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Alexander Shapeev
Alexander Shapeev
Skolkovo Institute of Science and Technology
Подтвержден адрес электронной почты в домене shapeev.com - Главная страница
Название
Процитировано
Процитировано
Год
Moment tensor potentials: A class of systematically improvable interatomic potentials
AV Shapeev
Multiscale Modeling & Simulation 14 (3), 1153-1173, 2016
9592016
Performance and cost assessment of machine learning interatomic potentials
Y Zuo, C Chen, X Li, Z Deng, Y Chen, J Behler, G Csányi, AV Shapeev, ...
The Journal of Physical Chemistry A 124 (4), 731-745, 2020
5762020
Active learning of linearly parametrized interatomic potentials
EV Podryabinkin, AV Shapeev
Computational Materials Science 140, 171-180, 2017
4742017
Exceptional piezoelectricity, high thermal conductivity and stiffness and promising photocatalysis in two-dimensional MoSi2N4 family confirmed by first-principles
B Mortazavi, B Javvaji, F Shojaei, T Rabczuk, AV Shapeev, X Zhuang
Nano Energy 82, 105716, 2021
3342021
The MLIP package: moment tensor potentials with MPI and active learning
IS Novikov, K Gubaev, EV Podryabinkin, AV Shapeev
Machine Learning: Science and Technology 2 (2), 025002, 2020
3272020
Accelerating crystal structure prediction by machine-learning interatomic potentials with active learning
EV Podryabinkin, EV Tikhonov, AV Shapeev, AR Oganov
Physical Review B 99 (6), 064114, 2019
3062019
Accelerating high-throughput searches for new alloys with active learning of interatomic potentials
K Gubaev, EV Podryabinkin, GLW Hart, AV Shapeev
Computational Materials Science 156, 148-156, 2019
2702019
First‐principles multiscale modeling of mechanical properties in graphene/borophene heterostructures empowered by machine‐learning interatomic potentials
B Mortazavi, M Silani, EV Podryabinkin, T Rabczuk, X Zhuang, ...
Advanced Materials 33 (35), 2102807, 2021
1732021
Machine learning of molecular properties: Locality and active learning
K Gubaev, EV Podryabinkin, AV Shapeev
The Journal of chemical physics 148 (24), 2018
1622018
Exploring phononic properties of two-dimensional materials using machine learning interatomic potentials
B Mortazavi, IS Novikov, EV Podryabinkin, S Roche, T Rabczuk, ...
Applied Materials Today 20, 100685, 2020
1482020
Machine-learning interatomic potentials enable first-principles multiscale modeling of lattice thermal conductivity in graphene/borophene heterostructures
B Mortazavi, EV Podryabinkin, S Roche, T Rabczuk, X Zhuang, ...
Materials Horizons 7 (9), 2359-2367, 2020
1382020
Impact of lattice relaxations on phase transitions in a high-entropy alloy studied by machine-learning potentials
T Kostiuchenko, F Körmann, J Neugebauer, A Shapeev
npj Computational Materials 5 (1), 55, 2019
1352019
Accelerating first-principles estimation of thermal conductivity by machine-learning interatomic potentials: A MTP/ShengBTE solution
B Mortazavi, EV Podryabinkin, IS Novikov, T Rabczuk, X Zhuang, ...
Computer Physics Communications 258, 107583, 2021
1162021
Machine-learned multi-system surrogate models for materials prediction
C Nyshadham, M Rupp, B Bekker, AV Shapeev, T Mueller, ...
npj Computational Materials 5 (1), 51, 2019
1132019
Young’s Modulus and Tensile Strength of Ti3C2 MXene Nanosheets As Revealed by In Situ TEM Probing, AFM Nanomechanical Mapping, and Theoretical …
KL Firestein, JE von Treifeldt, DG Kvashnin, JFS Fernando, C Zhang, ...
Nano Letters 20 (8), 5900-5908, 2020
1002020
Machine-learned interatomic potentials for alloys and alloy phase diagrams
CW Rosenbrock, K Gubaev, AV Shapeev, LB Pártay, N Bernstein, ...
npj Computational Materials 7 (1), 24, 2021
972021
Ab initio vibrational free energies including anharmonicity for multicomponent alloys
B Grabowski, Y Ikeda, P Srinivasan, F Körmann, C Freysoldt, AI Duff, ...
npj computational materials 5 (1), 80, 2019
922019
Deep elastic strain engineering of bandgap through machine learning
Z Shi, E Tsymbalov, M Dao, S Suresh, A Shapeev, J Li
Proceedings of the National Academy of Sciences 116 (10), 4117-4122, 2019
912019
Accessing thermal conductivity of complex compounds by machine learning interatomic potentials
P Korotaev, I Novoselov, A Yanilkin, A Shapeev
Physical Review B 100 (14), 144308, 2019
892019
Analysis of boundary conditions for crystal defect atomistic simulations
V Ehrlacher, C Ortner, AV Shapeev
Archive for Rational Mechanics and Analysis 222, 1217-1268, 2016
892016
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