9 citations · 15 across the 4 of their papers we have counts for
4 papers
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…
A machine learning potential-based generative algorithm for on-lattice crystal structure prediction
Vadim Sotskov, Alexander V. Shapeev, Evgeny V. Podryabinkin
We propose a method for crystal structure prediction based on a new structure generation algorithm and on-lattice machine learning interatomic potentials. Our algorithm generates t…
Machine-learning Driven Synthesis of TiZrNbHfTaC5 High-Entropy Carbide
Alexander Ya. Pak, Vadim Sotskov, Arina A. Gumovskaya +6
Synthesis of high-entropy carbides (HEC) requires high temperatures that can be provided by electric arc plasma method. However, the formation temperature of a single-phase sample…
Modelling Surface Segregation in Compositionally Complex Alloys with Ab-Initio Accuracy
Alberto Ferrari, Vadim Sotskov, Alexander V. Shapeev +1
Compositionally complex alloys or concentrated solid solutions are the latest frontier in catalyst design, but mixing different elements in one catalyst may result in surface segre…