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Exact ab initio transport coefficients in bcc Fe-X (X=Cr, Cu, Mn, Ni, P, Si) dilute alloys
KTH, School of Engineering Sciences (SCI), Physics, Reactor Physics.ORCID iD: 0000-0003-0562-9070
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2014 (English)In: Physical Review B. Condensed Matter and Materials Physics, ISSN 1098-0121, E-ISSN 1550-235X, Vol. 90, no 10, 104203- p.Article in journal (Refereed) Published
Abstract [en]

Defect-driven diffusion of impurities is the major phenomenon leading to formation of embrittling nanoscopic precipitates in irradiated reactor pressure vessel (RPV) steels. Diffusion depends strongly on the kinetic correlations that may lead to flux coupling between solute atoms and point defects. In this work, flux coupling phenomena such as solute drag by vacancies and radiation-induced segregation at defect sinks are systematically investigated for six bcc iron-based dilute binary alloys, containing Cr, Cu, Mn, Ni, P, and Si impurities, respectively. First, solute-vacancy interactions and migration energies are obtained by means of ab initio calculations; subsequently, self-consistent mean field theory is employed in order to determine the exact Onsager matrix of the alloys. This innovative multiscale approach provides a more complete treatment of the solute-defect interaction than previous multifrequency models. Solute drag is found to be a widespread phenomenon that occurs systematically in ferritic alloys and is enhanced at low temperatures (as for instance RPV operational temperature), as long as an attractive solute-vacancy interaction is present, and that the kinetic modeling of bcc alloys requires the extension of the interaction shell to the second-nearest neighbors. Drag occurs in all alloys except Fe(Cr); the transition from dragging to nondragging regime takes place for the other alloys around (Cu, Mn, Ni) or above (P, Si) the Curie temperature. As far as only the vacancy-mediated solute migration is concerned, Cr depletion at sinks is foreseen by the model, as opposed to the other impurities which are expected to enrich up to no less than 1000 K. The results of this study confirm the current interpretation of the hardening processes in ferritic-martensitic steels under irradiation.

Place, publisher, year, edition, pages
2014. Vol. 90, no 10, 104203- p.
Keyword [en]
Radiation-Induced Segregation, Pressure-Vessel Steels, Augmented-Wave Method, Monte-Carlo Approach, Alpha-Iron, Phenomenological Coefficients, Positron-Annihilation, Ultrasoft Pseudopotentials, Atomistic Simulations, Multicomponent Alloy
National Category
Physical Sciences
URN: urn:nbn:se:kth:diva-157221DOI: 10.1103/PhysRevB.90.104203ISI: 000344014700002ScopusID: 2-s2.0-84907478712OAI: diva2:769793

QC 20141209

Available from: 2014-12-09 Created: 2014-12-08 Last updated: 2015-11-23Bibliographically approved
In thesis
1. Multiscale modeling of atomic transport phenomena in ferritic steels
Open this publication in new window or tab >>Multiscale modeling of atomic transport phenomena in ferritic steels
2015 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Defect-driven transport of impurities plays a key role in the microstructure evolution of alloys, and has a great impact on the mechanical properties at the macroscopic scale. This phenomenon is greatly enhanced in irradiated materials because of the large amount of radiation-induced crystal defects (vacancies and interstitials). For instance, the formation of nanosized solute clusters in neutron-irradiated reactor pressure vessel (RPV) ferritic steels has been shown to hinder dislocation motion and induce hardening and embrittlement. In Swedish RPV steels, this mechanical-property degradation is enhanced by the high content of manganese and nickel impurities. It has been suggested that the formation of Mn-Ni-rich clusters (which contain also Cu, Si, and P) might be the outcome of a dynamic process, where crystal defects act both as nucleation sites and solute carriers. Solute transport by point defects is therefore a crucial mechanism to understand the origin and the dynamics of the clustering process.

The first part of this work aims at modeling solute transport by point defects in dilute iron alloys, to identify the intrinsic diffusion mechanisms for a wide range of impurities. Transport and diffusion coefficients are obtained by combining accurate ab initio calculations of defect transition rates with an exact mean-field model. The results show that solute drag by single vacancies is a common phenomenon occurring at RPV temperature (about 300 °C) for all impurities found in the solute clusters, and that transport of phosphorus and manganese atoms is dominated by interstitial-type defects. These transport tendencies confirm that point defects can indeed carry impurities towards nucleated solute clusters. Moreover, the obtained flux-coupling tendencies can also explain the observed radiation-induced solute enrichment on grain boundaries and dislocations.

In the second part of this work, the acquired knowledge about solute-transport mechanisms is transferred to kinetic Monte Carlo (KMC) models, with the aim of simulating the RPV microstructure evolution. Firstly, the needed parameters in terms of solute-defect cluster stability and mobility are calculated by means of dedicated KMC simulations. Secondly, an innovative approach to the prediction of transition rates in complex multicomponent alloys is introduced. This approach relies on a neural network based on ab initio-computed migration barriers. Finally, the evolution of the Swedish RPV steels is simulated in a "gray-alloy" fashion, where impurities are introduced indirectly as a modification of the defect-cluster mobilities. The latter simulations are compared to the experimental characterization of the Swedish RPV surveillance samples, and confirm the possibility that solute clusters might form on small interstitial clusters.

In conclusion, this work identifies from a solid theoretical perspective the atomic-transport phenomena underlying the formation of embrittling nanofeatures in RPV steels. In addition, it prepares the ground for the development of predictive KMC tools that can simulate the microstructure evolution of a wide variety of irradiated alloys. This is of great interest not only for reactor pressure vessels, but also for many other materials in extreme environments.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2015. xvii, 90 p.
TRITA-FYS, ISSN 0280-316X ; 2015:80
diffusion, impurities, iron, metals, kinetic Monte Carlo, ab initio, mean field, defects, embrittlement, reactor pressure vessel, neural networks
National Category
Condensed Matter Physics
Research subject
urn:nbn:se:kth:diva-177525 (URN)978-91-7595-764-7 (ISBN)
Public defence
2015-12-11, Svedberg Hall, Room FD5, Albanova Universtitetscentrum, Roslagstullsbacken 21, Stockholm, 13:00 (English)
Göran Gustafsson Foundation for promotion of scientific research at Uppala University and Royal Institute of TechnologyVattenfall ABEU, FP7, Seventh Framework Programme

QC 20151123

Available from: 2015-11-23 Created: 2015-11-23 Last updated: 2015-11-24Bibliographically approved

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