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Cited by 1,519

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Fundamentals of green chemistry: efficiency in reaction design

Sheldon, Roger A.·2012·Chem. Soc. Rev.

Abstract

In this tutorial review, the fundamental concepts underlying the principles of green and sustainable chemistry--atom and step economy and the E factor--are presented, within the general context of efficiency in organic synthesis. The importance of waste minimisation through the widespread application of catalysis in all its forms--homogeneous, heterogeneous, organocatalysis and biocatalysis--is discussed. These general principles are illustrated with simple practical examples, such as alcohol oxidation and carbonylation and the asymmetric reduction of ketones. The latter reaction is exemplified by a three enzyme process for the production of a key intermediate in the synthesis of the cholesterol lowering agent, atorvastatin. The immobilisation of enzymes as cross-linked enzyme aggregates (CLEAs) as a means of optimizing operational performance is presented. The use of immobilised enzymes in catalytic cascade processes is illustrated with a trienzymatic process for the conversion of benzaldehyde to (S)-mandelic acid using a combi-CLEA containing three enzymes. Finally, the transition from fossil-based chemicals manufacture to a more sustainable biomass-based production is discussed.

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Metadata

Authors
Sheldon, R. A.
Venue
Chem. Soc. Rev.
Published
2012
Volume
41
Issue
4
Pages
1437-1451
ISSN
  • 0306-0012 (ISSN-L)
  • 1460-4744
OpenAlex
W2131304252
Cited by
1,519
References
1
FWCI
6.04
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Fundamentals of green chemistry: efficiency in reaction design. https://app.cochat.ai/papers/10.1039/c1cs15219j
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Sheldon, R. A. (2012). Fundamentals of green chemistry: efficiency in reaction design. Chem. Soc. Rev. https://doi.org/10.1039/c1cs15219j

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.