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Stir casting method was used to produce conventional metal matrix composites (MMC) with fairly homogenous dispersion of reinforcement material. Commercial pure aluminum and silicon carbide particles (50 μm) were selected as matrix and reinforcement materials respectively. The matrix was first completely melt and kept constant at 750°C. Then SiC powder preheated to 800°C was added during stirring action. No wetting agents were used. The melt mixture was poured into a metallic mold. The composite contents were adjusted to contain 5% and 10% SiC. The as-cast composites were processed by Equal Channel Angular Pressing (ECAP) route A. The microstructure and mechanical properties were studied. Results indicated that as cast AlSiC composites can be successfully fabricated via a cheap conventional stir casting method, giving fairly dispersed SiC particle distribution and having low porosity levels < 3.6%. The mechanical properties have improved compared to as cast composites. ECAP technique has greatly reduced SiC particles from 50 to 3 μm. After the first ECAP pass, yield strength has almost twice its value in the as cast composites. The maximum yield of 245 MPa obtained after 8 passes is almost four times the corresponding values of the as cast MMC composites. Hardness has also increased to 1.5 times its value in the as cast composites after one ECAP pass. The maximum hardness of 71 HRB obtained after 8 passes, which is almost 3.5 times the corresponding values of the as cast MMC composites.
Aluminum matrix particulate reinforced
composites are of significant interest to industry, but it’s difficult to
provide stable properties for this group of material. The mechanical properties
of metal matrix composites are deeply influenced by the distribution of
reinforcement particulates in the matrix. In this paper uniformity of SiC
particles distribution in Al-based composites produced by stir casting and
powder metallurgy technique is assessed. Analysis is carried out by means of
classical and computer quantification metallographic image analysis methods. In
addition, we suggest setting hardness distribution in cross section of samples
as an indicator of reinforcement distribution uniformity in the matrix.