Investigation of arene and heteroarene nitration supported by high-throughput experimentation and machine learning
A systematic study of nitration of (hetero)arenes was conducted using HTE. The generated data were used to develop a predictive tool relying on machine learning to evaluate the best reaction conditions depending on the targeted substrate.
Authors
- Éric Pasquinet (ORCID: https://orcid.org/0000-0002-7601-5503)
- Eugénie Romero (ORCID: https://orcid.org/0000-0003-0484-1221)
- Matthieu Daniel (ORCID: https://orcid.org/0000-0003-2201-6305)
- Taline Kerackian
- Clément Wespiser (ORCID: https://orcid.org/0009-0005-2564-0420)
Institutions
- Commissariat à l'Énergie Atomique et aux Énergies Alternatives (FR)
- Université Paris-Saclay (FR)
- Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR)
- Technologies pour la Santé (FR)
- CEA Le Ripault (FR)
- CEA Paris-Saclay (FR)
Publication Details
- Journal
- Digital Discovery
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1039/d5dd00086f
- Primary Topic
- Chemical Reactions and Isotopes
- Type
- article
- Field-Weighted Citation Impact
- 0.00