{"title":"Revisiting the Reviewed: A Meta‐Analysis of Computational Studies on Transition Metal‐Catalysed Hydrogenation Reactions","authors":"Michael Bühl, Shahbaz Ahmad","doi":"10.1002/cctc.202401053","DOIUrl":null,"url":null,"abstract":"This meta‐review attempts to systematically analyse the recent advancements in transition metal‐catalysed hydrogenation reactions as discussed in previous review articles, emphasising the computational insights that enhance our understanding of reaction mechanisms. It highlights the efficacy of density functional theory (DFT) in calculating free energies, exploring the mechanistic pathways and kinetics of hydrogenation processes, focusing on substrates such as alkenes, alkynes, amides, imines, nitriles, and carbon dioxide. The review details significant studies where computational models help predict reaction outcomes and aid in catalyst design. Notable discussions include the role of solvent effects and metal‐ligand interactions, which are crucial for reactivity and selectivity but often underestimated in computational models. The review concludes with current computational challenges and prospects, suggesting enhanced models and experimental collaborations to refine catalyst design.","PeriodicalId":141,"journal":{"name":"ChemCatChem","volume":"11 1","pages":""},"PeriodicalIF":3.8000,"publicationDate":"2024-09-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ChemCatChem","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1002/cctc.202401053","RegionNum":3,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"CHEMISTRY, PHYSICAL","Score":null,"Total":0}
引用次数: 0
Abstract
This meta‐review attempts to systematically analyse the recent advancements in transition metal‐catalysed hydrogenation reactions as discussed in previous review articles, emphasising the computational insights that enhance our understanding of reaction mechanisms. It highlights the efficacy of density functional theory (DFT) in calculating free energies, exploring the mechanistic pathways and kinetics of hydrogenation processes, focusing on substrates such as alkenes, alkynes, amides, imines, nitriles, and carbon dioxide. The review details significant studies where computational models help predict reaction outcomes and aid in catalyst design. Notable discussions include the role of solvent effects and metal‐ligand interactions, which are crucial for reactivity and selectivity but often underestimated in computational models. The review concludes with current computational challenges and prospects, suggesting enhanced models and experimental collaborations to refine catalyst design.
期刊介绍:
With an impact factor of 4.495 (2018), ChemCatChem is one of the premier journals in the field of catalysis. The journal provides primary research papers and critical secondary information on heterogeneous, homogeneous and bio- and nanocatalysis. The journal is well placed to strengthen cross-communication within between these communities. Its authors and readers come from academia, the chemical industry, and government laboratories across the world. It is published on behalf of Chemistry Europe, an association of 16 European chemical societies, and is supported by the German Catalysis Society.