9 citations · 11 across the 8 of their papers we have counts for
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Actively-trained magnetic Moment Tensor Potentials for mechanical, dynamical, and thermal properties of paramagnetic CrN
Alexey S. Kotykhov, Max Hodapp, Christian Tantardini +4
We present a protocol for automated fitting of magnetic Moment Tensor Potential explicitly including magnetic moments in its functional form. For the fitting of this potential we u…
Accelerating Structure Prediction of Molecular Crystals using Actively Trained Moment Tensor Potential
Nikita Rybin, Ivan S. Novikov, Alexander Shapeev
Inspired by the recent success of machine-learned interatomic potentials for crystal structure prediction of the inorganic crystals, we present a methodology that exploits Moment T…
Interatomic Interaction Models for Magnetic Materials: Recent Advances
Tatiana S. Kostiuchenko, Alexander V. Shapeev, Ivan S. Novikov
Atomistic modeling is a widely employed theoretical method of computational materials science. It has found particular utility in the study of magnetic materials. Initially, magnet…
Fitting to magnetic forces improves the reliability of magnetic Moment Tensor Potentials
Alexey S. Kotykhov, Konstantin Gubaev, Vadim Sotskov +4
We developed a method for fitting machine-learning interatomic potentials with magnetic degrees of freedom, namely, magnetic Moment Tensor Potentials (mMTP). The main feature of ou…
Quantum Modelling of Magnetism in Strongly Correlated Materials: Evaluating Constrained DFT and the Hubbard Model for Y114
Christian Tantardini, Darina Fazylbekova, Sergey Levchenko +1
Transition-metal compounds represent a fascinating playground for exploring the intricate relationship between structural distortions, electronic properties, and magnetic behaviour…