Nanoparticle-Induced Superior Hot Tearing Resistance of A206 Alloy View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2013-04

AUTHORS

Hongseok Choi, Woo-hyun Cho, Hiromi Konishi, Sindo Kou, Xiaochun Li

ABSTRACT

Al-Cu alloys (such as A206) offer high strength and high fracture toughness at both room and elevated temperatures. However, their widespread applications are limited because of their high susceptibility to hot tearing. This article presents a nanotechnology approach to enhance hot-tearing resistance for A206. Specifically, γ-Al2O3 nanoparticles were used, and their effects on the hot-tearing resistance of the as-cast Al-4.5Cu alloy (A206) were investigated. While it is well known that grain refinement can improve the hot-tearing resistance of cast Al alloys, the current study demonstrated that nanoparticles can be much more effective in the case of A206. The hot-tearing susceptibilities (HTSs) of A206 alloy and its Al2O3 nanocomposite were evaluated by constrained rod casting (CRC) with a steel mold. Monolithic A206 and M206 (the Ti-free version of A206) alloys with the B contents of 20, 40, and 300 ppm from an Al-5Ti-1B master alloy addition were also cast under the same conditions for comparison. The results showed that with an addition of 1 wt pct γ-Al2O3 nanoparticles, the extent of hot tearing in A206 alloys was markedly reduced to nearly that of A356, an Al-Si alloy highly resistant to hot tearing. As compared with grain-refined A206 or M206, the hot-tearing resistance of the nanocomposites was significantly better, even though the grain size was not reduced as much. Microstructural analysis suggested that γ-Al2O3 nanoparticles modified the solidification microstructure of the eutectic of θ-Al2Cu and α-Al, as well as refined primary grains, resulting in the enhancement of the hot-tearing resistance of A206 to a level similar to that of A356 alloy. More... »

PAGES

1897-1907

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11661-012-1531-8

DOI

http://dx.doi.org/10.1007/s11661-012-1531-8

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https://app.dimensions.ai/details/publication/pub.1025230096


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