Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/31534
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dc.contributor.authorLi, S-
dc.contributor.authorDong, X-
dc.contributor.authorSun, J-
dc.contributor.authorTang, Z-
dc.contributor.authorYang, H-
dc.contributor.authorJi, S-
dc.date.accessioned2025-07-11T07:36:34Z-
dc.date.available2025-07-11T07:36:34Z-
dc.date.issued2025-04-29-
dc.identifierORCiD: Xixi Dong https://orcid.org/0000-0002-3128-1760-
dc.identifierORCiD: Shouxun Ji https://orcid.org/0000-0002-8103-8638-
dc.identifierArticle number: 2500485-
dc.identifier.citationLi, S. et al. (2025) 'Effects of Fe Content and Natural Ageing on Microstructure and Mechanical Properties of Recyclable Al5.5Mg2Si Die-Cast Alloys Assisted with Machine Learning', Advanced Engineering Materials, 27 (13), 2500485, pp. 1 - 13. doi: 10.1002/adem.202500485.en_US
dc.identifier.issn1438-1656-
dc.identifier.urihttps://bura.brunel.ac.uk/handle/2438/31534-
dc.descriptionData Availability Statement: Research data are not shared.en_US
dc.description.abstractEffects of Fe content and natural ageing (NA) on microstructure and mechanical properties of Al5.5Mg2SixFe (x = 0.12, 0.3, and 0.6, in wt%) heat treatment-free die-cast alloys are investigated in assistance with machine learning (ML). The main intermetallics in the alloys include β-Mg2Si and α-Al15(Fe,Mn)3Si2, while β-Al13(Fe,Mn)4Si0.25 with the number density of (0.15 ± 0.02) × 10^−2 μm^−2 appears in the Al5.5Mg2Si0.6Fe alloy. As Fe increases from 0.12% to 0.6%, the as-cast yield strength (YS) and elongation (El) reduce from 163.6 ± 2.6 MPa to 160.6 ± 2.5 MPa and 13.09 ± 1.16% to 10.58 ± 1.27%, respectively, which is attributed to the β-Al13(Fe,Mn)4Si0.25 and the increased number density of α-Al15(Fe,Mn)3Si2 from (1.26 ± 0.21) × 10^−2 to (6.32 ± 0.72) × 10^−2 μm^−2. After NA, the alloys show increased YS and decreased El. The Al5.5Mg2Si0.12Fe alloy exhibits considerable NA strengthening with YS increasing by 9.2 ± 5.1 MPa and El decreasing by 2.33 ± 3.21% after NA for 30 days, which is due to the nanoscale β″ precipitates. The quantitative relationship between Fe content, NA time, and tensile properties is established by the Random Forest ML model, i.e., YS(MPa) = 32485.5 − 32324.7 × exp(−0.5 × ((t(day) − 3.9)/2083.9)^2 − 0.5 × ((Fe(wt%) − 0.48)/18.87)^2) and El(%) = 827.5 − 1529.9 × exp(−0.5 × ((t(day) − 517.61)/3777.2)^2 − 0.5 × ((Fe(wt%) − 269.65)/242.01)^2). A high-performance and recyclable Al5.5Mg2Si0.56Fe die-cast alloy is predicted with the YS and El of 163.75 ± 3.4 MPa and 10.05 ± 0.21% after NA for 30 days. This study provides insights for intelligently developing high-performance and recyclable die-cast alloys.en_US
dc.description.sponsorshipNational Outstanding Youth Science Fund Project of the National Natural Science Foundation of China; Jiangsu Specially-Appointed Professor project and Innovate UK. Grant Number: 113151.en_US
dc.format.extent1 - 13-
dc.format.mediumPrint-Electronic-
dc.languageEnglish-
dc.language.isoen_USen_US
dc.publisherWiley-VCHen_US
dc.rightsCopyright © 2025 Wiley-VCH GmbH. This is the peer reviewed version of the following article: Li, S., Dong, X., Sun, J., Tang, Z., Yang, H. and Ji, S. (2025), Effects of Fe Content and Natural Ageing on Microstructure and Mechanical Properties of Recyclable Al5.5Mg2Si Die-Cast Alloys Assisted with Machine Learning. Adv. Eng. Mater., 27: 2500485, which has been published in final form at https://doi.org/10.1002/adem.202500485. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions (see: https://authorservices.wiley.com/author-resources/Journal-Authors/licensing/self-archiving.html).-
dc.rights.urihttps://authorservices.wiley.com/author-resources/Journal-Authors/licensing/self-archiving.html-
dc.subjectaluminum alloysen_US
dc.subjectmachine learningen_US
dc.subjectmechanical propertiesen_US
dc.subjectmicrostructuresen_US
dc.subjectnatural ageingen_US
dc.titleEffects of Fe Content and Natural Ageing on Microstructure and Mechanical Properties of Recyclable Al5.5Mg2Si Die-Cast Alloys Assisted with Machine Learningen_US
dc.typeArticleen_US
dc.date.dateAccepted2025-04-02-
dc.identifier.doihttps://doi.org/10.1002/adem.202500485-
dc.relation.isPartOfAdvanced Engineering Materials-
pubs.issue13-
pubs.publication-statusPublished-
pubs.volume27-
dc.identifier.eissn1527-2648-
dcterms.dateAccepted2025-04-02-
dc.rights.holderWiley-VCH GmbH-
Appears in Collections:Brunel Centre for Advanced Solidification Technology (BCAST)

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FullText.pdfEmbargoed until 29 April 2026. Copyright © 2025 Wiley-VCH GmbH. This is the peer reviewed version of the following article: Li, S., Dong, X., Sun, J., Tang, Z., Yang, H. and Ji, S. (2025), Effects of Fe Content and Natural Ageing on Microstructure and Mechanical Properties of Recyclable Al5.5Mg2Si Die-Cast Alloys Assisted with Machine Learning. Adv. Eng. Mater., 27: 2500485, which has been published in final form at https://doi.org/10.1002/adem.202500485. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions (see: https://authorservices.wiley.com/author-resources/Journal-Authors/licensing/self-archiving.html).3.83 MBAdobe PDFView/Open


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