Griffiths, Ryan-Rhys;
Greenfield, Jake L;
Thawani, Aditya R;
Jamasb, Arian R;
Moss, Henry B;
Bourached, Anthony;
Jones, Penelope;
... Lee, Alpha A; + view all
(2022)
Data-driven discovery of molecular photoswitches with multioutput Gaussian processes.
Chemical Science
, 13
(45)
pp. 13541-13551.
10.1039/d2sc04306h.
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Abstract
Photoswitchable molecules display two or more isomeric forms that may be accessed using light. Separating the electronic absorption bands of these isomers is key to selectively addressing a specific isomer and achieving high photostationary states whilst overall red-shifting the absorption bands serves to limit material damage due to UV-exposure and increases penetration depth in photopharmacological applications. Engineering these properties into a system through synthetic design however, remains a challenge. Here, we present a data-driven discovery pipeline for molecular photoswitches underpinned by dataset curation and multitask learning with Gaussian processes. In the prediction of electronic transition wavelengths, we demonstrate that a multioutput Gaussian process (MOGP) trained using labels from four photoswitch transition wavelengths yields the strongest predictive performance relative to single-task models as well as operationally outperforming time-dependent density functional theory (TD-DFT) in terms of the wall-clock time for prediction. We validate our proposed approach experimentally by screening a library of commercially available photoswitchable molecules. Through this screen, we identified several motifs that displayed separated electronic absorption bands of their isomers, exhibited red-shifted absorptions, and are suited for information transfer and photopharmacological applications. Our curated dataset, code, as well as all models are made available at https://github.com/Ryan-Rhys/The-Photoswitch-Dataset.
| Type: | Article |
|---|---|
| Title: | Data-driven discovery of molecular photoswitches with multioutput Gaussian processes |
| Location: | England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1039/d2sc04306h |
| Publisher version: | https://doi.org/10.1039/D2SC04306H |
| Language: | English |
| Additional information: | https://creativecommons.org/licenses/by/3.0/ |
| Keywords: | Science & Technology, Physical Sciences, Chemistry, Multidisciplinary, Chemistry, AZOBENZENE PHOTOSWITCHES, LIGHT, ISOMERIZATION, PERFORMANCE, PREDICTION, EXCHANGE, SYSTEMS |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Health Informatics |
| URI: | https://discovery-pp.ucl.ac.uk/id/eprint/10170727 |
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