High-Throughput Screening and Experimental Validation of Aqueous Organic Redox Flow Battery Electrolytes

Increasing renewables share in power mix has necessitated improvement and further research on various battery technologies. Aqueous organic redox flow batteries (AORFBs) exhibit many advantages, such as high ionic conductivity, safety, cost-effectiveness, and well-developed technology to compensate for the narrow voltage window that is limited by the electrolysis of water. For this purpose, discovery of novel organic electroactive molecules is highly warranted. Herein, we have developed a computational workflow that can screen millions of organic molecules in a modular fashion using similarity metrics with known electroactive molecules, machine learning based prediction of redox potential and solubility, and finally on the ease of availability and cost. Through this workflow we were able to narrow down to almost 60 molecules, among which some are already reported to have high performance in AORFBs, while some are completely new molecules for the redox flow battery application that are also experimentally validated through cyclic voltammetry experiments.