RESEARCH PAPER · Digital Discovery · 2026
Machine learning models for catalytic asymmetric reactions of simple alkenes: from enantioselectivity predictions to chemical insights
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Benchmarking molecular representations and machine learning algorithms for asymmetric catalysis: a palladium-catalysed decarboxylative asymmetric allylic alkylation case study
Journal of Cheminformatics · 2026-06-12
Eduardo Aguilar-Bejarano, Declan Galvin, David M. Rogers, Ender Özcan, Simon Woodward, Patrick J. Guiry, Grazziela Figueredo
Read original paper ↗ ·Predicting Enantioselectivity of Ruthenium-Catalyzed Ketone Hydrogenation with 3D Structure-Based Deep Learning
Journal of the American Chemical Society · 2026-07-23
Nicholas Hadler, Evelyn Ramirez, Matthew Avaylon, Masha Elkin, N. Ian Rinehart, Michael W. Mahoney, Gunther H. Weber, Joscha Hoche, Jan Gerit Brandenburg, Talita Perciano, John F. Hartwig
Read original paper ↗ ·3D, Structure-Based, Deep Learning Approach to Predict the Regioselectivity of Olefin Hydroformylations
Journal of the American Chemical Society · 2026-08-24
Nicholas Hadler, N. Ian Rinehart, Masha Elkin, Jeremy Nicolai, Golsa Gheibi, Jiaqing Chen, Matthew Avaylon, Ross Maciejewski, Gunther H. Weber, Michael W. Mahoney, Talita Perciano, John F. Hartwig
Read original paper ↗ ·Predicting Reactivity and Enantioselectivity from Small Experimental Datasets: A Case Study in Asymmetric Magnesium Catalysis
ACS Catalysis · 2026-09-14
Paulina Baczewska, Damian Nowak, Joanna A. Jaszczewska‐Adamczak, Rafał Adam Bachorz, Marcin Hoffmann, Jacek Młynarski
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