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Nature Communications|July 12, 2025
Highly parallel optimisation of chemical reactions through automation and machine intelligenceJoshua W Sin, Siu Lun Chau, Ryan P Burwood, et al.ACS Central Science|October 2, 2019
Molecular Transformer: A Model for Uncertainty-Calibrated Chemical Reaction PredictionPhilippe Schwaller, Teodoro Laino, Théophile Gaudin, et al.Chemistry of Materials : a Publication of the American Chemical Society|November 29, 2023
Fast Customization of Chemical Language Models to Out-of-Distribution Data SetsAlessandra Toniato, Alain C Vaucher, Marzena Maria Lehmann, et al.Proceedings of the National Academy of Sciences of the United States of America|March 13, 2024
Interpreting chemisorption strength with AutoML-based feature deletion experimentsZhuo Li, Changquan Zhao, Haikun Wang, et al.Nature Computational Science|July 23, 2025
Best practices for multi-fidelity Bayesian optimization in materials and molecular researchVíctor Sabanza-Gil, Riccardo Barbano, Daniel Pacheco Gutiérrez, et al.Briefings in Bioinformatics|November 30, 2023
From intuition to AI: evolution of small molecule representations in drug discoveryMiles McGibbon, Steven Shave, Jie Dong, et al.Journal of the American Chemical Society|May 23, 2026
Strong Dipole-Dipole Interaction Promotes Electrocatalytic Acetylene Semihydrogenation over Symmetric Organo-ElectrocatalystsRui Bai, Junwu Chen, Jin Lin, et al.Chemical Science|June 14, 2021
Predicting retrosynthetic pathways using transformer-based models and a hyper-graph exploration strategyPhilippe Schwaller, Riccardo Petraglia, Valerio Zullo, et al.Communications Chemistry|June 19, 2026
Fine-tuning large language models to generate single-atom catalyst synthesis proceduresManu Suvarna, Matteo Manica, Fillipo Ficarra, et al.Nature Nanotechnology|February 8, 2018
Two-dimensional materials from high-throughput computational exfoliation of experimentally known compoundsNicolas Mounet, Marco Gibertini, Philippe Schwaller, et al.Pageof 6