电解质
离子
化学物理
锂(药物)
化学
分子
电池(电)
离子电导率
离子键合
溶剂化
计算化学
物理化学
热力学
物理
有机化学
电极
医学
内分泌学
功率(物理)
作者
Chao Fang,Aashutosh Mistry,Venkat Srinivasan,Nitash P. Balsara,Rui Wang
出处
期刊:JACS Au
[American Chemical Society]
日期:2023-02-02
卷期号:3 (2): 306-315
被引量:19
标识
DOI:10.1021/jacsau.2c00590
摘要
The rate at which rechargeable batteries can be charged and discharged is governed by the selective transport of the working ions through the electrolyte. Conductivity, the parameter commonly used to characterize ion transport in electrolytes, reflects the mobility of both cations and anions. The transference number, a parameter introduced over a century ago, sheds light on the relative rates of cation and anion transport. This parameter is, not surprisingly, affected by cation–cation, anion–anion, and cation–anion correlations. In addition, it is affected by correlations between the ions and neutral solvent molecules. Computer simulations have the potential to provide insights into the nature of these correlations. We review the dominant theoretical approaches used to predict the transference number from simulations by using a model univalent lithium electrolyte. In electrolytes of low concentration, one can obtain a quantitative model by assuming that the solution is made up of discrete ion-containing clusters–neutral ion pairs, negatively and positively charged triplets, neutral quadruplets, and so on. These clusters can be identified in simulations using simple algorithms, provided their lifetimes are sufficiently long. In concentrated electrolytes, more clusters are short-lived and more rigorous approaches that account for all correlations are necessary to quantify transference. Elucidating the molecular origin of the transference number in this limit remains an unmet challenge.
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