Mn-PNP螯合物催化苯氰与肉桂腈加成反应动力学及机理的计算研究

IF 4.8 3区 化学 Q2 CHEMISTRY, MULTIDISCIPLINARY
Visuwesh Muthukumar, Debdutta Chakraborty
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引用次数: 0

摘要

金属配体配合(MLC)是一种金属中心和配体框架都有助于反应物结合的催化剂设计技术。最近,一种第一排过渡金属Mn-PNP钳形配合物通过MLC的芳香化-去芳香化机制起作用,用于无碱二腈偶联。考虑到整个方案中反应物的竞争性结合和分支途径,我们对相关反应进行了微动力学建模。我们提出的动力学方案可以很好地再现实验报告的产物收率。我们的结果表明,系统中存在的水是抑制的,并没有帮助结合的反应物的互变异构,不像以前的实验结果对脂肪族腈。通过福井函数分析和能量分解分析,对竞争结合和分支途径中涉及的过渡态和中间体进行了分析,使计算得到的反应路径合理化。根据这些分析,影响一种途径或另一种途径偏好的潜在因素可以合理地合理化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Computational Study on the Kinetics and Mechanism of Mn-PNP Pincer Complex Catalyzed Addition Reaction Between Benzyl Cyanide and Cinnamonitrile

Computational Study on the Kinetics and Mechanism of Mn-PNP Pincer Complex Catalyzed Addition Reaction Between Benzyl Cyanide and Cinnamonitrile

Metal ligand cooperation (MLC) is a catalyst design technique where both the metal center and the ligand framework aid in the binding of the reactant. Recently, a first-row transition metal Mn-PNP pincer complex that works via an aromatisation–dearomatisation mechanism of MLC was reported for base-free dinitrile coupling. We perform microkinetic modeling of the pertinent reaction considering competitive binding of the reactants and branching pathways in the overall scheme. The experimentally reported product yield could be well reproduced by our proposed kinetic scheme. Our results suggest that the presence of water in the system is inhibitive and does not help with the tautomerism of the bound reactant, unlike the previous experimental results for an aliphatic nitrile. We analyze the transition states and intermediates involved in the competitive binding and branching pathways by Fukui function analysis and energy decomposition analysis to rationalize the computed reaction path. The underlying factors that influence the preference of one pathway or the other could be reasonably rationalized based on these analyses.

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来源期刊
CiteScore
6.60
自引率
3.30%
发文量
247
审稿时长
1.7 months
期刊介绍: This distinguished journal publishes articles concerned with all aspects of computational chemistry: analytical, biological, inorganic, organic, physical, and materials. The Journal of Computational Chemistry presents original research, contemporary developments in theory and methodology, and state-of-the-art applications. Computational areas that are featured in the journal include ab initio and semiempirical quantum mechanics, density functional theory, molecular mechanics, molecular dynamics, statistical mechanics, cheminformatics, biomolecular structure prediction, molecular design, and bioinformatics.
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