Battery electrolytes aren’t just one chemical, but a complex mixture of salts, solvents, and additives interacting and reacting with each other. Artificial intelligence has made great headway in helping select ideal materials to go into that chemical soup. But a team from the University of Chicago Pritzker School of Molecular Engineering (UChicago PME) is using AI to generate the entire formulation, balancing the complicated tradeoffs and interactions that go into the electrolytes that make batteries possible.

The research is published in JACS Au. It is the next step in the Amanchukwu Lab’s ongoing development of an AI for battery work, ElectrolyteGPT.

“Next-generation battery electrolytes must meet multiple, often conflicting property requirements,” said first author Jaemin Kim. “With the model’s capability of generating outputs under diverse conditions, ElectrolyteGPT is able to generate novel candidates satisfying the desired properties simultaneously.”