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Physical Review Letters|July 9, 2019
Phase Transitions of Hybrid Perovskites Simulated by Machine-Learning Force Fields Trained on the Fly with Bayesian InferenceRyosuke Jinnouchi, Jonathan Lahnsteiner, Ferenc Karsai, et al.The Journal of Chemical Physics|June 24, 2020
Descriptors representing two- and three-body atomic distributions and their effects on the accuracy of machine-learned inter-atomic potentialsRyosuke Jinnouchi, Ferenc Karsai, Carla Verdi, et al.Journal of the American Chemical Society|March 4, 2016
Activities and Stabilities of Au-Modified Stepped-Pt Single-Crystal Electrodes as Model Cathode Catalysts in Polymer Electrolyte Fuel CellsKensaku Kodama, Ryosuke Jinnouchi, Naoko Takahashi, et al.Journal of Chemical Theory and Computation|February 24, 2025
Machine Learning Model to Predict Free-Energy Landscape and Position-Dependent Diffusion Constant to Extend the Scale of Dynamic Monte Carlo SimulationsTetsuro Nagai, Nobuaki Kikkawa, Ryosuke Jinnouchi, et al.The Journal of Chemical Physics|October 3, 2024
Density isobar of water and melting temperature of ice: Assessing common density functionalsPablo Montero de Hijes, Christoph Dellago, Ryosuke Jinnouchi, et al.The Journal of Physical Chemistry Letters|August 14, 2020
On-the-Fly Active Learning of Interatomic Potentials for Large-Scale Atomistic SimulationsRyosuke Jinnouchi, Kazutoshi Miwa, Ferenc Karsai, et al.Nature Nanotechnology|January 22, 2021
Challenges in applying highly active Pt-based nanostructured catalysts for oxygen reduction reactions to fuel cell vehiclesKensaku Kodama, Tomoyuki Nagai, Akira Kuwaki, et al.The Journal of Chemical Physics|March 17, 2026
Local diffusion analysis using square displacement averaged in subspaceNobuaki Kikkawa, Ryosuke Jinnouchi, Tetsuro Nagai, et al.Soft Matter|February 8, 2018
Viscoelasticity of dense suspensions of thermosensitive microgel mixtures undergoing colloidal gelationSaori Minami, Takumi Watanabe, Daisuke Suzuki, et al.The Journal of Chemical Physics|March 20, 2024
Comparing machine learning potentials for water: Kernel-based regression and Behler-Parrinello neural networksPablo Montero de Hijes, Christoph Dellago, Ryosuke Jinnouchi, et al.Pageof 5