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Wiley Interdisciplinary Reviews Computational Molecular Science
Article . 2022 . Peer-reviewed
License: CC BY
Data sources: Crossref
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Catalyst design within asymmetric organocatalysis

Authors: Iñigo Iribarren; Marianne Rica Garcia; Cristina Trujillo;

Catalyst design within asymmetric organocatalysis

Abstract

AbstractThe field of organocatalysis, more specifically asymmetric organocatalysis, is continuously expanding having grown significantly over the recent years. However, despite this exponential expansion, the ability to determine with any degree of certainty the reaction mechanisms of these types of reactions fails to keep within pace. Due to increasing calculation capacity and methods accuracy, computational methodologies have been established as an essential approach in both a predictive and supportive role to aid the synthetic design of novel catalysts by enabling the prediction of catalytic behaviour. This review is focused on the computationally‐led catalyst design within asymmetric organocatalysis, discussing the different theoretical approaches most commonly utilised.This article is categorized under: Structure and Mechanism > Reaction Mechanisms and Catalysis Software > Quantum Chemistry Quantum Computing > Algorithms

Countries
Ireland, United Kingdom
Related Organizations
Keywords

organocatalysts, asymmetric organocatalysis, computationally-led catalyst design, computational design, prediction

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    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
13
Top 10%
Average
Top 10%
Green
hybrid