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Your search keyword '"Korolev, D. S."' showing total 137 results
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137 results on '"Korolev, D. S."'

1. Stochastic resonance in a metal-oxide memristive device

Author

Mikhaylov, A. N., Guseinov, D. V., Belov, A. I., Korolev, D. S., Shishmakova, V. A., Koryazhkina, M. N., Filatov, D. O., Gorshkov, O. N., Maldonado, D., Alonso, F. J., Roldan, J. B., Krichigin, A. V., Agudov, N. V., Dubkov, A. A., Carollo, A., and Spagnolo, B.

Subjects
Condensed Matter - Mesoscale and Nanoscale Physics
Abstract

The stochastic resonance phenomenon has been studied experimentally and theoretically for a state-of-art metal-oxide memristive device based on yttria-stabilized zirconium dioxide and tantalum pentoxide, which exhibits bipolar filamentary resistive switching of anionic type. The effect of white Gaussian noise superimposed on the sub-threshold sinusoidal driving signal is analyzed through the time series statistics of the resistive switching parameters, the spectral response to a periodic perturbation and the signal-to-noise ratio at the output of the nonlinear system. The stabilized resistive switching and the increased memristance response are revealed in the observed regularities at an optimal noise intensity corresponding to the stochastic resonance phenomenon and interpreted using a stochastic memristor model taking into account an external noise source added to the control voltage. The obtained results clearly show that noise and fluctuations can play a constructive role in nonlinear memristive systems far from equilibrium.

Published
2024
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2. Ion-Beam Modification of Metastable Gallium Oxide Polymorphs

Author

Tetelbaum, D. I., Nikolskaya, A. A., Korolev, D. S., Belov, A. I., Trushin, V. N., Dudin, Yu. A., Mikhaylov, A. N., Pechnikov, A. I., Scheglov, M. P., Nikolaev, V. I., and Gogova, D.

Subjects
Condensed Matter - Materials Science, Physics - Applied Physics
Abstract

Gallium oxide with a corundum structure ({\alpha}-Ga2O3) has recently attracted great attention in view of electronic and photonic applications due to its unique properties including a wide band gap exceeding that of the most stable beta phase (\b{eta}-Ga2O3). However, the lower thermal stability of the {\alpha}-phase at ambient conditions in comparison with the \b{eta}-phase requires careful investigation of its resistance to other external influences such as ion irradiation, ion doping, etc. In this work, the structural changes under the action of Al+ ion irradiation have been investigated for a polymorphic gallium oxide layers grown by hydride vapor phase epitaxy on c-plane sapphire and consisting predominantly of {\alpha}-phase with inclusions of {\alpha}(\k{appa})-phase. It is established by the X-ray diffraction technique that inclusions of {\alpha}(\k{appa})-phase in the irradiated layer undergo the expansion along the normal to the substrate surface, while there is no a noticeable deformation for the {\alpha}-phase. This speaks in favor of the different radiation tolerance of various Ga2O3 polymorphs, especially the higher radiation tolerance of the {\alpha}-phase. This fact should be taken into account when utilizing ion implantation to modify gallium oxide properties in terms of development of efficient doping strategies.

Published
2021

4. Towards Hardware Implementation of Double-Layer Perceptron Based on Metal-Oxide Memristive Nanostructures

Author

Mikhaylov, A. N., Morozov, O. A., Ovchinnikov, P. E., Antonov, I. N., Belov, A. I., Korolev, D. S., Koryazhkina, M. N., Sharapov, A. N., Gryaznov, E. G., Gorshkov, O. N., and Kazantsev, V. B.

Subjects
Computer Science - Emerging Technologies, Physics - Applied Physics
Abstract

Construction and training principles have been proposed and tested for an artificial neural network based on metal-oxide thin-film nanostructures possessing bipolar resistive switching (memristive) effect. Experimental electronic circuit of neural network is implemented as a double-layer perceptron with a weight matrix composed of 32 memristive devices. The network training algorithm takes into account technological variations of the parameters of memristive nanostructures. Despite the limited size of weight matrix the developed neural network model is well scalable and capable of solving nonlinear classification problems.

