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Growth of β intermetallic in an Al-Cu-Si alloy during directional solidification via machine learned 4D quantification

Growth of β intermetallic in an Al-Cu-Si alloy during directional solidification via machine learned 4D quantification

Cai, B., Kao, A. ORCID: 0000-0002-6430-2134, Lee, P. D., Boller, E., Basevi, H., Phillion, A. B., Leonardis, A. and Pericleous, K. ORCID: 0000-0002-7426-9999 (2019) Growth of β intermetallic in an Al-Cu-Si alloy during directional solidification via machine learned 4D quantification. Scripta Materialia, 165. pp. 29-33. ISSN 1359-6462 (doi:https://doi.org/10.1016/j.scriptamat.2019.02.007)

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Abstract

Fe contamination is a serious composition barrier for Al recycling. In Fe-containing Al-Si-Cu alloy, a brittle and plate-shaped β phase forms, degrading the mechanical properties. 4D (3D plus time) synchrotron X-ray tomography was used to observe the directional solidification of Fe-containing Al-Si-Cu alloy. The quantification of the coupled growth of the primary and β phase (Al5FeSi) via machine learning and particle tracking, demonstrates that the final size of the β intermetallics was strongly influenced by the solute segregation and space available for growth. The temperature gradient direction controlled the β orientation. The work can be used to validate predictive models.

Item Type: Article
Uncontrolled Keywords: Al alloys, Intermetallics, Synchrotron X-ray Tomography, 4D Imaging
Subjects: Q Science > QA Mathematics
Faculty / Department / Research Group: Faculty of Architecture, Computing & Humanities
Faculty of Architecture, Computing & Humanities > Centre for Numerical Modelling & Process Analysis (CNMPA)
Faculty of Architecture, Computing & Humanities > Centre for Numerical Modelling & Process Analysis (CNMPA) > Computational Science & Engineering Group (CSEG)
Faculty of Architecture, Computing & Humanities > Department of Mathematical Sciences
Last Modified: 04 Mar 2019 14:54
Selected for GREAT 2016: None
Selected for GREAT 2017: None
Selected for GREAT 2018: None
Selected for GREAT 2019: None
URI: http://gala.gre.ac.uk/id/eprint/22935

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