Accurate Ionic Conductivity Calculations of Battery Electrolytes at High Salt Concentration Using Molecular Dynamics Simulations

Abstract

The ionic conductivity of an electrolyte formulation is a crucial property influencing battery performance. The dependence of ionic conductivity on multiple parameters, such as salt and solvent type, concentration, and temperature complicates the design of next-generation electrolytes. Efficient design of superior electrolytes requires methods capable of accurately and rapidly predicting ionic conductivity. Such methods would enable high-throughput screening of electrolyte chemistries to establish structure-property relationships.The simple Nernst-Einstein approximation is widely used in the literature to estimate ionic conductivity of electrolytes using the measured self-diffusivity. However, the failure of this approximation for concentrated solutions due to stronger intermolecular interactions requires incorporating a rigorous concentrated solution theory, such as Maxwell-Stefan (MS) diffusivity. Here, we present a molecular dynamics (MD) simulation workflow for calculating the ionic conductivity of liquid electrolytes utilizing the ion-correlated MS diffusion approach. We explore the sensitivity of calculated ionic conductivity to various simulation parameters and various methods in the literature to guide a standardized simulation protocol. Through rigorous benchmarking across a diverse range of electrolyte systems, we validate the model's accuracy by directly comparing the calculated ionic conductivities against experiments and existing literature. This work is a significant step toward a more unified and comprehensive evaluation procedure for ionic conductivity, accelerating the development of advanced electrolytes for improved battery performance.