Department of Chemistry , University of Tennessee , Knoxville , Tennessee 37996 , United States.
TheoMAT group , ITMO University , Lomonosova 9, St. Petersburg 191002 , Russia.
Chem Rev. 2019 Feb 27;119(4):2453-2523. doi: 10.1021/acs.chemrev.8b00361. Epub 2018 Oct 30.
Computational chemistry provides a versatile toolbox for studying mechanistic details of catalytic reactions and holds promise to deliver practical strategies to enable the rational in silico catalyst design. The versatile reactivity and nontrivial electronic structure effects, common for systems based on 3d transition metals, introduce additional complexity that may represent a particular challenge to the standard computational strategies. In this review, we discuss the challenges and capabilities of modern electronic structure methods for studying the reaction mechanisms promoted by 3d transition metal molecular catalysts. Particular focus will be placed on the ways of addressing the multiconfigurational problem in electronic structure calculations and the role of expert bias in the practical utilization of the available methods. The development of density functionals designed to address transition metals is also discussed. Special emphasis is placed on the methods that account for solvation effects and the multicomponent nature of practical catalytic systems. This is followed by an overview of recent computational studies addressing the mechanistic complexity of catalytic processes by molecular catalysts based on 3d metals. Cases that involve noninnocent ligands, multicomponent reaction systems, metal-ligand and metal-metal cooperativity, as well as modeling complex catalytic systems such as metal-organic frameworks are presented. Conventionally, computational studies on catalytic mechanisms are heavily dependent on the chemical intuition and expert input of the researcher. Recent developments in advanced automated methods for reaction path analysis hold promise for eliminating such human-bias from computational catalysis studies. A brief overview of these approaches is presented in the final section of the review. The paper is closed with general concluding remarks.
计算化学为研究催化反应的机理细节提供了一个通用的工具箱,并有望提供实用的策略,以实现合理的计算机催化剂设计。基于 3d 过渡金属的体系具有通用的反应性和复杂的电子结构效应,这增加了额外的复杂性,这可能对标准计算策略构成特殊挑战。在这篇综述中,我们讨论了现代电子结构方法在研究 3d 过渡金属分子催化剂促进的反应机制方面的挑战和能力。特别关注的是解决电子结构计算中多组态问题的方法,以及在实际应用现有方法时专家偏见的作用。还讨论了设计用于解决过渡金属问题的密度泛函的发展。特别强调考虑溶剂化效应和实际催化体系多组分性质的方法。接下来概述了最近基于 3d 金属的分子催化剂对催化过程机理复杂性的计算研究。介绍了涉及非中性配体、多组分反应体系、金属-配体和金属-金属协同作用以及模拟复杂催化体系(如金属有机骨架)的情况。通常,催化机制的计算研究严重依赖于研究人员的化学直觉和专家输入。用于反应路径分析的先进自动化方法的最新发展有望消除计算催化研究中的这种人为偏见。在综述的最后一节简要介绍了这些方法。本文以一般性结论结束。