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

Pomberger, A; Pedrina McCarthy, AA; Khan, A; Sung, S; Taylor, CJ; Gaunt, MJ; Colwell, L; Walz, D; Lapkin, AA

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Authors

Pomberger, A

Pedrina McCarthy, AA

Khan, A

Sung, S

Taylor, CJ

Gaunt, MJ

Colwell, L

Publication Date

2022

Journal Title

Reaction Chemistry and Engineering

ISSN

2058-9883

Publisher

Royal Society of Chemistry (RSC)

Type

Article

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Citation

Pomberger, A., Pedrina McCarthy, A., Khan, A., Sung, S., Taylor, C., Gaunt, M., Colwell, L., et al. (2022). The effect of chemical representation on active machine learning towards closed-loop optimization†. Reaction Chemistry and Engineering https://doi.org/10.1039/d2re00008c

Abstract

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

Sponsorship

Alexander

Funder references

Engineering and Physical Sciences Research Council (EP/S024220/1)

Identifiers

External DOI: https://doi.org/10.1039/d2re00008c

This record's URL: https://www.repository.cam.ac.uk/handle/1810/333755

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Licence URL: http://www.rioxx.net/licenses/all-rights-reserved

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