Search Results - "Novikov, Ivan S"

Constrained DFT-based magnetic machine-learning potentials for magnetic alloys: a case study of Fe–Al by Kotykhov, Alexey S., Gubaev, Konstantin, Hodapp, Max, Tantardini, Christian, Shapeev, Alexander V., Novikov, Ivan S.

“…We propose a machine-learning interatomic potential for multi-component magnetic materials. In this potential we consider magnetic moments as degrees of…”
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A machine-learning-based investigation on the mechanical/failure response and thermal conductivity of semiconducting BC2N monolayers by Mortazavi, Bohayra, Novikov, Ivan S., Shapeev, Alexander V.

“…Graphene-like lattices consisting of neighboring elements of boron, carbon and nitrogen are currently among the most attractive two-dimensional (2D)…”
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The MLIP package: moment tensor potentials with MPI and active learning by Novikov, Ivan S, Gubaev, Konstantin, Podryabinkin, Evgeny V, Shapeev, Alexander V

“…The subject of this paper is the technology (the 'how') of constructing machine-learning interatomic potentials, rather than science (the 'what' and 'why') of…”
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Exploring phononic properties of two-dimensional materials using machine learning interatomic potentials by Mortazavi, Bohayra, Novikov, Ivan S., Podryabinkin, Evgeny V., Roche, Stephan, Rabczuk, Timon, Shapeev, Alexander V., Zhuang, Xiaoying

“…•Machine-learning interatomic potentials (MLIPs) could accurately examine the phononic properties.•MLIPs can substitute the standard DFT-based methods for the…”
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Fitting to magnetic forces improves the reliability of magnetic Moment Tensor Potentials by Kotykhov, Alexey S., Gubaev, Konstantin, Sotskov, Vadim, Tantardini, Christian, Hodapp, Max, Shapeev, Alexander V., Novikov, Ivan S.

“…We developed a method for fitting machine-learning interatomic potentials with magnetic degrees of freedom, namely, magnetic Moment Tensor Potentials (mMTP)…”
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Efficient machine-learning based interatomic potentialsfor exploring thermal conductivity in two-dimensional materials by Mortazavi, Bohayra, Podryabinkin, Evgeny V, Novikov, Ivan S, Roche, Stephan, Rabczuk, Timon, Zhuang, Xiaoying, Shapeev, Alexander V

“…It is well-known that the calculation of thermal conductivity using classical molecular dynamics (MD) simulations strongly depends on the choice of the…”
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Computational study of pulsed neutron induced activation analysis of cargo by Barzilov, Alexander P., Novikov, Ivan S., Cooper, Brian

“…Pulsed neutron induced activation analysis is a nondestructive technique to detect threats hidden in bulk objects such as cargo pallets, trucks, etc. Isotopic…”
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Accelerating first-principles estimation of thermal conductivity by machine-learning interatomic potentials: A MTP/ShengBTE solution by Mortazavi, Bohayra, Podryabinkin, Evgeny V., Novikov, Ivan S., Rabczuk, Timon, Zhuang, Xiaoying, Shapeev, Alexander V.

“…Accurate evaluation of the thermal conductivity of a material can be a challenging task from both experimental and theoretical points of view. In particular…”
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Quantum modelling of magnetism in strongly correlated materials: Evaluating constrained DFT and the Hubbard model for Y114 by Tantardini, Christian, Fazylbekova, Darina, Levchenko, Sergey V., Novikov, Ivan S.

“…Transition-metal compounds represent a fascinating playground for exploring the intricate relationship between structural distortions, electronic properties,…”
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Towards reliable calculations of thermal rate constants: Ring polymer molecular dynamics for the OH + HBr → Br + H2O reaction by Novikov, Ivan S., Makarov, Edgar M., Suleimanov, Yury V., Shapeev, Alexander V.

“…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…”
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Towards reliable calculations of thermal rate constants: Ring polymer molecular dynamics for the OH + HBr → Br + H 2 O reaction by Novikov, Ivan S., Makarov, Edgar M., Suleimanov, Yury V., Shapeev, Alexander V.

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Assessing parameters for ring polymer molecular dynamics simulations at low temperatures: DH + H chemical reaction by Novikov, Ivan S., Suleimanov, Yury V., Shapeev, Alexander V.

“…[Display omitted] •RPMD rate constants for the reaction DH + H → D + H2 are reported.•RPMD simulation parameters should be carefully chosen at low…”
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Improving accuracy of interatomic potentials: more physics or more data? A case study of silica by Novikov, Ivan S., Shapeev, Alexander V.

“…In this paper we test two strategies to improving the accuracy of machine-learning potentials, namely adding more fitting parameters thus making use of large…”
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Accelerating Structure Prediction of Molecular Crystals using Actively Trained Moment Tensor Potential by Rybin, Nikita, Novikov, Ivan S, Shapeev, Alexander

“…Inspired by the recent success of machine-learned interatomic potentials for crystal structure prediction of the inorganic crystals, we present a methodology…”
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Interatomic Interaction Models for Magnetic Materials: Recent Advances by Kostiuchenko, Tatiana S, Shapeev, Alexander V, Novikov, Ivan S

“…Atomistic modeling is a widely employed theoretical method of computational materials science. It has found particular utility in the study of magnetic…”
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Quantum Modelling of Magnetism in Strongly Correlated Materials: Evaluating Constrained DFT and the Hubbard Model for Y114 by Tantardini, Christian, Fazylbekova, Darina, Levchenko, Sergey, Novikov, Ivan S

“…Transition-metal compounds represent a fascinating playground for exploring the intricate relationship between structural distortions, electronic properties,…”
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Fitting to magnetic forces improves the reliability of magnetic Moment Tensor Potentials by Kotykhov, Alexey S, Gubaev, Konstantin, Sotskov, Vadim, Tantardini, Christian, Hodapp, Max, Shapeev, Alexander V, Novikov, Ivan S

“…We developed a method for fitting machine-learning interatomic potentials with magnetic degrees of freedom, namely, magnetic Moment Tensor Potentials (mMTP)…”
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Assessing Parameters for Ring Polymer Molecular Dynamics Simulations at Low Temperatures: DH+H Chemical Reaction by Novikov, Ivan S, Suleimanov, Yury V, Shapeev, Alexander V

“…Ring polymer molecular dynamics (RPMD) is an accurate method for calculating thermal chemical reaction rates. It has recently been discovered that…”
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Towards reliable calculations of thermal rate constants: ring polymer molecular dynamics for the OH + HBr $\to$ Br + H$_2$O reaction by Novikov, Ivan S, Makarov, Edgar M, Shapeev, Alexander V, Suleimanov, Yury V

“…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…”
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Improving accuracy of interatomic potentials: more physics or more data? A case study of silica by Novikov, Ivan S, Shapeev, Alexander V

“…In this paper we test two strategies to improving the accuracy of machine-learning potentials, namely adding more fitting parameters thus making use of large…”
Get full text