Experimental Validation of a Computational Screening Approach to Predict Redox Potentials for a Diverse Variety of Redox-Active Organic Molecules

Organic redox flow batteries are currently the focus of intense scientific interest because they have the potential to be developed into low-cost, environmentally sustainable solutions to the energy storage problem that stands in the way of widespread uptake of renewable power generation technologies. Because the search space of suitable redox-active electrolytes is large, computational screening is increasingly being employed as a tool to identify promising candidates. It is well known in the computational chemistry literature that redox potentials for organic molecules can be accurately calculated on a class-by-class basis, but the general utility and accuracy of the relatively low-cost quantum chemical methods used in high-throughput screening are currently unclear. In this work, we measure the redox potentials of 24 commonly available but chemically diverse redox-active organic molecules in acetonitrile, carefully controlling experimental errors by using an internal reference (a ferrocene/ferrocenium redox couple), and compare these with redox potentials computed at B3LYP/6–31+G­(d,p) using a polarizable continuum model to account for solvation. Unlike previous large-scale computational screening studies, this work carefully establishes the accuracy of the computational procedure by benchmarking against experimental results. While previous small-scale computational studies have been carried out on structurally homologous compounds, this work assesses the accuracy of the computational model across a variety of compound classes, without applying class-dependent empirical corrections. We find that redox potential differences for coupled one-electron transfer processes can be computed to within 0.4 V and two-electron redox potential differences can usually be computed to within 0.15 V.