Comparison of Computational Chemistry Methods for the Discovery of Quinone-Based Electroactive Compounds for Energy Storage

High-throughput computational screening (HTCS) is an approach that can enable rational and time-efficient discovery of electroactive compounds. The effectiveness of HTCS is dependent on the accuracy and speed at which the performance descriptors can be estimated for possibly millions of candidate compounds. Here, a systematic evaluation of computational methods, including force field (FF), semi-empirical quantum mechanics (SEQM), density functional based tight binding (DFTB), and density functional theory (DFT), is performed on the basis of their accuracy in predicting the redox potentials of redox-active organic compounds. Geometry optimizations at lower level theories followed by single point energy (SPE) DFT calculations including an implicit solvation model are found to offer equipollent accuracy as the higher level DFT methods, albeit at significantly lower computational costs. Effects of implicit solvation on molecular geometries and SPEs, and their overall effects on the prediction accuracy of redox potentials are analyzed in view of computational cost versus prediction accuracy, which outlines the best choice of methods corresponding to a desired level of accuracy. The modular computational approach presented here is expected to be applicable for accelerating virtual studies on functional quinones and the respective discovery of candidate compounds for energy storage.