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Chemical Science|July 10, 2026
DeepMech: a machine learning framework for chemical reaction mechanism predictionManajit Das, Ajnabiul Hoque, Mayank Baranwal, et al.Journal of the American Chemical Society|October 2, 2024
Reinforcement Learning for Improving Chemical Reaction PerformanceAjnabiul Hoque, Mihir Surve, Shivaram Kalyanakrishnan, et al.Chemical Science|June 25, 2025
Molecular Machine Learning Approach to Enantioselective C-H Bond Activation Reactions: From Generative AI to Experimental ValidationAjnabiul Hoque, Taiwei Chang, Jin-Quan Yu, et al.The Journal of Chemical Physics|March 23, 2022
Machine learning studies on asymmetric relay Heck reaction-Potential avenues for reaction developmentManajit Das, Pooja Sharma, Raghavan B SunojJournal of Computational Chemistry|February 1, 2024
Advances in machine learning with chemical language models in molecular property and reaction outcome predictionsManajit Das, Ankit Ghosh, Raghavan B SunojThe Journal of Organic Chemistry|November 9, 2021
Molecular Insights on Solvent Effects in Organic Reactions as Obtained through Computational Chemistry ToolsManajit Das, Achyut Ranjan Gogoi, Raghavan B SunojAccounts of Chemical Research|April 22, 2016
Transition State Models for Understanding the Origin of Chiral Induction in Asymmetric CatalysisRaghavan B SunojChemistry (Weinheim an Der Bergstrasse, Germany)|May 10, 2007
Computational investigations on the general reaction profile and diastereoselectivity in sulfur ylide promoted aziridinationDeepa Janardanan, Raghavan B SunojThe Journal of Organic Chemistry|October 2, 2021
Iridium-Catalyzed Regioselective Borylation through C-H Activation and the Origin of Ligand-Dependent Regioselectivity SwitchingAnju Unnikrishnan, Raghavan B SunojChemistry (Weinheim an Der Bergstrasse, Germany)|October 20, 2009
On the origin of reversible hydrogen activation by phosphine-boranesRamanan Rajeev, Raghavan B SunojPageof 14