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R E Ryltsev

Showing results (1-10 of 14) with videos related to

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Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics|December 17, 2013
Multistage structural evolution in simple monatomic supercritical fluids: superstable tetrahedral local orderR E Ryltsev, N M Chtchelkatchev
Journal of Physics. Condensed Matter : an Institute of Physics Journal|July 22, 2022
Freezing in two-length-scale systems: complexity, universality and predictionR E Ryltsev, N M Chtchelkatchev
The Journal of Chemical Physics|October 3, 2014
Hydrodynamic anomalies in supercritical fluidR E Ryltsev, N M Chtchelkatchev
Journal of Physics. Condensed Matter : an Institute of Physics Journal|October 16, 2020
Structure of the simple harmonic-repulsive system in liquid and glassy states studied by the triple correlation functionV A Levashov, R E Ryltsev, N M Chtchelkatchev
The Journal of Chemical Physics|October 8, 2018
Polytetrahedral structure and glass-forming ability of simulated Ni-Zr alloysB A Klumov, R E Ryltsev, N M Chtchelkatchev
Physical Review Letters|February 7, 2013
Superfragile glassy dynamics of a one-component system with isotropic potential: competition of diffusion and frustrationR E Ryltsev, N M Chtchelkatchev, V N Ryzhov
The Journal of Chemical Physics|November 1, 2024
Transfer learning for accurate description of atomic transport in Al-Cu meltsE O Khazieva, N M Chtchelkatchev, R E Ryltsev
Journal of Physics. Condensed Matter : an Institute of Physics Journal|February 8, 2020
Effect of copper concentration on the structure and properties of Al-Cu-Fe and Al-Cu-Ni meltsL V Kamaeva, R E Ryltsev, A A Suslov, et al.
Physical Review. E|December 17, 2020
Deep machine learning interatomic potential for liquid silicaI A Balyakin, S V Rempel, R E Ryltsev, et al.
Physical Review. E|December 23, 2025
Accuracy and limitations of machine-learned interatomic potentials for magnetic systems: A case study on Fe-Cr-CE O Khazieva, N M Chtchelkatchev, N N Katkov, et al.
Pageof 2

Showing results (1-10 of 14) with videos related to

Sort By:
Pageof 2
Physical Review. E, Statistical, Nonlinear, and Soft Matter Physics|December 17, 2013
Multistage structural evolution in simple monatomic supercritical fluids: superstable tetrahedral local orderR E Ryltsev, N M Chtchelkatchev
Journal of Physics. Condensed Matter : an Institute of Physics Journal|July 22, 2022
Freezing in two-length-scale systems: complexity, universality and predictionR E Ryltsev, N M Chtchelkatchev
The Journal of Chemical Physics|October 3, 2014
Hydrodynamic anomalies in supercritical fluidR E Ryltsev, N M Chtchelkatchev
Journal of Physics. Condensed Matter : an Institute of Physics Journal|October 16, 2020
Structure of the simple harmonic-repulsive system in liquid and glassy states studied by the triple correlation functionV A Levashov, R E Ryltsev, N M Chtchelkatchev
The Journal of Chemical Physics|October 8, 2018
Polytetrahedral structure and glass-forming ability of simulated Ni-Zr alloysB A Klumov, R E Ryltsev, N M Chtchelkatchev
Physical Review Letters|February 7, 2013
Superfragile glassy dynamics of a one-component system with isotropic potential: competition of diffusion and frustrationR E Ryltsev, N M Chtchelkatchev, V N Ryzhov
The Journal of Chemical Physics|November 1, 2024
Transfer learning for accurate description of atomic transport in Al-Cu meltsE O Khazieva, N M Chtchelkatchev, R E Ryltsev
Journal of Physics. Condensed Matter : an Institute of Physics Journal|February 8, 2020
Effect of copper concentration on the structure and properties of Al-Cu-Fe and Al-Cu-Ni meltsL V Kamaeva, R E Ryltsev, A A Suslov, et al.
Physical Review. E|December 17, 2020
Deep machine learning interatomic potential for liquid silicaI A Balyakin, S V Rempel, R E Ryltsev, et al.
Physical Review. E|December 23, 2025
Accuracy and limitations of machine-learned interatomic potentials for magnetic systems: A case study on Fe-Cr-CE O Khazieva, N M Chtchelkatchev, N N Katkov, et al.
Pageof 2