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Linear Scaling Relationships to Predict pK(a)’s and Reduction Potentials for Bioinspired Hydrogenase Catalysis
[Image: see text] Biomimetic catalysts inspired by the active site of the [FeFe] hydrogenase enzyme can convert protons into molecular hydrogen. Minimizing the overpotential of the electrocatalytic process remains a major challenge for practical application of the catalyst. The catalytic cycle of th...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Chemical Society
2021
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8753599/ https://www.ncbi.nlm.nih.gov/pubmed/34955025 http://dx.doi.org/10.1021/acs.inorgchem.1c02429 |
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author | Puthenkalathil, Rakesh C. Ensing, Bernd |
author_facet | Puthenkalathil, Rakesh C. Ensing, Bernd |
author_sort | Puthenkalathil, Rakesh C. |
collection | PubMed |
description | [Image: see text] Biomimetic catalysts inspired by the active site of the [FeFe] hydrogenase enzyme can convert protons into molecular hydrogen. Minimizing the overpotential of the electrocatalytic process remains a major challenge for practical application of the catalyst. The catalytic cycle of the hydrogen production follows an ECEC mechanism (E represents an electron transfer step, and C refers to a chemical step), in which the electron and proton transfer steps can be either sequential or coupled (PCET). In this study, we have calculated the pK(a)’s and the reduction potentials for a series of commonly used ligands (80 different complexes) using density functional theory. We establish that the required acid strength for protonation at the Fe–Fe site correlates with the standard reduction potential of the di-iron complexes with a linear energy relationship. These linear relationships allow for fast screening of ligands and tuning of the properties of the catalyst. Our study also suggests that bridgehead ligand properties, such as bulkiness and aromaticity, can be exploited to alter or even break the linear scaling relationships. |
format | Online Article Text |
id | pubmed-8753599 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | American Chemical Society |
record_format | MEDLINE/PubMed |
spelling | pubmed-87535992022-01-12 Linear Scaling Relationships to Predict pK(a)’s and Reduction Potentials for Bioinspired Hydrogenase Catalysis Puthenkalathil, Rakesh C. Ensing, Bernd Inorg Chem [Image: see text] Biomimetic catalysts inspired by the active site of the [FeFe] hydrogenase enzyme can convert protons into molecular hydrogen. Minimizing the overpotential of the electrocatalytic process remains a major challenge for practical application of the catalyst. The catalytic cycle of the hydrogen production follows an ECEC mechanism (E represents an electron transfer step, and C refers to a chemical step), in which the electron and proton transfer steps can be either sequential or coupled (PCET). In this study, we have calculated the pK(a)’s and the reduction potentials for a series of commonly used ligands (80 different complexes) using density functional theory. We establish that the required acid strength for protonation at the Fe–Fe site correlates with the standard reduction potential of the di-iron complexes with a linear energy relationship. These linear relationships allow for fast screening of ligands and tuning of the properties of the catalyst. Our study also suggests that bridgehead ligand properties, such as bulkiness and aromaticity, can be exploited to alter or even break the linear scaling relationships. American Chemical Society 2021-12-26 2022-01-10 /pmc/articles/PMC8753599/ /pubmed/34955025 http://dx.doi.org/10.1021/acs.inorgchem.1c02429 Text en © 2021 The Authors. Published by American Chemical Society https://creativecommons.org/licenses/by-nc-nd/4.0/Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Puthenkalathil, Rakesh C. Ensing, Bernd Linear Scaling Relationships to Predict pK(a)’s and Reduction Potentials for Bioinspired Hydrogenase Catalysis |
title | Linear Scaling Relationships to Predict pK(a)’s and Reduction Potentials for Bioinspired Hydrogenase
Catalysis |
title_full | Linear Scaling Relationships to Predict pK(a)’s and Reduction Potentials for Bioinspired Hydrogenase
Catalysis |
title_fullStr | Linear Scaling Relationships to Predict pK(a)’s and Reduction Potentials for Bioinspired Hydrogenase
Catalysis |
title_full_unstemmed | Linear Scaling Relationships to Predict pK(a)’s and Reduction Potentials for Bioinspired Hydrogenase
Catalysis |
title_short | Linear Scaling Relationships to Predict pK(a)’s and Reduction Potentials for Bioinspired Hydrogenase
Catalysis |
title_sort | linear scaling relationships to predict pk(a)’s and reduction potentials for bioinspired hydrogenase
catalysis |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8753599/ https://www.ncbi.nlm.nih.gov/pubmed/34955025 http://dx.doi.org/10.1021/acs.inorgchem.1c02429 |
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