电解质
溶剂化
氢氟酸
化学
六氟磷酸盐
降级(电信)
锂(药物)
分子动力学
离子液体
极地的
杂质
溶剂
无机化学
计算化学
有机化学
物理化学
计算机科学
物理
电信
天文
医学
电极
内分泌学
催化作用
作者
Da Zhu,Li Sheng,Taiping Hu,Sian Chen,Mengchao Shi,Haiming Hua,Kai Yang,Jianlong Wang,Yaping Tang,Xiangming He,Hong Xu
标识
DOI:10.1021/acs.jpclett.4c00575
摘要
The nonaqueous electrolyte based on lithium hexafluorophosphate (LiPF6) is the dominant liquid electrolyte in lithium-ion batteries (LIBs). However, trace protic impurities, including H3O+, alcohols, and hydrofluoric acid (HF), can trigger a series of side reactions that lead to rapid capacity fading in high energy density LIBs. It is worth noting that this degradation process is highly dependent on the polarity of the solvents. In this work, a deep potential (DP) model is trained with a certain commercial electrolyte formula through a machine learning method. H3O+ is anchored with polar solvents, making it difficult to approach the PF6–, and suppressing the degradation process quickly at room temperature. Control experiments and simulations at different temperatures or concentrations are also performed to verify it. This work proposes a precise model to describe the solvation structure quantitatively and offers a new perspective on the degradation mechanism of PF6– in polar solvents.
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