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Ab-initio based modeling of precipitation in Al–(Sc,Zr) alloy. Formation and stability of a core–shell structure
National Research Centre ”Kurchatov Institute”, 123182, Moscow, Russia; Moscow Institute of Physics and Technology (State University), 141700, Dolgoprudny, Moscow Region, Russia.ORCID iD: 0000-0001-6077-8445
Luleå University of Technology, Department of Engineering Sciences and Mathematics, Material Science. Laboratory for Mechanics of Gradient Nanomaterials, Nosov Magnitogorsk State Technical University, Magnitogorsk 455000, Russia.ORCID iD: 0000-0001-8629-5193
Institute of Metal Physics, Ural Division RAS, Ekaterinburg 620219, Russia.
Department of Materials Science and Engineering, KTH Royal Institute of Technology, SE-100 44 Stockholm, Sweden.ORCID iD: 0000-0002-9920-5393
2023 (English)In: Computational materials science, ISSN 0927-0256, E-ISSN 1879-0801, Vol. 218, article id 111912Article in journal (Refereed) Published
Abstract [en]

Statistical alloy theory based on the Master Equation approach with ab initio calculated interatomic interactions is employed to investigate the growth of precipitates at the early stages of solid solution decomposition, as well as the dissolution of small precipitates during the coarsening stage, upon simulated annealing of ternary Al–Sc–Zr alloys. We show, in agreement with previous studies, that the Zr alloying to Al–Sc alloys promotes the formation of core–shell nanoparticles whose structure is found to be very sensitive to the parameters characterizing the solute diffusion rates in the alloy. We demonstrate that the core–shell structure of precipitates slows down the dissolution of small particles, thus hampering the microstructure coarsening at elevated temperatures.

Place, publisher, year, edition, pages
Elsevier, 2023. Vol. 218, article id 111912
Keywords [en]
Ab initio based modeling, Aluminum-based alloys, Core–shell structure, Precipitation
National Category
Metallurgy and Metallic Materials Physical Chemistry
Research subject
Applied Physics
Identifiers
URN: urn:nbn:se:ltu:diva-94661DOI: 10.1016/j.commatsci.2022.111912ISI: 000910752000003Scopus ID: 2-s2.0-85142505328OAI: oai:DiVA.org:ltu-94661DiVA, id: diva2:1716997
Note

Validerad;2022;Nivå 2;2022-12-07 (hanlid);

Funder: Russian Science Foundation (18-12-00366)

Available from: 2022-12-07 Created: 2022-12-07 Last updated: 2024-04-22Bibliographically approved

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Gorbatov, Oleg I.

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