqiang Huang
摘要
Abstract Interfacial instability in electrochemical systems remains a fundamental challenge, particularly in high-nickel layered oxides where reactive surfaces drive parasitic chemistry even under near-equilibrium conditions. Here, we elucidate the chemical origins of storage-induced degradation in LiNi0.8Mn0.1Co0.1O2 cathodes, showing that electrolyte decomposition and interfacial Ni dissolution are correlated processes that govern capacity loss during storage. Building on this mechanistic insight, we develop a data-driven framework for engineering cathode–electrolyte interphases (CEIs) by integrating density functional theory with machine-learning interatomic potentials. This approach enables rapid evaluation of molecular descriptors for a diverse set of electrolyte additives. Unsupervised clustering highlights lithium bis(oxalato)borate (LiBOB) and lithium trifluoromethanesulfinate as effective CEI-forming additives. Experimental validation confirms that incorporating 0.05 M LiBOB significantly stabilizes the interface, improving capacity retention from 82% to 95.5% after 28 days of storage at 60 °C, with consistent behavior in a pouch cell. Furthermore, interfacial stability is assessed using distribution-of-relaxation-time analysis, providing a practical descriptor for evaluating CEI evolution. This work establishes a generalizable, data-driven strategy for understanding and controlling interfacial reactivity in metastable electrochemical systems.
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