Published
2017

29. Non-equilibrium methods for synthesis and modification of gallium oxide

Author

Nikolskaya, A A, primary, Korolev, D S, additional, Mikhaylov, A N, additional, Mullagaliev, T D, additional, Chigirinsky, Yu I, additional, Belov, A I, additional, Nezhdanov, A V, additional, Trushin, V N, additional, Nikolichev, D E, additional, Almaev, A V, additional, Giulian, R, additional, Kumar, M, additional, and Tetelbaum, D I, additional

Published
2021
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38. Mathematical intellectual algorithm for determining the fire hazard parameters of oil and oil refining products.

Author

Korolev, D. S., Vytovtov, A. V., Odnolko, A. A., Kargashilov, D. V., and Sitnikov, I. V.

Subjects
*ALGORITHMS, *PETROLEUM refining, *DEEP learning, *COMPUTER simulation, *HAZARDS, *FIRE detectors
Abstract

To improve the accuracy of the obtained values when predicting the fire hazardous properties of organic substances, it was decided to modify the existing algorithm, supplementing it with deep learning technology. Verification of the data was carried out based on some reference and practical data. It was found that the values obtained in the course of computer simulation provide a satisfactory error, which means that the data obtained can be used in practice. [ABSTRACT FROM AUTHOR]

Published
2021
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46. Structural and emitting properties of Zinc Oxide nanocrystals synthesized by high-fluence ion implantation

Author

Parkhomenko, I. N., Vlasukova, L. A., Komarov, F. F., Makhavikou, M., Milchanin, O. V., Wendler, E., Ronning, C., Zaph, M., and Korolev, D. S.

Subjects
ЕСТЕСТВЕННЫЕ И ТОЧНЫЕ НАУКИ::Физика [ЭБ БГУ]
Abstract

Секция 4. Формирование наноматериалов и наноструктур = Section 4. Formation of Nanomaterials and Nanostructures Samples of SiO2 (600 nm)/Si have been implanted with Zn ions (140 keV, 5×10 16 cm-2) and O ions (50 keV, 5×10 16 cm-2) at room temperature and afterwards annealed at 750ºС for 120 min in air ambient. The Zn depth distribution profiles of the implanted and annealed samples were analyzed by Rutherford backscattering spectroscopy (RBS). The structural and light emitting properties of the annealed samples were studied using TEM in “plan-view” geometry as well as electron micro-diffraction and photoluminescence (PL) at low (4 K) and room temperatures. The RBS analysis has revealed the bimodal shape of the Zn concentration profile. TEM analysis shows a non-uniform Zn-based cluster size distribution after annealing. The near-surface (0-60 nm) layer contains small clusters (2-11 nm). The large clusters (up to 35 nm) and clusters covered with oxide shells as well as and the secondary defects have been formed in the depth of 60-120 nm. The deepest implanted layer (120 - 200 nm) layer contains small nanoclusters with sizes of 5-10 nm. The crystal structure of the synthesized ZnO clusters is confirmed by the presence of narrow rings in diffraction patterns. Room-temperature PL spectrum exhibits the intensive deep level emission (DLE) in visible spectral range with dominant orange band (2.1 eV) and sharp weak near band edge (NBE) emission at 3.244 eV. At low-temperature (4.2 K) UV band dominates in PL spectrum which consists of two intense peaks at 3.324 and 3.274 eV and some narrow bands in blue-violet range attributed to phonon replicas of these bands. The crucial role of oxygen interstitials in radiative recombination is discussed. The work was supported by the Belarusian Republican Foundation for Fundamental Research, grant no. T19RM-041 and Russian Foundation for Basic Research (RFBR) (19-57-04005).

Published
2019

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