Abstract
Aqueous soluble organic (ASO) redox-active materials have recently shown great promise as alternatives to transition metal ions to be employed as energy-bearing active materials in redox flow batteries for large-scale energy storage because of their structural tunability, cost-effectiveness, availability, and safety features. Development so far however has been limited to a small palette of organics that are aqueous soluble. How to quickly identify and design organic molecules for the targeted properties became a critical challenge in accelerating the aqueous organic flow battery development.In this presentation, a data-driven material design process is discussed. This process incorporates database building, machine learning modeling for properties prediction, and the subsequent material synthesis and testing. Examples including Fluorenone and Phenizane derivative development for the flow battery application will be discussed.
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