A Quantitative Evaluation of Computational Methods to Accelerate the Study of Alloxazine-Derived Electroactive Compounds for Energy Storage

09 September 2020, Version 1
This content is a preprint and has not undergone peer review at the time of posting.


Alloxazines are a promising class of organic electroactive molecules for application in aqueous redox flow batteries. Preliminary studies show that structural modifications of alloxazines with electron-donating and/or -withdrawing functional groups help in tuning of their redox properties. High-throughput computational screening enables rational and time-efficient discovery of functional compounds. The effectiveness of high-throughput computational screening efforts is strongly dependent on the accuracy and speed at which the performance descriptors are estimated for a large pool of candidate compounds. Here, we performed a quantitative study to assess the performance of computational methods, including the forcefield based molecular mechanics, semi-empirical quantum mechanics, density functional based tight binding, and density functional theory, on the basis of their accuracy and computational cost in predicting the redox potentials of electroactive alloxazines. We compared the performances of various energy-based descriptors, including the redox reaction energy and the frontier orbital energies of the reactant and product molecules. We found that the lowest unoccupied molecular orbital energy of the reactant molecules is the best performing descriptor for the alloxazines, which is in contrast to other classes of molecules, such as quinones that we reported earlier. Importantly, we present a flexible in silico approach to accelerate both the singly and the high-throughput computational screening studies, therewithal considering the level of accuracy vs measured electrochemical data, that is principally applicable for the discovery of efficient, alloxazine-derived organic compounds for energy storage in aqueous redox flow batteries.


Computational Chemistry
High-throughput Virtual Screening
Redox Flow Batteries
Energy Storage Materials

Supplementary materials

20200908 SupportingInformation


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