Sarah Allec¹, Woochul Shin², P. Alex Greaney¹, Xiulei Ji²; ¹University of California Riverside, ²Oregon State University

While aqueous batteries offer a lowered risk of danger over conventional metal ion batteries, they still face many limitations (e.g., low electrochemical stability window, short battery cycle life) which have prevented them from transforming industry. However, the recent discovery of water-in-salt electrolytes (WiSEs) has renewed interest in their potential, particularly for Zn-ion batteries, by widening the electrochemical stability window and by alleviating the irreversibility issue of Zn anode materials. Nonetheless, optimization of a WiSE for aqueous batteries requires a mechanistic understanding of why a highly concentrated electrolyte provides favorable Zn plating/stripping. Here, we provide such an understanding via the development of a neural network potential (NNP) based on data from ab initio molecular dynamics (AIMD) simulations in order to uncover the structure-property relationships of relevant WiSEs. Armed with these relationships, we hope to guide and accelerate the development of WiSEs for aqueous batteries.