| 1. |
- Kuronen, A., et al.
(författare)
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Segregation, precipitation, and alpha-alpha ' phase separation in Fe-Cr alloys
- 2015
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Ingår i: Physical Review B. Condensed Matter and Materials Physics. - : American Physical Society. - 1098-0121 .- 1550-235X. ; 92:21
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Tidskriftsartikel (refereegranskat)abstract
- Iron-chromium alloys, the base components of various stainless steel grades, have numerous technologically and scientifically interesting properties. However, these features are not yet sufficiently understood to allow their full exploitation in technological applications. In this work, we investigate segregation, precipitation, and phase separation in Fe-Cr systems analyzing the physical mechanisms behind the observed phenomena. To get a comprehensive picture of Fe-Cr alloys as a function of composition, temperature, and time the present investigation combines Monte Carlo simulations using semiempirical interatomic potential, first-principles total energy calculations, and experimental spectroscopy. In order to obtain a general picture of the relation of the atomic interactions and properties of Fe-Cr alloys in bulk, surface, and interface regions several complementary methods have to be used. Using the exact muffin-tin orbitals method with the coherent potential approximation (CPA-EMTO) the effective chemical potential as a function of Cr content (0-15 at. % Cr) is calculated for a surface, second atomic layer, and bulk. At similar to 10 at. % Cr in the alloy the reversal of the driving force of a Cr atom to occupy either bulk or surface sites is obtained. The Cr-containing surfaces are expected when the Cr content exceeds similar to 10 at. %. The second atomic layer forms about a 0.3 eV barrier for the migration of Cr atoms between the bulk and surface atomic layer. To get information on Fe-Cr in larger scales we use semiempirical methods. However, for Cr concentration regions less than 10 at. %, the ab initio (CPA-EMTO) result of the important role of the second atomic layer to the surface is not reproducible from the large-scale Monte Carlo molecular dynamics (MCMD) simulation. On the other hand, for the nominal concentration of Cr larger than 10 at. % the MCMD simulations show the precipitation of Cr into isolated pockets in bulk Fe-Cr and the existence of the upper limit of the solubility of Cr into Fe layers in Fe/Cr layer systems. For high Cr concentration alloys the performed spectroscopic measurements support the MCMD simulations. Hard x-ray photoelectron spectroscopy and Auger electron spectroscopy investigations were carried out to explore Cr segregation and precipitation in the Fe/Cr double layer and Fe0.95Cr0.05 and Fe0.85Cr0.15 alloys. Initial oxidation of Fe-Cr was investigated experimentally at 10(-8) Torr pressure of the spectrometers showing intense Cr2O3 signal. Cr segregation and the formation of Cr-rich precipitates were traced by analyzing the experimental atomic concentrations and chemical shifts with respect to annealing time, Cr content, and kinetic energy of the exited electron.
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| 2. |
- Levämäki, Henrik, et al.
(författare)
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An automated algorithm for reliable equation of state fitting of magnetic systems
- 2019
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Ingår i: Computational materials science. - : Elsevier. - 0927-0256 .- 1879-0801. ; 156, s. 121-128
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Tidskriftsartikel (refereegranskat)abstract
- In computational physics and materials science ground-state properties are often extracted from an equation of state fit to energy-volume data. Magnetic systems often have multiple magnetic phases present in the energy-volume data, which poses a challenge for the fitting approach because the results are sensitive to the selection of included fitting points. This is because practically all popular equation of state fitting functions, such as Murnaghan and Birch-Murnaghan, assume just one phase and therefore cannot correctly fit magnetic energy-volume data that contains multiple phases. When fitting magnetic energy-volume data it is therefore important to select the range of fitting points in such a way that only points from the one relevant phase are included. We present a simple algorithm that makes the point selection automatically. Selecting fitting points automatically removes human bias and should also be useful for large-scale projects where selecting all fitting points by hand is not feasible.
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