activity
20132026
most citedSuperfragile glassy dynamics of onecomponent system with isotropic potential: competition of diffusion and frustration

59 citations · 375 across the 26 of their papers we have counts for

collaborators

24 papers

cond-mat.mtrl-sci2026

Adaptive fine-tuning of foundation models for crystal structure prediction: Discovery of high-pressure phases in the CaFeNi system

N. M. Chtchelkatchev, M. V. Magnitskaya, R. E. Ryltsev

The prediction of crystal structures is a key challenge in chemistry and materials science, but evolutionary crystal structure prediction (CSP) remains computationally expensive be…

cond-mat.mtrl-sci2025

Accuracy and Limitations of Machine-Learned Interatomic Potentials for Magnetic Systems: A Case Study on Fe-Cr-C

E. O. Khazieva, N. M. Chtchelkatchev, R. E. Ryltsev

Machine-learned interatomic potentials (MLIPs) have become the gold standard for atomistic simulations, yet their extension to magnetic materials remains challenging because spin f…

cond-mat.mtrl-sci2023★ 9 cited

Local structure, thermodynamics, and melting curve of boron phosphide at high pressures by deep learning-driven ab initio simulations

N. M. Chtchelkatchev, R. E. Ryltsev, M. V. Magnitskaya +4

Boron phosphide (BP) is a (super)hard semiconductor constituted of light elements, which is promising for high demand applications at extreme conditions. The behavior of BP at high…

cond-mat.str-el2022★ 17 cited

Ground-state structure, orbital ordering and metal-insulator transition in double-perovskite PrBaMn2O6

Sergey V. Streltsov, R. E. Ryltsev, N. M. Chtchelkatchev

In recent years, A-site ordered half-doped double-perovskite manganites (R=rare earth) have attracted much attention due to their remarkable physical properties an…

cond-mat.mtrl-sci2021

Deep machine learning potentials for multicomponent metallic melts: development, predictability and compositional transferability

R. E. Ryltsev, N. M. Chtchelkatchev

The use of machine learning interatomic potentials (MLIPs) in simulations of materials is a state-of-the-art approach, which allows achieving nearly \textit{ab initio} accuracy wit…

cond-mat.soft2020★ 5 cited

Structure of the simple harmonic-repulsive system in liquid and glassy states studied by the triple correlation function

V. A. Levashov, R. E. Ryltsev, N. M. Chtchelkatchev

An efficient description of the structures of liquids and, in particular, the structural changes that happen with liquids on supercooling remains to be a challenge. The systems com…