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Novikov, Ivan S., Shapeev, Alexander V., Suleimanov, Yury V. (2019) Ring polymer molecular dynamics and active learning of moment tensor potential for gas-phase barrierless reactions: Application to S + H2. The Journal of Chemical Physics, 151 (22). 224105pp. doi:10.1063/1.5127561

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Reference TypeJournal (article/letter/editorial)
TitleRing polymer molecular dynamics and active learning of moment tensor potential for gas-phase barrierless reactions: Application to S + H2
JournalThe Journal of Chemical Physics
AuthorsNovikov, Ivan S.Author
Shapeev, Alexander V.Author
Suleimanov, Yury V.Author
Year2019 (December 14)Volume151
Issue22
PublisherAIP Publishing
DOIdoi:10.1063/1.5127561Search in ResearchGate
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Mindat Ref. ID2413019Long-form Identifiermindat:1:5:2413019:8
GUID0
Full ReferenceNovikov, Ivan S., Shapeev, Alexander V., Suleimanov, Yury V. (2019) Ring polymer molecular dynamics and active learning of moment tensor potential for gas-phase barrierless reactions: Application to S + H2. The Journal of Chemical Physics, 151 (22). 224105pp. doi:10.1063/1.5127561
Plain TextNovikov, Ivan S., Shapeev, Alexander V., Suleimanov, Yury V. (2019) Ring polymer molecular dynamics and active learning of moment tensor potential for gas-phase barrierless reactions: Application to S + H2. The Journal of Chemical Physics, 151 (22). 224105pp. doi:10.1063/1.5127561
In(2019, December) The Journal of Chemical Physics Vol. 151 (22) AIP Publishing

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Novikov, Ivan S., Suleimanov, Yury V., Shapeev, Alexander V. (2021) Assessing parameters for ring polymer molecular dynamics simulations at low temperatures: DH + H chemical reaction. Chemical Physics Letters, 773. 138567pp. doi:10.1016/j.cplett.2021.138567
Novikov, Ivan S., Makarov, Edgar M., Suleimanov, Yury V., Shapeev, Alexander V. (2024) Towards reliable calculations of thermal rate constants: Ring polymer molecular dynamics for the OH + HBr → Br + H2O reaction. Chemical Physics Letters, 856. doi:10.1016/j.cplett.2024.141620
Novikov, I. S., Suleimanov, Y. V., Shapeev, A. V. (2018) Automated calculation of thermal rate coefficients using ring polymer molecular dynamics and machine-learning interatomic potentials with active learning. Physical Chemistry Chemical Physics, 20 (46). 29503-29512 doi:10.1039/c8cp06037a
Podryabinkin, Evgeny, Garifullin, Kamil, Shapeev, Alexander, Novikov, Ivan (2023) MLIP-3: Active learning on atomic environments with moment tensor potentials. The Journal of Chemical Physics, 159 (8) doi:10.1063/5.0155887
Rybin, Nikita, Novikov, Ivan S., Shapeev, Alexander (2025) Accelerating structure prediction of molecular crystals using actively trained moment tensor potential. Physical Chemistry Chemical Physics, 27 (10). doi:10.1039/d4cp04578e
Suleimanov, Yury V., Collepardo-Guevara, Rosana, Manolopoulos, David E. (2011) Bimolecular reaction rates from ring polymer molecular dynamics: Application to H + CH4→ H2 + CH3. The Journal of Chemical Physics, 134 (4). 44131pp. doi:10.1063/1.3533275
Suleimanov, Yury V., Kong, Wendi J., Guo, Hua, Green, William H. (2014) Ring-polymer molecular dynamics: Rate coefficient calculations for energetically symmetric (near thermoneutral) insertion reactions (X + H2) → HX + H(X = C(1D), S(1D)). The Journal of Chemical Physics, 141 (24). 244103pp. doi:10.1063/1.4904080
Kotykhov, Alexey S., Gubaev, Konstantin, Sotskov, Vadim, Tantardini, Christian, Hodapp, Max, Shapeev, Alexander V., Novikov, Ivan S. (2024) Fitting to magnetic forces improves the reliability of magnetic Moment Tensor Potentials. Computational Materials Science, 245. doi:10.1016/j.commatsci.2024.113331
Hele, Timothy J. H., Suleimanov, Yury V. (2015) Should thermostatted ring polymer molecular dynamics be used to calculate thermal reaction rates?. The Journal of Chemical Physics, 143 (7). 74107pp. doi:10.1063/1.4928599
Collepardo-Guevara, Rosana, Suleimanov, Yury V., Manolopoulos, David E. (2009) Bimolecular reaction rates from ring polymer molecular dynamics. The Journal of Chemical Physics, 130 (17). 174713pp. doi:10.1063/1.3127145
Gubaev, Konstantin, Podryabinkin, Evgeny V., Shapeev, Alexander V. (2018) Machine learning of molecular properties: Locality and active learning. The Journal of Chemical Physics, 148 (24). 241727pp. doi:10.1063/1.5005095
 
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