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

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...

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Detalles Bibliográficos
Autores principales: Fornari, Rocco Peter, de Silva, Piotr
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8271517/
https://www.ncbi.nlm.nih.gov/pubmed/34209898
http://dx.doi.org/10.3390/molecules26133978
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author Fornari, Rocco Peter
de Silva, Piotr
author_facet Fornari, Rocco Peter
de Silva, Piotr
author_sort Fornari, Rocco Peter
collection PubMed
description 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.
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spelling pubmed-82715172021-07-11 A Computational Protocol Combining DFT and Cheminformatics for Prediction of pH-Dependent Redox Potentials Fornari, Rocco Peter de Silva, Piotr Molecules Article 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. MDPI 2021-06-29 /pmc/articles/PMC8271517/ /pubmed/34209898 http://dx.doi.org/10.3390/molecules26133978 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Fornari, Rocco Peter
de Silva, Piotr
A Computational Protocol Combining DFT and Cheminformatics for Prediction of pH-Dependent Redox Potentials
title A Computational Protocol Combining DFT and Cheminformatics for Prediction of pH-Dependent Redox Potentials
title_full A Computational Protocol Combining DFT and Cheminformatics for Prediction of pH-Dependent Redox Potentials
title_fullStr A Computational Protocol Combining DFT and Cheminformatics for Prediction of pH-Dependent Redox Potentials
title_full_unstemmed A Computational Protocol Combining DFT and Cheminformatics for Prediction of pH-Dependent Redox Potentials
title_short A Computational Protocol Combining DFT and Cheminformatics for Prediction of pH-Dependent Redox Potentials
title_sort computational protocol combining dft and cheminformatics for prediction of ph-dependent redox potentials
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8271517/
https://www.ncbi.nlm.nih.gov/pubmed/34209898
http://dx.doi.org/10.3390/molecules26133978
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