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Benchmarking First-Principles Reaction Equilibrium Composition Prediction

The availability of thermochemical properties allows for the prediction of the equilibrium compositions of chemical reactions. The accurate prediction of these can be crucial for the design of new chemical synthesis routes. However, for new processes, these data are generally not completely availabl...

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Autores principales: Marques, Esteban A., De Gendt, Stefan, Pourtois, Geoffrey, van Setten, Michiel J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10179931/
https://www.ncbi.nlm.nih.gov/pubmed/37175062
http://dx.doi.org/10.3390/molecules28093649
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author Marques, Esteban A.
De Gendt, Stefan
Pourtois, Geoffrey
van Setten, Michiel J.
author_facet Marques, Esteban A.
De Gendt, Stefan
Pourtois, Geoffrey
van Setten, Michiel J.
author_sort Marques, Esteban A.
collection PubMed
description The availability of thermochemical properties allows for the prediction of the equilibrium compositions of chemical reactions. The accurate prediction of these can be crucial for the design of new chemical synthesis routes. However, for new processes, these data are generally not completely available. A solution is the use of thermochemistry calculated from first-principles methods such as Density Functional Theory (DFT). Before this can be used reliably, it needs to be systematically benchmarked. Although various studies have examined the accuracy of DFT from an energetic point of view, few studies have considered its accuracy in predicting the temperature-dependent equilibrium composition. In this work, we collected 117 molecules for which experimental thermochemical data were available. From these, we constructed 2648 reactions. These experimentally constructed reactions were then benchmarked against DFT for 6 exchange–correlation functionals and 3 quality of basis sets. We show that, in reactions that do not show temperature dependence in the equilibrium composition below 1000 K, over 90% are predicted correctly. Temperature-dependent equilibrium compositions typically demonstrate correct qualitative behavior. Lastly, we show that the errors are equally caused by errors in the vibrational spectrum and the DFT electronic ground state energy.
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spelling pubmed-101799312023-05-13 Benchmarking First-Principles Reaction Equilibrium Composition Prediction Marques, Esteban A. De Gendt, Stefan Pourtois, Geoffrey van Setten, Michiel J. Molecules Article The availability of thermochemical properties allows for the prediction of the equilibrium compositions of chemical reactions. The accurate prediction of these can be crucial for the design of new chemical synthesis routes. However, for new processes, these data are generally not completely available. A solution is the use of thermochemistry calculated from first-principles methods such as Density Functional Theory (DFT). Before this can be used reliably, it needs to be systematically benchmarked. Although various studies have examined the accuracy of DFT from an energetic point of view, few studies have considered its accuracy in predicting the temperature-dependent equilibrium composition. In this work, we collected 117 molecules for which experimental thermochemical data were available. From these, we constructed 2648 reactions. These experimentally constructed reactions were then benchmarked against DFT for 6 exchange–correlation functionals and 3 quality of basis sets. We show that, in reactions that do not show temperature dependence in the equilibrium composition below 1000 K, over 90% are predicted correctly. Temperature-dependent equilibrium compositions typically demonstrate correct qualitative behavior. Lastly, we show that the errors are equally caused by errors in the vibrational spectrum and the DFT electronic ground state energy. MDPI 2023-04-22 /pmc/articles/PMC10179931/ /pubmed/37175062 http://dx.doi.org/10.3390/molecules28093649 Text en © 2023 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
Marques, Esteban A.
De Gendt, Stefan
Pourtois, Geoffrey
van Setten, Michiel J.
Benchmarking First-Principles Reaction Equilibrium Composition Prediction
title Benchmarking First-Principles Reaction Equilibrium Composition Prediction
title_full Benchmarking First-Principles Reaction Equilibrium Composition Prediction
title_fullStr Benchmarking First-Principles Reaction Equilibrium Composition Prediction
title_full_unstemmed Benchmarking First-Principles Reaction Equilibrium Composition Prediction
title_short Benchmarking First-Principles Reaction Equilibrium Composition Prediction
title_sort benchmarking first-principles reaction equilibrium composition prediction
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10179931/
https://www.ncbi.nlm.nih.gov/pubmed/37175062
http://dx.doi.org/10.3390/molecules28093649
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