Collaborative Research: DMREF: High-Throughput Screening of Electrolytes for the Next Generation of Rechargeable Batteries

This research project aims to uncover the intricate relationships between liquid electrolytes and battery performance, which is crucial for developing next-generation rechargeable batteries. By systematically varying the composition and concentration of electrolytes, the team will identify optimal solutions. This project aligns seamlessly with the Materials Genome Initiative, using high-throughput advanced characterization, computational simulations, and machine learning data-driven analysis to understand fundamental interactions of electrolytes. With a focus on the long-term goal of developing high-performance, safe, and sustainable energy storage solutions, this project holds tremendous potential. Beyond technological advancements, the research outcomes will contribute to STEM education and public awareness about energy storage, fostering a brighter and greener future for all. The fundamental interactions in the electrolyte directly determine the solvation structures, kinetics, and battery performance of the bulk electrolytes. Understanding the complex interactions and their correlation with electrolyte performance is significant for exploring their working mechanisms and realizing the rational design of battery electrolytes. The proposal aims to (1) gain a good understanding of the solvation structure through high-throughput multimodal characterization methods; (2) correlate the structure-property relationship by studying transport properties through high-throughput computational screening studies; (3) a machine learning-based data analysis platform will be created to predict and identify battery properties by analyzing high-throughput structural and simulation data. This project is supported by the Division of Materials Research and the Chemical, Biological, Environmental Engineering and Transport Systems Division. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.