Self-Optimizing Continuous Reactions in Supercritical Carbon Dioxide

Self-Optimizing Continuous Reactions in Supercritical Carbon Dioxide

Hands‐free optimization: A combination of an automated flow reactor, online analysis, and a control algorithm leads to efficient optimization of reactions to a given product without the need for human intervention.

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Bibliographic Details
Published in:Angewandte Chemie International Edition Vol. 50; no. 16; pp. 3788 - 3792
Main Authors: Parrott, Andrew J., Bourne, Richard A., Akien, Geoffrey R., Irvine, Derek J., Poliakoff, Martyn
Format: Journal Article
Language:English
Published: Weinheim WILEY-VCH Verlag 11-04-2011
WILEY‐VCH Verlag
Wiley Subscription Services, Inc
Edition:International ed. in English
Subjects:
Algorithms
Alkylation
Carbon Dioxide - chemistry
Catalysis
heterogeneous catalysis
reaction optimization
supercritical fluids
sustainable chemistry
Online Access:Get full text
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Description
Summary:Hands‐free optimization: A combination of an automated flow reactor, online analysis, and a control algorithm leads to efficient optimization of reactions to a given product without the need for human intervention.
Bibliography:EU
ark:/67375/WNG-DV1ZCLHR-P
We thank the EPSRC, grant no. EP/D501229/1 (the DICE project), the EU SYNFLOW project, AstraZeneca, and Croda Europe Ltd. for funding. We also thank David Litchfield, James Warren, Peter Fields, Richard Wilson, and Mark Guyler for technical support. We are grateful to Prof. Walter Leitner for suggesting the Simplex algorithm for self-optimization.
EPSRC - No. EP/D501229/1
ArticleID:ANIE201100412
istex:BCEAB3A80DEE440911BEC8142DC22A964BE69390
We thank the EPSRC, grant no. EP/D501229/1 (the DICE project), the EU SYNFLOW project, AstraZeneca, and Croda Europe Ltd. for funding. We also thank David Litchfield, James Warren, Peter Fields, Richard Wilson, and Mark Guyler for technical support. We are grateful to Prof. Walter Leitner for suggesting the Simplex algorithm for self‐optimization.
ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 23
ISSN:1433-7851
1521-3773
DOI:10.1002/anie.201100412