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19982023
most citedAccelerating first-principles estimation of thermal conductivity by machine-learning interatomic potentials: A MTP/ShengBTE solution

224 citations · 654 across the 20 of their papers we have counts for

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physics.chem-ph2022

Towards reliable calculations of thermal rate constants: ring polymer molecular dynamics for the OH + HBr Br + HO reaction

Ivan S. Novikov, Edgar M. Makarov, Alexander V. Shapeev +1

We combined Moment Tensor Potential (MTP) and Ring Polymer Molecular Dynamics (RPMD) for calculating the thermal rate constants of the OH + HBr system. We used the active learning…

physics.chem-ph2020

Assessing Parameters for Ring Polymer Molecular Dynamics Simulations at Low Temperatures: DH+H Chemical Reaction

Ivan S. Novikov, Yury V. Suleimanov, Alexander V. Shapeev

Ring polymer molecular dynamics (RPMD) is an accurate method for calculating thermal chemical reaction rates. It has recently been discovered that low-temperature calculations are…

physics.chem-ph2019★ 18 cited

Ring Polymer Molecular Dynamics and Active Learning of Moment Tensor Potential for Gas-Phase Barrierless Reactions: Application to S + H2

Ivan S. Novikov, Alexander V. Shapeev, Yury V. Suleimanov

Ring polymer molecular dynamics (RPMD) has proven to be an accurate approach for calculating thermal rate coefficients of various chemical reactions. For wider application of this…

physics.chem-ph2018★ 47 cited

Automated Calculation of Thermal Rate Coefficients using Ring Polymer Molecular Dynamics and Machine-Learning Interatomic Potentials with Active Learning

Ivan S. Novikov, Yury V. Suleimanov, Alexander V. Shapeev

We propose a methodology for fully automated calculation of thermal rate coefficients of gas phase chemical reactions, which is based on combining the ring polymer molecular dynami…