AI-Assisted Self-Driving Experimentation for Energy Storage Materials Discovery and Development

Aqueous organic redox active materials have recently shown great promise as alternatives to transition metal ions as energy bearing active materials in redox flow batteries for large-scale energy storage due to their structural tunability, cost effectiveness, availability, and safety features. However, development to date has been limited to a small palette of aqueous soluble organics. This presentation will provide an overview of a data-driven approach to accelerate the discovery and development of aqueous organic redox-active molecules for flow batteries, including database curation, structure-property correlation, and automated property characterization and performance testing.

Reference: P. Gao, etc. “SOMAS: a platform for data-driven material discovery in redox flow battery development”, Scientific Data, 9, 740, 2022