ML meets MLn: Machine learning in ligand promoted homogeneous catalysis

ML meets MLn: Machine learning in ligand promoted homogeneous catalysis

The benefits of using machine learning approaches in the design, optimisation and understanding of homogeneous catalytic processes are being increasingly realised. We focus on the understanding and implementation of key concepts, which serve as conduits to more advanced chemical machine learning lit...

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Bibliographic Details
Main Authors: Jonathan D. Hirst, Samuel Boobier, Jennifer Coughlan, Jessica Streets, Philippa L. Jacob, Oska Pugh, Ender Özcan, Simon Woodward
Format: Article
Language:English
Published: Elsevier 2023-12-01
Series:Artificial Intelligence Chemistry
Subjects:
Homogeneous catalysis
Machine learning
Cheminformatics
Online Access:http://www.sciencedirect.com/science/article/pii/S2949747723000064

Internet

http://www.sciencedirect.com/science/article/pii/S2949747723000064

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