Jeraal, MI, Holmes, N orcid.org/0000-0002-3846-6493, Akien, GR et al. (1 more author) (2018) Enhanced process development using automated continuous reactors by self-optimisation algorithms and statistical empirical modelling. Tetrahedron, 74 (25). pp. 3158-3164. ISSN 0040-4020
Abstract
Reaction optimisation and understanding is fundamental for process development and is achieved using a variety of techniques. This paper explores the use of self-optimisation and experimental design as a tandem approach to reaction optimisation. A Claisen-Schmidt condensation was optimised using a branch and fit minimising algorithm, with the resulting data being used to fit a response surface model. The model was then applied to find new responses for different metrics, highlighting the most important for process development purposes.
Metadata
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Copyright, Publisher and Additional Information: | © 2018 Elsevier Ltd. This is an author produced version of a paper published in Tetrahedron. Uploaded in accordance with the publisher's self-archiving policy. | ||||
Keywords: | Self-optimisation; Design of experiments; Clasien-schmidt condensation; Reaction metrics; Process development; Flow chemistry | ||||
Dates: |
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Institution: | The University of Leeds | ||||
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Chemical & Process Engineering (Leeds) | ||||
Funding Information: |
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Depositing User: | Symplectic Publications | ||||
Date Deposited: | 28 Feb 2018 13:49 | ||||
Last Modified: | 27 Feb 2019 01:39 | ||||
Status: | Published | ||||
Publisher: | Elsevier | ||||
Identification Number: | https://doi.org/10.1016/j.tet.2018.02.061 |