Multi-objective Bayesian optimisation using <i>q</i>-noisy expected hypervolume improvement (<i>q</i>NEHVI) for the Schotten–Baumann reaction-Reference-Cited by-同舟云学术

Multi-objective Bayesian optimisation using q-noisy expected hypervolume improvement (qNEHVI) for the Schotten–Baumann reaction

Published:2024 Issue: Volume: Page:
ISSN:2058-9883
Container-title:Reaction Chemistry & Engineering
language:en
Short-container-title:React. Chem. Eng.

Author:

Zhang Jiyizhe¹^ORCID,Sugisawa Naoto¹²^ORCID,Felton Kobi C.¹^ORCID,Fuse Shinichiro²^ORCID,Lapkin Alexei A.¹³⁴^ORCID

Affiliation:

1. Department of Chemical Engineering and Biotechnology, University of Cambridge, Cambridge CB3 0AS, UK

2. Department of Basic Medicinal Sciences, Graduate School of Pharmaceutical Sciences, Nagoya University, Nagoya, 464-8601, Japan

3. Innovation Centre in Digital Molecular Technologies, Yusuf Hamied Department of Chemistry, University of Cambridge, Lensfield Road, Cambridge, CB2 1EW, UK

4. Cambridge Centre for Advanced Research and Education in Singapore (CARES Ltd), #05-05 CREATE Tower, 1 Create Way, 138602, Singapore

Abstract

Multi-objective Bayesian optimisation allows for finding trade-off solutions of the Schotten–Baumann reaction in a continuous flow. The effect of mixing efficiency on the fast reaction results in the complexity of the reaction space.

Funder

Japan Society for the Promotion of Science

Publisher

Royal Society of Chemistry (RSC)

Subject

Fluid Flow and Transfer Processes,Process Chemistry and Technology,Chemical Engineering (miscellaneous),Chemistry (miscellaneous),Catalysis

Link

http://pubs.rsc.org/en/content/articlepdf/2024/RE/D3RE00502J

Reference45 articles.

1. Analysis of Past and Present Synthetic Methodologies on Medicinal Chemistry: Where Have All the New Reactions Gone?

2. Key green chemistry research areas—a perspective from pharmaceutical manufacturers

3. Large-Scale Amidations in Process Chemistry: Practical Considerations for Reagent Selection and Reaction Execution