Machine learning driven design of spiropyran photoswitches
This study presents the development of a generative machine learning model for the design of photoswitches with enhanced switching and small spectral overlap between open and closed forms.
Authors
- Stefan Hecht (ORCID: https://orcid.org/0000-0002-6124-0222)
- Karsten Reuter (ORCID: https://orcid.org/0000-0001-8473-8659)
- Johannes T. Margraf (ORCID: https://orcid.org/0000-0002-0862-5289)
- Robert Strothmann
- Mehran Amanpur
- Tomás Nevesely
Institutions
- Fritz Haber Institute of the Max Planck Society (DE)
- Humboldt-Universität zu Berlin (DE)
- University of Bayreuth (DE)
Publication Details
- Journal
- Digital Discovery
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1039/d5dd00327j
- Primary Topic
- Photochromic and Fluorescence Chemistry
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- Deutsche Forschungsgemeinschaft
- Einstein Stiftung Berlin