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Structure and Conformational Analysis of 5-Methyl-2,2-diphenyl-1,3-dioxane
Kuramshina, A.E., Khalikov, R.A., Kataev, V.A., Tyumkina, T.V., Meshcheryakova, E.S., Khalilov, L.M., Kuznetsov, V.V. (2020)
computer simulation
STRUCTURE AND CONFORMATIONAL ANALYSIS OF 5,5-BIS(BROMOMETHYL)-2,2-DIPHENYL-1,3-DIOXANE
KHAZHIEV, S.Y., KHUSAINOV, M.A., KUZNETSOV, V.V., KHALIKOV, R.A., KATAEV, V.A., TYUMKINA, T.V., MESHCHERYAKOVA, E.S., KHALILOV, L.M. (2020)
-temperature NMR data, the interconversion barrier amounts to 8.9 kcal/mol. The ring inversion path was simulated
TWO-DIMENSIONAL DISCRETE BREATHERS IN FCC METALS
BACHURINA, O.V., KUDREYKO, A.A. (2020)
by means of molecular dynamics simulations in defect-free single crystals of fcc metals (Al, Cu and Ni
СТРОЕНИЕ И КОНФОРМАЦИОННЫЙ АНАЛИЗ 5,5-БИС(БРОММЕТИЛ)-2,2-ДИФЕНИЛ- 1,3-ДИОКСАНА
STRUCTURE AND CONFORMATIONAL ANALYSIS OF 5,5-BIS(BROMOMETHYL)-2,2-DIPHENYL-1,3-DIOXANE
Хажиев, Ш.Ю., Хусаинов, М.А., Халиков, Р.А., Катаев, В.А., Тюмкина, Т.В., Мещерякова, Е.С., Халилов, Л.М., Кузнецов, В.В., KHAZHIEV S.Y., KHUSAINOV M.A., KUZNETSOV V.V., KHALIKOV R.A., KATAEV V.A., TYUMKINA T.V., MESHCHERYAKOVA E.S., KHALILOV L.M. (2020)
COMPUTER SIMULATION
СТРОЕНИЕ И КОНФОРМАЦИОННЫЙ АНАЛИЗ 5,5-БИС(БРОММЕТИЛ)-2,2-ДИФЕНИЛ- 1,3-ДИОКСАНА
STRUCTURE AND CONFORMATIONAL ANALYSIS OF 5,5-BIS(BROMOMETHYL)-2,2-DIPHENYL-1,3-DIOXANE
ХАЖИЕВ, Ш.Ю., ХУСАИНОВ, М.А., ХАЛИКОВ, Р.А., КАТАЕВ, В.А., ТЮМКИНА, Т.В., МЕЩЕРЯКОВА, Е.С., ХАЛИЛОВ, Л.М., КУЗНЕЦОВ, В.В., Khazhiev S.Y., Khusainov M.A., Kuznetsov V.V., Khalikov R.A., Kataev V.A., Tyumkina T.V., Meshcheryakova E.S., Khalilov L.M. (2020)
COMPUTER SIMULATION
SPHERICALLY LOCALIZED DISCRETE BREATHERS IN BCC METALS V AND NB
KRYLOVA, K.A., DMITRIEV, S.V., LOBZENKO, I.P., SEMENOV, A.S., KUDREYKO, A.A. (2020)
reported in fcc Ni and bcc Nb by Haas et al. in 2011 based on molecular dynamics simulations. Here we use a
Supersonic voidions in 2D Morse lattice
SHEPELEV, I.A., DMITRIEV, S.V., KUDREIKO, A.A., VELARDE, M.G., KORZNIKOVA, E.A. (2020)
ATOMISTIC SIMULATIONS
Identification of Pathological Formations in the Lungs Based on Machine Learning Methods
Shakhmametova, G.R., Vakkazov, N.O., Zulkarneev, R.KH. (2020)
of computed lung tomography. The recognition is carried out in two stages: segmentation of lung image
Reliability analysis of power distribution network based on Pso-DBN
Shan, H., Sun, Y., Zhang, W., Kudreyko, A., Ren, L. (2020)
the characteristics of large-scale parallel processing and self-learning, a deep belief network (DBN) simulation model
Design and Optimization of Plasmon Resonance Sensor Based on Micro-Nano Symmetrical Localized Surface
Fengyu, Yin, Jin, Liu, Haima, Yang, Aleksey, Kudreyko, Bo, Huang (2020)
, using a finite difference time domain (FDTD) simulation system. When the incident angle is 42 degrees

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