Literature DB >> 27171796

Computation and Experiment: A Powerful Combination to Understand and Predict Reactivities.

Theresa Sperger1, Italo A Sanhueza1,2, Franziska Schoenebeck1.   

Abstract

Computational chemistry has become an established tool for the study of the origins of chemical phenomena and examination of molecular properties. Because of major advances in theory, hardware and software, calculations of molecular processes can nowadays be done with reasonable accuracy on a time-scale that is competitive or even faster than experiments. This overview will highlight broad applications of computational chemistry in the study of organic and organometallic reactivities, including catalytic (NHC-, Cu-, Pd-, Ni-catalyzed) and noncatalytic examples of relevance to organic synthesis. The selected examples showcase the ability of computational chemistry to rationalize and also predict reactivities of broad significance. A particular emphasis is placed on the synergistic interplay of computations and experiments. It is discussed how this approach allows one to (i) gain greater insight than the isolated techniques, (ii) inspire novel chemistry avenues, and (iii) assist in reaction development. Examples of successful rationalizations of reactivities are discussed, including the elucidation of mechanistic features (radical versus polar) and origins of stereoselectivity in NHC-catalyzed reactions as well as the rationalization of ligand effects on ligation states and selectivity in Pd- and Ni-catalyzed transformations. Beyond explaining, the synergistic interplay of computation and experiments is then discussed, showcasing the identification of the likely catalytically active species as a function of ligand, additive, and solvent in Pd-catalyzed cross-coupling reactions. These may vary between mono- or bisphosphine-bound or even anionic Pd complexes in polar media in the presence of coordinating additives. These fundamental studies also inspired avenues in catalysis via dinuclear Pd(I) cycles. Detailed mechanistic studies supporting the direct reactivity of Pd(I)-Pd(I) with aryl halides as well as applications of air-stable dinuclear Pd(I) catalysts are discussed. Additional combined experimental and computational studies are described for alternative metals, these include the discussion of the factors that control C-H versus C-C activation in the aerobic Cu-catalyzed oxidation of ketones, and ligand and additive effects on the nature and favored oxidation state of the active catalyst in Ni-catalyzed trifluoromethylthiolations of aryl chlorides. Examples of successful computational reactivity predictions along with experimental verifications are then presented. This includes the design of a fluorinated ligand [(CF3)2P(CH2)2P(CF3)2] for the challenging reductive elimination of ArCF3 from Pd(II) as well as the guidance of substrate scope (functional group tolerance and suitable leaving group) in the Ni-catalyzed trifluoromethylthiolation of C(sp(2))-O bonds. In summary, this account aims to convey the benefits of integrating computational studies in experimental research to increase understanding of observed phenomena and guide future experiments.

Entities:  

Year:  2016        PMID: 27171796     DOI: 10.1021/acs.accounts.6b00068

Source DB:  PubMed          Journal:  Acc Chem Res        ISSN: 0001-4842            Impact factor:   22.384


  22 in total

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

Authors:  Konstantinos D Vogiatzis; Mikhail V Polynski; Justin K Kirkland; Jacob Townsend; Ali Hashemi; Chong Liu; Evgeny A Pidko
Journal:  Chem Rev       Date:  2018-10-30       Impact factor: 60.622

2.  Harnessing Noncovalent Interactions in Dual-Catalytic Enantioselective Heck-Matsuda Arylation.

Authors:  Yernaidu Reddi; Cheng-Che Tsai; Carolina M Avila; F Dean Toste; Raghavan B Sunoj
Journal:  J Am Chem Soc       Date:  2018-12-28       Impact factor: 15.419

3.  Ligand-Substrate Dispersion Facilitates the Copper-Catalyzed Hydroamination of Unactivated Olefins.

Authors:  Gang Lu; Richard Y Liu; Yang Yang; Cheng Fang; Daniel S Lambrecht; Stephen L Buchwald; Peng Liu
Journal:  J Am Chem Soc       Date:  2017-11-09       Impact factor: 15.419

4.  Mechanisms, Challenges, and Opportunities of Dual Ni/Photoredox-Catalyzed C(sp2)-C(sp3) Cross-Couplings.

Authors:  Mingbin Yuan; Osvaldo Gutierrez
Journal:  Wiley Interdiscip Rev Comput Mol Sci       Date:  2021-09-21

5.  Experimental-Computational Synergy for Selective Pd(II)-Catalyzed C-H Activation of Aryl and Alkyl Groups.

Authors:  Yun-Fang Yang; Xin Hong; Jin-Quan Yu; K N Houk
Journal:  Acc Chem Res       Date:  2017-11-08       Impact factor: 22.384

6.  Mechanistically Guided Design of Ligands That Significantly Improve the Efficiency of CuH-Catalyzed Hydroamination Reactions.

Authors:  Andy A Thomas; Klaus Speck; Ilia Kevlishvili; Zhaohong Lu; Peng Liu; Stephen L Buchwald
Journal:  J Am Chem Soc       Date:  2018-10-15       Impact factor: 15.419

Review 7.  An invocation for computational evaluation of isomerization transforms: cationic skeletal reorganizations as a case study.

Authors:  Alexander W Schuppe; Yannan Liu; Timothy R Newhouse
Journal:  Nat Prod Rep       Date:  2020-09-15       Impact factor: 13.423

8.  Quantum-mechanical transition-state model combined with machine learning provides catalyst design features for selective Cr olefin oligomerization.

Authors:  Steven M Maley; Doo-Hyun Kwon; Nick Rollins; Johnathan C Stanley; Orson L Sydora; Steven M Bischof; Daniel H Ess
Journal:  Chem Sci       Date:  2020-08-21       Impact factor: 9.825

Review 9.  Computational Design of Functionalized Metal-Organic Framework Nodes for Catalysis.

Authors:  Varinia Bernales; Manuel A Ortuño; Donald G Truhlar; Christopher J Cramer; Laura Gagliardi
Journal:  ACS Cent Sci       Date:  2017-12-21       Impact factor: 14.553

10.  An automated method to find reaction mechanisms and solve the kinetics in organometallic catalysis.

Authors:  J A Varela; S A Vázquez; E Martínez-Núñez
Journal:  Chem Sci       Date:  2017-03-07       Impact factor: 9.825

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