Abstract
Quinones are one of the most promising and widely investigated classes of redox active materials for organic aqueous redox flow batteries. However, quinone-based flow batteries still lack the necessary performance in terms of metrics, such as specific capacity, power density, and long-term stability, to achieve mass market adoption. These performance metrics are directly related to the physicochemical properties of the quinone molecules, including their equilibrium redox potential, aqueous solubility, and chemical stability. Given the enormous chemical and configurational space of possible quinones and the high tunability of their properties, there has been a recent surge in the use of high-throughput virtual screening (HTVS) for the rational design and discovery of new high-performing molecules. In this review article, HTVS efforts for the computational design and discovery of quinones are reviewed with a special focus on the enumerated space of core quinone motif, the methods and approximations used for the estimation of performance descriptors, and the emergent structure-property relationships. The knowledge and methodological gaps in conventional HTVS efforts are discussed, and strategies for improvement are suggested.
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