Computational Analysis of Ion Clustering Statistics in Liquid Battery Electrolytes

The transport properties of liquid battery electrolytes critically depend on molecular-level solvation structures of ions. In contrast to the dilute regime where the majority of counterions are sufficiently separated spatially, in global or localized high-concentrated electrolytes (HCEs) counterions tend to form superstructures such as contact-ion pairs (CIPs) or aggregates (AGGs). The presence and relative population of such superstructures can drastically change the ionic transport behavior in liquid electrolytes. We have developed a computer program [1] that can efficiently perform analysis of ion clustering statistics from molecular dynamics simulations, complementary to experimental measurements. We have successfully applied our method to various systems, including (1) a prototypical concentrated liquid electrolyte (Li:EC:DEC) [2], and (2) a series of newly developed high-entropy liquid electrolytes [3]. In both cases, we find consistent agreements between our prediction and experimentally measured nanostructures and solvation strengths. We envision that our method would be widely applicable to generic structurally disordered systems. [1] Cohen et al., Journal of Open Source Software 8 , 84 (2023) [2] Xie and Wang et al., Science Advances 9 , eadc9721 (2023) [3] Kim and Wang et al. Nature Energy 8 , 814–826 (2023)