Effect of Semisolid and Heat Treatment Process on Microstructural Refinement of Al-7Si Alloy.

Improving the engineering properties of Al-7Si cast alloys (300 series) provides an attractive alternative to automotive and aircraft engine industries. The solubility limit of silicon (Si) in Al contributes to the precipitation of flake-shaped Si particles with sharp edges, which function as a stress riser and promote crack propagation during the eutectic phase while also weakening the protective layer's durability. In this study, the impact of microstructure refinement of Al-7Si alloys by using cooling slope, thixoforming and the T6 heat treatment process on hardness and corrosion resistance behavior was investigated. Results showed that the microstructures of the as-cast alloy had a very coarse dendritic shape, whereas the dendritic transferred to the globular α-Al phase, and the Si particles were replaced into a lamellar- or acicular-like shape after the cooling slope and thixoforming process, respectively. The as-cast, cooling slope and thixoformed samples were subjected to the T6 heat treatment process, which enhanced the hardness to 79, 99 and 104 HV, respectively, due to Si particle refinement. The potentiodynamic test revealed that the corrosion rate dropped to 0.00790 and 0.00736 mmpy-1 in the heat-treated cooling slope and thixoforming samples. This finding can be attributed to the substantially refined Si particles and reduced eutectic phase area due to the smaller cathodic to anodic area ratio.

Mechanical Behaviour and Morphology of Thixoformed Aluminium Alloy Reinforced by Graphene.

Thixoforming is a promising method that offers several advantages over both liquid and solid processing. This process utilizes semi-solid behaviour and reduces macrosegregation, porosity and forming forces during the shaping process. Microstructural and mechanical characterization of 0.3, 0.5 and 1.0 wt% graphene nanoplatelet (GNP) reinforced A356 aluminium alloy composite fabricated by thixoforming was investigated. Stir casting was employed to fabricate feedstocks before they were thixoformed at 50% liquid. The microstructure was characterized and evaluated by field emission scanning electron microscopy with an energy dispersive X-ray detector and X-ray diffraction. Mechanical testing, such as microhardness and tensile testing, was also performed to estimate the mechanical properties of the composites. The incorporation of 0.3 wt.% GNPs in Al alloy increased by about 27% in ultimate tensile strength and 29% in hardness. The enhancement in tensile strength is primarily attributed to load transfer strengthening due to the uniform dispersion of these GNPs within the Al matrix, which promotes effective load transfer during tensile deformation, and GNPs' wrinkled surface structure. Simultaneously, the addition of GNPs enhances the grain refinement effect of the Al alloy matrix, resulting in a grain size strengthening mechanism of the GNPs/Al composites. The results reveal that thixoformed composite microstructure consists of uniformly distributed GNPs, α-Al globules and fine fibrous Si particles. The composites' grains were refined and equiaxed, and the mechanical properties were improved significantly. This study creates a new method for incorporating GNPs into Al alloy for high-performance composites.

Prediction of Fatigue Crack Growth Rate Based on Entropy Generation.

This paper presents the assessment of fatigue crack growth rate for dual-phase steel under spectrum loading based on entropy generation. According to the second law of thermodynamics, fatigue crack growth is related to entropy gain because of its irreversibility. In this work, the temperature evolution and crack length were simultaneously measured during fatigue crack growth tests until failure to ensure the validity of the assessment. Results indicated a significant correlation between fatigue crack growth rate and entropy. This relationship is the basis in developing a model that can determine the characteristics of fatigue crack growth rates, particularly under spectrum loading. Predictive results showed that the proposed model can accurately predict the fatigue crack growth rate under spectrum loading in all cases. The root mean square error in all cases is 10-7 m/cycle. In conclusion, entropy generation can accurately predict the fatigue crack growth rate of dual-phase steels under spectrum loading.