Mistry Aashutosh, Yu Zhou, Peters Brandon L, Fang Chao, Wang Rui, Curtiss Larry A, Balsara Nitash P, Cheng Lei, Srinivasan Venkat
Chemical Sciences and Engineering, Argonne National Laboratory, Lemont, Illinois 60439, United States.
Joint Center for Energy Storage Research, Argonne National Laboratory, Lemont, Illinois 60439, United States.
ACS Cent Sci. 2022 Jul 27;8(7):880-890. doi: 10.1021/acscentsci.2c00348. Epub 2022 Jun 28.
Bottom-up understanding of transport describes how molecular changes alter species concentrations and electrolyte voltage drops in operating batteries. Such an understanding is essential to predictively design electrolytes for desired transport behavior. We herein advocate building a structure-property-performance relationship as a systematic approach to accurate bottom-up understanding. To ensure generalization across salt concentrations as well as different electrolyte types and cell configurations, the property-performance relation must be described using Newman's concentrated solution theory. It uses Stefan-Maxwell diffusivity, , to describe the role of molecular motions at the continuum scale. The key challenge is to connect to the structure. We discuss existing methods for making such a connection, their peculiarities, and future directions to advance our understanding of electrolyte transport.
自下而上的传输理解描述了分子变化如何改变工作电池中的物种浓度和电解质电压降。这种理解对于预测性地设计具有所需传输行为的电解质至关重要。我们在此提倡建立结构-性质-性能关系，作为一种准确的自下而上理解的系统方法。为确保在不同盐浓度、不同电解质类型和电池配置之间具有通用性，必须使用纽曼浓溶液理论来描述性质-性能关系。它使用斯特凡-麦克斯韦扩散系数 来描述连续尺度上分子运动的作用。关键挑战在于将 与结构联系起来。我们讨论了进行这种联系的现有方法、它们的特点以及推进我们对电解质传输理解的未来方向。
