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The effect of chemical representation on active machine learning towards closed-loop optimization

Accepted version
Peer-reviewed

Repository URI

https://www.repository.cam.ac.uk/handle/1810/333755

Repository DOI

https://doi.org/10.17863/CAM.81172
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Accepted version (7.17 MB)

Type

Article

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Authors

Abstract

Multivariate chemical reaction optimization involving catalytic systems is a non-trivial task due to the high number of tuneable parameters and discrete choices.

Description

Keywords

3404 Medicinal and Biomolecular Chemistry, 34 Chemical Sciences, Networking and Information Technology R&D (NITRD), Machine Learning and Artificial Intelligence

Journal Title

Reaction Chemistry and Engineering

Conference Name

Journal ISSN

2058-9883
2058-9883

Volume Title

Publisher

Royal Society of Chemistry (RSC)

Publisher DOI

https://doi.org/10.1039/d2re00008c

Rights and licensing

All Rights Reserved
Except where otherwised noted, this item's license is described as All Rights Reserved
Sponsorship
Engineering and Physical Sciences Research Council (EP/S024220/1)
Alexander

Relationships

Is derived from:
https://doi.org/10.26434/chemrxiv-2022-htmn0-v2

Collections

University of Cambridge Research Outputs (Articles and Conferences)