Cohort: 3

Members: Qichao Hu (Executive Sponsor), Kang Xu, Yumin Zhang, Dan Hannah, Adam Atanas, Bokyung (Olivia) Kim 

Problem: Developing better batteries for electric vehicles and energy storage remains slow and expensive because scientists must navigate vast chemical design spaces while relying on fragmented research data and time-intensive laboratory testing. Traditional approaches explore only a small fraction of possible materials, limiting progress in improving performance, safety, charging speed, and lifespan. 

Approach: The company has developed an AI-driven materials discovery platform that integrates scientific literature, molecular simulations, laboratory data, and autonomous experimentation into a unified system. The platform uses AI agents and chemistry-focused models to search through hundreds of millions of molecules, predict properties, recommend promising battery materials, and continuously improve through feedback from automated lab testing and human experts. 

Result: Reduced electrolyte discovery timelines from approximately two years to three months and cut physical experimentation by up to 70%, helping accelerate R&D efficiency, reduce costs, and speed up the development of safer energy storage systems.