Linear Scaling Relationships to Predict pKa's and Reduction Potentials for Bioinspired Hydrogenase Catalysis

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 product...

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Veröffentlicht in:Inorganic chemistry 2022-01, Vol.61 (1), p.113-120
Hauptverfasser: Puthenkalathil, Rakesh C, Ensing, Bernd
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Ensing, Bernd
description 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 pKa'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.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 pKa'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.
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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.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 pKa'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.</description><identifier>ISSN: 1520-510X</identifier><identifier>ISSN: 0020-1669</identifier><identifier>EISSN: 1520-510X</identifier><identifier>DOI: 10.1021/acs.inorgchem.1c02429</identifier><identifier>PMID: 34955025</identifier><language>eng</language><publisher>American Chemical Society</publisher><ispartof>Inorganic chemistry, 2022-01, Vol.61 (1), p.113-120</ispartof><rights>2021 The Authors. 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title Linear Scaling Relationships to Predict pKa's and Reduction Potentials for Bioinspired Hydrogenase Catalysis
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