Vladimir P. Antropov

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Advanced materials characterization techniques with ever-growing data acquisition speed and storage capabilities represent a challenge in modern materials science, and new procedures to quickly assess and analyze the data are needed. Machine learning approaches are effective in reducing the complexity of data and rapidly homing in on the underlying trend in(More)
The electronic structure and magnetic properties of pure and doped Fe 16 N 2 systems have been studied in the local-density (LDA) and quasiparticle self-consistent GW approximations. The GW magnetic moment of pure Fe 16 N 2 is somewhat larger compared to LDA but not anomalously large. The effects of doping on magnetic moment and exchange coupling were(More)
The electronic structure and numerous magnetic properties of MnBi magnetic systems are investigated using local spin density approximation (LSDA) with on-cite Coulomb correlations (LSDA+U) included. We show that the inclusion of Coulomb correlations provides a much better description of equilibrium magnetic moments on Mn atoms as well as the magnetic(More)
Solving the crystal structures of novel phases with nanoscale dimensions resulting from rapid quenching is difficult due to disorder and competing polymorphic phases. Advances in computer speed and algorithm sophistication have now made it feasible to predict the crystal structure of an unknown phase without any assumptions on the Bravais lattice type, atom(More)
The origins of the anomalous temperature dependence of magnetocrystalline anisotropy in (Fe_{1-x}Co_{x})_{2}B alloys are elucidated using first-principles calculations within the disordered local moment model. Excellent agreement with experimental data is obtained. The anomalies are associated with the changes in band occupations due to Stoner-like band(More)
A first-principles approach to the construction of concentration-temperature magnetic phase diagrams of metallic alloys is presented. The method employs self-consistent total energy calculations based on the coherent potential approximation for partially ordered and noncollinear magnetic states and is able to account for competing interactions and multiple(More)
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