Computational Approach to Molecular Catalysis by 3d Transition Metals: Challenges and Opportunities

• Published in: Chemical reviews 2019-02, Vol.119 (4), p.2453-2523
• Main Authors: Vogiatzis, Konstantinos D, Polynski, Mikhail V, Kirkland, Justin K, Townsend, Jacob, Hashemi, Ali, Liu, Chong, Pidko, Evgeny A
• Format: Article
• Language: English
• Subjects: Catalysis; Catalysts; Complexity; Computational chemistry; Electronic structure; Human bias; Ligands; Metal-organic frameworks; Metals; Organic chemistry; Reaction mechanisms; Review; Solvation; Transition metals
• ISSN: 0009-2665; 1520-6890
• DOI: 10.1021/acs.chemrev.8b00361

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.