Design and Optimization of Catalysts Based on Mechanistic Insights Derived from Quantum Chemical Reaction Modeling

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Until recently, computational tools were mainly used to explain chemical reactions after experimental results were obtained. With the rapid development of software and hardware technologies to make computational modeling tools more reliable, they can now provide valuable insights and even become predictive. In this review, we highlighted several studies involving computational predictions of unexpected reactivities or providing mechanistic insights for organic and organometallic reactions that led to improved experimental results. Key to these successful applications is an integration between theory and experiment that allows for incorporation of empirical knowledge with precise computed values. Computer modeling of chemical reactions is already a standard tool that is being embraced by an ever increasing group of researchers, and it is clear that its utility in predictive reaction design will increase further in the near future.
Publisher
AMER CHEMICAL SOC
Issue Date
2019-06
Language
English
Article Type
Review
Citation

CHEMICAL REVIEWS, v.119, no.11, pp.6509 - 6560

ISSN
0009-2665
DOI
10.1021/acs.chemrev.9b00073
URI
http://hdl.handle.net/10203/263095
Appears in Collection
CH-Journal Papers(저널논문)
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