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Article

A Computational Protocol Combining DFT and Cheminformatics for Prediction of pH-Dependent Redox Potentials

Department of Energy Conversion and Storage, Technical University of Denmark, Anker Engelunds Vej 301, 2800 Kongens Lyngby, Denmark
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Author to whom correspondence should be addressed.
Academic Editor: James Gauld
Molecules 2021, 26(13), 3978; https://doi.org/10.3390/molecules26133978
Received: 7 June 2021 / Revised: 25 June 2021 / Accepted: 28 June 2021 / Published: 29 June 2021
Discovering new materials for energy storage requires reliable and efficient protocols for predicting key properties of unknown compounds. In the context of the search for new organic electrolytes for redox flow batteries, we present and validate a robust procedure to calculate the redox potentials of organic molecules at any pH value, using widely available quantum chemistry and cheminformatics methods. Using a consistent experimental data set for validation, we explore and compare a few different methods for calculating reaction free energies, the treatment of solvation, and the effect of pH on redox potentials. We find that the B3LYP hybrid functional with the COSMO solvation method, in conjunction with thermal contributions evaluated from BLYP gas-phase harmonic frequencies, yields a good prediction of pH = 0 redox potentials at a moderate computational cost. To predict how the potentials are affected by pH, we propose an improved version of the Alberty-Legendre transform that allows the construction of a more realistic Pourbaix diagram by taking into account how the protonation state changes with pH. View Full-Text
Keywords: redox flow batteries; high-throughput screening; computational protocol; redox potential prediction; quinones; solvation free energy redox flow batteries; high-throughput screening; computational protocol; redox potential prediction; quinones; solvation free energy
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MDPI and ACS Style

Fornari, R.P.; de Silva, P. A Computational Protocol Combining DFT and Cheminformatics for Prediction of pH-Dependent Redox Potentials. Molecules 2021, 26, 3978. https://doi.org/10.3390/molecules26133978

AMA Style

Fornari RP, de Silva P. A Computational Protocol Combining DFT and Cheminformatics for Prediction of pH-Dependent Redox Potentials. Molecules. 2021; 26(13):3978. https://doi.org/10.3390/molecules26133978

Chicago/Turabian Style

Fornari, Rocco P., and Piotr de Silva. 2021. "A Computational Protocol Combining DFT and Cheminformatics for Prediction of pH-Dependent Redox Potentials" Molecules 26, no. 13: 3978. https://doi.org/10.3390/molecules26133978

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