Predicting Electrolyte Conductivity Directly from Molecular-Level Interactions

Ionic conductivity is a fundamental property to evaluate an electrolyte blend’s per- formance. Though it is a macroscopic quantity, ionic conductivity is derived from molecular interactions including the stoichiometry and relative population of ion solvation clusters. There is growing interest in constructing low-cost, high-throughput electrolyte design frameworks that can evaluate the properties of novel electrolyte blends in silico. A framework that can accurately predict ionic conductivity without empirical fitting would therefore be transformative. This study outlines such an approach built on a chemical physics formalism with parameters computed by classical molecular dynamic (MD) simulations. Quantitative and qualitative agreements are achieved for strong and weak electrolytes, respectively. This work provides the basis for conductivity predictions for novel battery electrolyte systems, facilitating in silico screening before synthesis.