In this study, we investigate the recycling of aluminum-based metal matrix composites(AMCs) embedded with SiC particulates. The microstructure of the AMCs is characterized by X-ray diffraction and scanning electron microscopy. The possibility of recycling the composite scrap is attempted from the melted alloy and SiC particulates by re-melting, holding and solidification in crucibles. The recovery percentage of the matrix alloy is calculated after a number of holding times, 0, 5, 10, 15, 20, 25 and 30 minutes and for different particulate sizes and weight fractions in the Al matrix. The results show that the recovery percentage of the matrix alloy, as well as the time required for maximum recovery of the matrix, is dependent on the size and weight fraction of SiC particulates. In addition, the percentage recovery increases with particulate size but drops with the particulate fraction in the matrix. The time to reach maximum recovery falls rapidly with an increase in particulate size and fraction.

Composite materials consisting of pure aluminum matrix reinforced with different amounts of graphite particles are successfully fabricated by mechanical ball milling and spark plasma sintering (SPS) processes. The shrinkage rates of the composite powders vary with the amount of graphite particles and the lowest shrinkage value is observed for the composite with the highest amount of graphite particles. The current slopes of time increase with increase in the amount of graphite particles whereas the current slopes of temperature show the opposite trend. The highest thermal conductivity is achieved for the composite with the least amount of graphite particles. Therefore, the thermal properties of the composite materials can be controlled by controlling the amount of the graphite particles during the SPS process.

This paper presents a new approach for analyzing the microstructure of -reinforced aluminum matrix composites from digital images. Various samples of aluminum matrix composite were fabricated by hot pressing the powder mixtures with certain volume and size combinations of pure Al and SiC particles. Microstructures of the samples were analyzed by computer-based image processing methods. Since the conventional methods are not suitable for separating phases of such complex microstructures, some new algorithms have been developed for the improved recognition and characterization of the particles in the metal matrix composites.