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线性标度关系预测仿生氢化酶催化的 p 值和还原电位。

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

机构信息

Van 't Hoff Institute for Molecular Sciences (HIMS), University of Amsterdam, Science Park 904, 1098 XH Amsterdam, The Netherlands.

出版信息

Inorg Chem. 2022 Jan 10;61(1):113-120. doi: 10.1021/acs.inorgchem.1c02429. Epub 2021 Dec 26.

Abstract

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 p'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.

摘要

受 [FeFe] 氢化酶活性位点启发的仿生催化剂可以将质子转化为氢气。最小化电催化过程的过电势仍然是催化剂实际应用的主要挑战。制氢的催化循环遵循 ECEC 机制(E 代表电子转移步骤,C 表示化学步骤),其中电子和质子转移步骤可以是顺序的或耦合的(PCET)。在这项研究中,我们使用密度泛函理论计算了一系列常用配体(80 种不同的配合物)的 p 值和还原电位。我们确定了在 Fe-Fe 位点质子化所需的酸强度与二铁配合物的标准还原电位呈线性能量关系。这些线性关系允许快速筛选配体并调整催化剂的性能。我们的研究还表明,可以利用桥头配体的性质,如体积和芳香性,来改变甚至打破线性标度关系。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2875/8753599/46a6845cb80e/ic1c02429_0001.jpg

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