Simple concentration-dependent pair interaction model for large-scale simulations of Fe-Cr alloys

Levesque, Maximilien; Martínez, E.; Fu, Chu‐Chun; Nastar, Maylise; Soisson, Frédéric

doi:10.1103/physrevb.84.184205

Cited by 68 publications

(65 citation statements)

References 64 publications

(166 reference statements)

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“…[35] and used to model FeCr surfaces in Ref. [12] also predicts chromium depletion from the surface (in this case two topmost layers instead of one as in this work).…”

Section: Monte Carlo Simulationsmentioning

confidence: 99%

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Segregation, precipitation, andα−α′phase separation in Fe-Cr alloys

et al. 2015

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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 ∼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 ∼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 Fe 0.95 Cr 0.05 and Fe 0.85 Cr 0.15 alloys. Initial oxidation of Fe-Cr was investigated experimentally at 10 −8 Torr pressure of the spectrometers showing intense Cr 2 O 3 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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“…[35] and used to model FeCr surfaces in Ref. [12] also predicts chromium depletion from the surface (in this case two topmost layers instead of one as in this work).…”

Section: Monte Carlo Simulationsmentioning

confidence: 99%

“…In rigid lattice MC simulations [12,20,[34][35][36][37] using Ising-type interaction the Hamiltonian must be made temperature dependent. Semiempirical potentials have been used in both Metropolis MC (MMC) [38][39][40] and kinetic MC (KMC) [9,[41][42][43][44][45][46][47] studies.…”

Section: B Large-scale Monte Carlo Simulationsmentioning

confidence: 99%

Segregation, precipitation, andα−α′phase separation in Fe-Cr alloys

et al. 2015

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“…It reflects a subtle compensation between the temperature dependence of the order energy, more specifically of the energy associated with magnetism, and the entropic effects. It was identified in the bulk as the cause of the anomalously steep solubility limit of the Fe-Cr alloy at low temperatures, and identified by Williams as an effect of magnetism 29,37 .…”

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confidence: 99%

“…29 . It is specifically designed to reproduce both (i) the whole experimental α-α phase diagram at all temperatures and compositions, and (ii) the change of sign of the mixing energies.…”

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confidence: 99%

Anomalous surface segregation profiles in ferritic Fe-Cr stainless steel

Levesque

2013

Phys. Rev. B

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The iron-chromium alloy and its derivatives are widely used for their remarkable resistance to corrosion, which only occurs in a narrow concentration range around 9 to 13 atomic percent chromium. Although known to be due to chromium enrichment of a few atoms thick layer at the surfaces, the understanding of its complex atomistic origin has been a remaining challenge. We report an investigation of the thermodynamics of such surfaces at the atomic scale by means of Monte Carlo simulations. We use a Hamiltonian which provides a parameterization of previous ab initio results and successfully describes the alloy's unusual thermodynamics. We report a strong enrichment in Cr of the surfaces for low bulk concentrations, with a narrow optimum around 12 atomic percent chromium, beyond which the surface composition decreases drastically. This behavior is explained by a synergy between (i) the complex phase separation in the bulk alloy, (ii) local phase transitions that tune the layers closest to the surface to an iron-rich state and inhibit the bulk phase separation in this region, and (iii) its compensation by a strong and non-linear enrichment in Cr of the next few layers. Implications with respect to the design of prospective nanomaterials are briefly discussed.PACS numbers: 64.75. Nx, 68.35.bd, 61.66.Dk, 64.70.kd, 81.30.Bx The iron-chromium alloy and its derivatives are inexpensive, have satisfactory mechanical properties and above all exhibit a remarkable resistance to corrosion: it is the most widely used class of alloy in the world. Its outstanding corrosion resistance is known for a century 1 to only occur in a narrow range of concentrations, around 10 atomic percent of chromium (at. % Cr) 2 . Their excellent properties make them candidate materials for future fusion nuclear reactors 3,4 , one of the reasons that induced a considerable amount of work on the various aspects of the Fe-Cr alloy both experimentally 5,6 and theoretically 7 .Corrosion resistance of stainless steels is due to the passivation of the material by an inert, chromium rich layer at the interface between the alloy and the environment, i.e. at the surfaces. Passivation is a phenomena inherent to how much Cr is located at the surfaces, which is a non-linear function of the bulk concentration 8 . In austenitic Fe-Cr, which only exists at high temperatures above ≈ 800 C and for less than ≈ 10 at. % Cr, the more chromium in the bulk, the more chromium in the surface and thus the more stainless the alloy. In ferritic Fe-Cr alloys, the picture is more complex. Without additive elements, the Cr content at which the alloy is passivated is narrow, from 9 to 13 at. % Cr, beyond which occurs an increase in the corrosion rate and a strong decrease in mechanical properties.This important property of stainless steels has been extensively studied, but its complex origin at the atomic scale has remained a missing understanding, subject to controversial findings: How chromium causes passivation, i.e. how it interacts and reacts with chemical elements coming fr...

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“…[4,5] Kinetics of coherent phase transformation have been successfully studied primarily using various broken bond models in fcc and bcc alloys using KMC method. [6][7][8][9][10][11][12][13][14][15][16][17] To the best of our knowledge, no such simulations were performed in HCP alloys. This paper focuses on the development and our implementation of the SLKMC method [18] and its application to the study of vacancy and Al atom diffusion in Mg matrix.…”

Section: Introductionmentioning

confidence: 99%

Self-learning kinetic Monte Carlo simulations of Al diffusion in Mg

Nandipati

Govind²,

Andersen³

et al. 2016

J. Phys.: Condens. Matter

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Abstract. Vacancy-mediated diffusion of an Al atom in pure Mg matrix is studied using the atomistic, on-lattice self-learning kinetic Monte Carlo (SLKMC) method. Activation barriers for vacancy-Mg and vacancy-Al atom exchange processes are calculated on-the-fly using the climbing image nudged-elastic band method and binary Mg-Al modified embedded-atom method interatomic potential. Diffusivities of an Al atom obtained from SLKMC simulations show the same behavior as observed in experimental and theoretical studies available in the literature, that is, Al atom diffuses faster within the basal plane than along the c−axis. Although, the effective activation barriers for Al-atom diffusion from SLKMC simulations are close to experimental and theoretical values, the effective prefactors are lower than those obtained from experiments. We present all the possible vacancy-Mg and vacancy-Al atom exchange processes and their activation barriers identified in SLKMC simulations. A simple mapping scheme to map an HCP lattice on to a simple cubic lattice is described, which enables the simulation of HCP lattice using on-lattice framework. We also present the pattern recognition scheme which is used in SLKMC simulations to identify the local Al atom configuration around a vacancy.

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Simple concentration-dependent pair interaction model for large-scale simulations of Fe-Cr alloys

Cited by 68 publications

References 64 publications

Segregation, precipitation, andα−α′phase separation in Fe-Cr alloys

Segregation, precipitation, andα−α′phase separation in Fe-Cr alloys

Anomalous surface segregation profiles in ferritic Fe-Cr stainless steel

Self-learning kinetic Monte Carlo simulations of Al diffusion in Mg

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