A Data-Driven Platform for Automated Characterization of Polymer Electrolytes

Lithium-ion batteries aid in decarbonization through enabling electric vehicles and renewable energy generation, but these applications put increasing demands on the energy density, safety, and cost of the batteries. Polymer electrolytes could improve battery safety but currently do not have sufficient ionic conductivity for ambient operation. To address this challenge, we developed a high throughput platform to increase the speed and scale of polymer electrolyte research by an estimated 100X. We utilized automated formulation and characterization operations, including electrochemical impedance spectroscopy with in situ thickness measurements, to perform a comparison of lithium and sodium salts in poly(ethylene oxide). Our study provides a high-quality, unified reference dataset for the community, and greatly expands available data for sodium-based electrolytes. Secondly, our large dataset allows us to find that the local minima in glass transition temperature that corresponds to maximum ionic conductivity is a colligative property, independent of either anion or cation chemistry.