Geodesic
Short-range order in Fe-Cr alloys: simulation by the lattice Monte Carlo method
Vestnik Ûžno-Uralʹskogo gosudarstvennogo universiteta. Seriâ, Matematika, mehanika, fizika, Tome 11 (2019) no. 2, pp. 51-57 Cet article a éte moissonné depuis la source Math-Net.Ru

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Short-range order in Fe-Cr alloys was studied by the Monte Carlo method. The simulation was carried out in the framework of the Metropolis algorithm in LAMMPS software package. Simulation data analysis was carried out using Ovito data visualization and analysis software. The alloy model assumes that the lattice structure is fixed and that interactions exist between the first neighbors and the second neighbors. The FeCr interaction was determined using the Abell-Brenner-Tersoff interatomic interaction potential (ABOP). Various admixture concentrations of chromium interstitial in iron have been studied, namely, 5-50 at. %. The mixing energy of the Fe-Cr system was calculated for various concentrations of interstitial impurities. Calculations showed that the chosen interaction potential correctly simulates changes in the sign of the mixing energy as a function of Cr concentration. When used in Monte Carlo kinetic modeling, the potential correctly predicts decomposition of initially random Fe-Cr alloys, depending on Cr concentration. The Cowley short-range order parameter, which is used for quantitative assessment of the degree of order, has been determined. According to experiments, there is a strong tendency of ordering in distribution of Cr at low concentrations, which becomes evident in negative values of the short-range order parameters.
Mots-clés : solid solutions, Monte Carlo simulation
Keywords: mixing energy, chromium, short-range order. 
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     title = {Short-range order in {Fe-Cr} alloys: simulation by the lattice {Monte} {Carlo} method},
     journal = {Vestnik \^U\v{z}no-Uralʹskogo gosudarstvennogo universiteta. Seri\^a, Matematika, mehanika, fizika},
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G. D. Bairova; A. A. Mirzoev. Short-range order in Fe-Cr alloys: simulation by the lattice Monte Carlo method. Vestnik Ûžno-Uralʹskogo gosudarstvennogo universiteta. Seriâ, Matematika, mehanika, fizika, Tome 11 (2019) no. 2, pp. 51-57. http://geodesic.mathdoc.fr/item/VYURM_2019_11_2_a6/

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