电解质
图表
电化学
溶剂
分子间力
盐(化学)
材料科学
化学物理
化学
电极
物理化学
数学
统计
有机化学
分子
作者
Renzhi Huang,Xin Guo,Binbin Chen,Mengying Ma,Qinlong Chen,Canfu Zhang,Yingchun Liu,Xueqian Kong,Xiulin Fan,Linjun Wang,Min Ling,Huilin Pan
出处
期刊:JACS Au
[American Chemical Society]
日期:2024-05-03
卷期号:4 (5): 1986-1996
被引量:1
标识
DOI:10.1021/jacsau.4c00196
摘要
Developing advanced electrolytes has been regarded as a pivotal strategy for enhancing the electrochemical performance of batteries; however, the criteria for electrolyte design remain elusive. In this study, we present an electrolyte design chart reframed through intermolecular interactions. By combining systematic nuclear magnetic resonance, Fourier transform infrared measurements, molecular dynamics (MD) simulations, and machine-learning-assisted classifications, we establish semiquantitative correlations between electrolyte components and the electrochemical reversibility of electrolytes. We propose the equivalent increment of Li salt resulting from functional cosolvent and solvent–solvent interactions for effective electrolyte design and prediction. The controllable regulation of the electrolyte design chart by the properties of solvent–solvent interactions presents varying equivalent effects of increasing Li salt concentrations in different electrolyte systems. Based on this mechanism, we demonstrate highly reversible and nonflammable phosphate-based electrolytes for graphite||NCM811 full cells. The proposed electrolyte design chart, semiquantitatively determined by intermolecular interactions, provides the necessary experimental foundation and basis for the future rapid screening and prediction of electrolytes using machine-learning methods.
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