Enhanced process development using automated continuous reactors by self-optimisation algorithms and statistical empirical modelling

TETRAHEDRON

卷:74

Article

Jeraal, Mohammed I.^1,2  Holmes, Nicholas^1,2  Akien, Geoffrey R.^1,2,3  Bourne, Richard A.^1,2 

[1] Univ Leeds, Sch Chem, Inst Proc Res & Dev, Leeds LS2 9JT, W Yorkshire, England

[2] Univ Leeds, Sch Chem & Proc Engn, Leeds LS2 9JT, W Yorkshire, England

[3] Univ Lancaster, Dept Chem, Faraday Bldg, Lancaster LA1 4YB, England

关键词: Self-optimisation;    Design of experiments;    Clasien-schmidt condensation;    Reaction metrics;    Process development;    Flow chemistry;   

DOI  :  10.1016/j.tet.2018.02.061

来源: Elsevier

【 摘 要 】

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. (C) 2018 Elsevier Ltd. All rights reserved.

【 授权许可】

Free