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Molecular Informatics|August 9, 2024
Chemography-guided analysis of a reaction path network for ethylene hydrogenation with a model Wilkinson's catalystPhilippe Gantzer, Ruben Staub, Yu Harabuchi, et al.
Molecules (Basel, Switzerland)|June 10, 2023
Challenges for Kinetics Predictions via Neural Network Potentials: A Wilkinson's Catalyst CaseRuben Staub, Philippe Gantzer, Yu Harabuchi, et al.
Journal of Chemical Theory and Computation|December 26, 2025
An Accurate and Efficient Reaction Path Search with Iteratively Trained Neural Network Potential: Answering the Passerini Mechanism ControversyRuben Staub, Yu Harabuchi, Carine Seraphim, et al.
Journal of Chemical Theory and Computation|March 16, 2026
Toward Reaction Vessel Mimicry: Machine Learning-Assisted Automated Exploration of Alkene Polymerization and Its TransferabilitySagar Ghorai, Ruben Staub, Yu Harabuchi, et al.
ACS Central Science|April 27, 2026
Predicting Enantioselectivity via Kinetic Simulations on Gigantic Reaction Path NetworksYu Harabuchi, Ruben Staub, Min Gao, et al.
Chemical Science|July 14, 2025
"Node" facilitated thermostable mechanophores for rapid self-strengthening in double network materialsJulong Jiang, Zhi Jian Wang, Ruben Staub, et al.
Journal of the American Chemical Society|June 2, 2026
Catalytic Asymmetric Hydration of AlkenesHibiki Hatano, Vitor Alcantara Fernandes, Subrata Mukherjee, et al.
Journal of Chemical Theory and Computation|March 13, 2019
On Benchmarking of Automated Methods for Performing Exhaustive Reaction Path SearchSatoshi Maeda, Yu Harabuchi
Physical Chemistry Chemical Physics : PCCP|July 2, 2020
AFIR explorations of transition states of extended unsaturated systems: automatic location of ambimodal transition statesTakuma Ito, Yu Harabuchi, Satoshi Maeda
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