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高效计算金配合物的几何结构。

Efficient Computation of Geometries for Gold Complexes.

机构信息

Molecular Inorganic Chemistry, Stratingh Institute for Chemistry, University of Groningen, 9747, AG Groningen, The Netherlands.

Zernike Institute for Advanced Materials, University of Groningen, 9747, AG Groningen, The Netherlands.

出版信息

Chemphyschem. 2021 Jun 16;22(12):1262-1268. doi: 10.1002/cphc.202001052. Epub 2021 May 28.

DOI:10.1002/cphc.202001052
PMID:33729673
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8252628/
Abstract

Computationally obtaining structural parameters along a reaction coordinate is commonly performed with Kohn-Sham density functional theory which generally provides a good balance between speed and accuracy. However, CPU times still range from inconvenient to prohibitive, depending on the size of the system under study. Herein, the tight binding GFN2-xTB method [C. Bannwarth, S. Ehlert, S. Grimme, J. Chem. Theory Comput. 2019, 15, 1652] is investigated as an alternative to produce reasonable geometries along a reaction path, that is, reactant, product and transition state structures for a series of transformations involving gold complexes. A small mean error (1 kcal/mol) was found, with respect to an efficient composite hybrid-GGA exchange-correlation functional (PBEh-3c) paired with a double-ζ basis set, which is 2-3 orders of magnitude slower. The outlined protocol may serve as a rapid tool to probe the viability of proposed mechanistic pathways in the field of gold catalysis.

摘要

通过 Kohn-Sham 密度泛函理论计算沿着反应坐标的结构参数是常见的做法,该理论通常在速度和准确性之间取得很好的平衡。然而,根据所研究系统的大小,CPU 时间仍然从不方便到不可行。在此,作为替代方法,研究了紧束缚 GFN2-xTB 方法[C. Bannwarth, S. Ehlert, S. Grimme, J. Chem. Theory Comput. 2019, 15, 1652],以沿着反应路径生成合理的几何形状,即金配合物系列转化的反应物、产物和过渡态结构。与高效的复合混合泛函(PBEh-3c)与双 ζ 基组配对相比,发现其平均误差较小(1 kcal/mol),而后者的速度要慢 2-3 个数量级。所概述的方案可以作为一种快速工具,用于探测金催化领域中提出的机理途径的可行性。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73ee/8252628/c7e71b47bac7/CPHC-22-1262-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73ee/8252628/58f3489fce7d/CPHC-22-1262-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73ee/8252628/685e03524869/CPHC-22-1262-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73ee/8252628/2635d63d82d1/CPHC-22-1262-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73ee/8252628/dbfee40df20c/CPHC-22-1262-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73ee/8252628/79b02ae7b691/CPHC-22-1262-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73ee/8252628/c7e71b47bac7/CPHC-22-1262-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73ee/8252628/58f3489fce7d/CPHC-22-1262-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73ee/8252628/685e03524869/CPHC-22-1262-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73ee/8252628/2635d63d82d1/CPHC-22-1262-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73ee/8252628/dbfee40df20c/CPHC-22-1262-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73ee/8252628/79b02ae7b691/CPHC-22-1262-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/73ee/8252628/c7e71b47bac7/CPHC-22-1262-g001.jpg

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