17 citations · 56 across the 6 of their papers we have counts for
5 papers · 1 filter
Machine learning-based prediction of elastic properties of amorphous metal alloys
B. N. Galimzyanov, M. A. Doronina, A. V. Mokshin
The Young's modulus is the key mechanical property that determines the resistance of solids to tension/compression. In the present work, the correlation of the quantity wit…
Neural network as a tool for design of amorphous metal alloys with desired elastoplastic properties
B. N. Galimzyanov, M. A. Doronina, A. V. Mokshin
The development and implementation of the methods for designing amorphous metal alloys with desired mechanical properties is one of the most promising areas of modern materials sci…
Arrhenius Crossover Temperature of Glass-Forming Liquids Predicted by an Artificial Neural Network
Bulat N. Galimzyanov, Maria A. Doronina, Anatolii V. Mokshin
The Arrhenius crossover temperature, , corresponds to a thermodynamic state wherein the atomistic dynamics of a liquid becomes heterogeneous and cooperative; and the activat…
Unusual effect of high pressures on phase transformations in NiNb alloy
B. N. Galimzyanov, M. A. Doronina, A. V. Mokshin
Binary NiNb alloy belongs to the unique class of binary off-eutectic systems, which are able to form a bulk glassy state [L. Xia et al., J. Appl. Phys. 99 (2006) 0261…
Excellent glass former NiNb crystallizing under combined shear and ultra-high pressure
Bulat N. Galimzyanov, Maria A. Doronina, Anatolii V. Mokshin
Study of condensed matter in certain extreme conditions allows one to better understand the mechanisms of microscopic structural transformations and to develop materials with compl…