Taherzadeh Mousavian, Reza ORCID: 0000-0002-2274-3636, Behnamfard, S., Azari Khosroshahi, Rasoul ORCID: 0000-0002-9571-8087, Zavasnik, Janez ORCID: 0000-0002-8822-4089, Ghosh, Paheli ORCID: 0000-0001-9870-6842, Krishnamurthy, Satheesh ORCID: 0000-0001-7237-9206, Heidarzadeh, A. and Brabazon, Dermot ORCID: 0000-0003-3214-6381 (2020) Strength-ductility trade-off via SiC nanoparticle dispersion in A356 aluminium matrix. Materials Science and Engineering A, 771 . ISSN 0921-5093
Abstract
A process was developed to disperse β-SiC nanoparticles (NPs), with a high propensity to agglomerate, within a matrix of A356 aluminum alloy. A suitable dispersion of 1 wt% SiC NPs in the A356 matrix was obtained through a hybrid process including a solid-state modification on the surface of the NPs, a two-step stirring process in the semi-solid and then the liquid-state, and a final hot-rolling process for fragmentation of the brittle eutectic silicon phase and porosity elimination. Titanium and nickel where used as the nanoparticle SiC surface modifiers. Both modifiers were found to improve the mechanical properties of the resulting material, however, the highest improvement was found from the nickel surface modification. For the nickel modification, compared to the non-reinforced rolled alloy, more than a 77%, 85%, and 70% increase in ultimate tensile strength (UTS), yield strength (YS), and strain % at the break, respectively were found with respect to the unreinforced rolled A356. For the rolled nanocomposite containing 1 wt % SiCnp and nickel modification, an average YS, UTS, and strain % at the break of 277 MPa, 380 MPa, and 16.4% were obtained, respectively, which are unique and considerable property improvements for A356 alloy
Metadata
Item Type: | Article (Published) |
---|---|
Refereed: | Yes |
Additional Information: | Article number: 138639 |
Uncontrolled Keywords: | SiC NPs; Aluminium nanocomposite; Nanoparticles; Mechanical properties |
Subjects: | Engineering > Materials Engineering > Mechanical engineering Engineering > Production engineering |
DCU Faculties and Centres: | DCU Faculties and Schools > Faculty of Engineering and Computing > School of Mechanical and Manufacturing Engineering Research Institutes and Centres > I-Form Research Institutes and Centres > Adaptive Information Cluster (AIC) |
Publisher: | Elsevier |
Official URL: | https://dx.doi.org/10.1016/j.msea.2019.138639 |
Copyright Information: | © 2019 Elsevier |
Funders: | SFI |
ID Code: | 26103 |
Deposited On: | 11 Aug 2021 11:53 by Dermot Brabazon . Last Modified 27 Nov 2024 14:18 |
Documents
Full text available as:
Preview |
PDF
- Requires a PDF viewer such as GSview, Xpdf or Adobe Acrobat Reader
1MB |
Metrics
Altmetric Badge
Dimensions Badge
Downloads
Downloads
Downloads per month over past year
Archive Staff Only: edit this record