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Machine-learning augmented prediction of multi-phase crystallization from rapid heat treatments in the Fe-Si-B syste
Malmö University, Faculty of Technology and Society (TS), Department of Materials Science and Applied Mathematics (MTM).ORCID iD: 0009-0007-8282-8336
(English)Manuscript (preprint) (Other academic)
National Category
Metallurgy and Metallic Materials
Identifiers
URN: urn:nbn:se:mau:diva-83938OAI: oai:DiVA.org:mau-83938DiVA, id: diva2:2056782
Available from: 2026-04-30 Created: 2026-04-30 Last updated: 2026-05-11Bibliographically approved
In thesis
1. Temperature induced phase evolution in metallic glasses
Open this publication in new window or tab >>Temperature induced phase evolution in metallic glasses
2026 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Many material properties of alloys are strongly influenced by the precipitation of secondary phases in the bulk material. Traditional alloys have been polycrystalline; however, over the years, many types of advanced alloys have been produced through precise tailoring of their microstructure. One of these advanced alloys is metallic glass, which is obtained by rapidly quenching a liquid into a metastable amorphous solid. The lack of long-range ordering in this phase has been shown to yield remarkable material properties such as extremely high yield strength and high corrosion resistance. One drawback of the amorphous phase is that it is very brittle, and critical failure caused by inhomogeneous deformation is common. At the frontier of research on glass-type alloys are the nanocrystalline composite alloys, where a controlled dispersion of nanosized crystallites is allowed to form through controlled heat treatment of the alloy system, yielding even more refined material properties. For example,alloys with high ductility and high strength, tunable corrosion resistance, or excellent soft-magnetic properties have been developed.

Regardless of whether the alloy is glass, nanocrystalline, or polycrystalline, the engineering of the microstructure is key; however, it is far from trivial. A theoretical method well suited for simulating phase evolution on a continuum scale is the classical nucleation and growth theory (CNGT), in which a statistical precipitate population within a unit volume can be simulated. Coupled with the framework of calculation of phase diagram, rigid thermodynamic descriptions of alloy systems can be utilized. To quantitatively study colloid distributions of precipitates experimentally, small-angle scattering is an advantageous method.

This PhD thesis aims to contribute to the understanding of crystallization in metallic glass through the investigation of highly relevant alloys and the development of analytical tools. Utilizing a combined approach of experimental measurements and modeling by CNGT, rapid devitrification in Zr-based and Fe-based metallic glass is studied in high detail. Numerical strategies to simulate and analyze data from crystallization are developed and refined, providing insights into both non-equilibrium multiphase phase evolution and methods for high throughput analysis.

Place, publisher, year, edition, pages
Malmö: Malmö University Press, 2026. p. 57
Series
Studies in Applied Physics
National Category
Metallurgy and Metallic Materials
Identifiers
urn:nbn:se:mau:diva-83933 (URN)10.24834/isbn.9789178777563 (DOI)978-91-7877-755-6 (ISBN)978-91-7877-756-3 (ISBN)
Public defence
2026-06-09, NI:B0E07, Niagara, Nordenskiöldsgatan 1, Malmö, 09:15 (English)
Opponent
Supervisors
Available from: 2026-04-30 Created: 2026-04-30 Last updated: 2026-05-19Bibliographically approved

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Tidefelt, Mattias

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