Conductivity experiments for electrolyte formulations and their automated analysis

Electrolytes are considered crucial for the performance of batteries, and therefore indispensable forfuture energy storage research. This paper presents data that describes the effect of the electrolytecomposition on the ionic conductivity. In particular, the data focuses on electrolytes composed ofethylene carbonate (EC), propylene carbonate (PC), ethyl methyl carbonate (EMC), and lithiumhexafluorophosphate (LiPF6). The mass ratio of EC to PC was varied, while keeping the mass ratio of(EC + PC) and EMC at fixed values of 3:7 and 1:1. The conducting salt concentration was also variedduring the study. Conductivity data was obtained from electrochemical impedance spectroscopy (EIS)measurements at various temperatures. Based on the thus obtained temperature series, the activationenergy for ionic conduction was determined during the analysis. The data is presented here in amachine-readable format and includes a Python package for analyzing temperature series of electrolyteconductivity according to the Arrhenius equation and EIS data. The data may be useful e.g. for thetraining of machine learning models or for reference prior to experiments.