Fang Chao, Mistry Aashutosh, Srinivasan Venkat, Balsara Nitash P, Wang Rui
Materials Sciences Division, Lawrence Berkeley National Laboratory, Berkeley, California94720, United States.
Department of Chemical and Biomolecular Engineering, University of California, Berkeley, California94720, United States.
JACS Au. 2023 Feb 2;3(2):306-315. doi: 10.1021/jacsau.2c00590. eCollection 2023 Feb 27.
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.
可充电电池的充放电速率由工作离子在电解质中的选择性传输所决定。电导率是常用于表征电解质中离子传输的参数，反映了阳离子和阴离子的迁移率。迁移数是一个多世纪前引入的参数，它揭示了阳离子和阴离子传输的相对速率。不出所料，这个参数受到阳离子 - 阳离子、阴离子 - 阴离子以及阳离子 - 阴离子相关性的影响。此外，它还受到离子与中性溶剂分子之间相关性的影响。计算机模拟有潜力深入了解这些相关性的本质。我们通过使用一种单价锂电解质模型，回顾了用于从模拟中预测迁移数的主要理论方法。在低浓度电解质中，通过假设溶液由离散的含离子簇（中性离子对、带负电和正电的三重态、中性四重态等）组成，可以得到一个定量模型。只要这些簇的寿命足够长，就可以使用简单算法在模拟中识别它们。在浓电解质中，更多的簇寿命较短，需要更严格的方法来考虑所有相关性以量化迁移数。在这个极限下阐明迁移数的分子起源仍然是一个未解决的挑战。
