A critical review of developments in the characterization of metal matrix composites with particulate reinforcements

Abstract

Metal matrix composites reinforced with particulates have been extensively studied in recent decades due to their excellent properties and characteristics, including high strength, stiffness, toughness, density, lightweight, and a higher strength-to-weight ratio. Over the last decade, the characterization techniques of particle-reinforced metal matrix composites (PMMCs) have shifted to a different paradigm. The development of characterization not only depends on the machines used or tests conducted but also on the approach and methodology used to characterize composites. Characterization techniques have come a long way from the experimental phase to simulation modeling and, finally, to the machine learning phase. Like every technology, these various characterization techniques have pros and cons and dependencies on each other. Therefore, this study discusses characterization techniques with a comparative view and critical reasoning to review their reliability and accuracy. The study also includes that other than using conventional experimental equipment, the properties and characteristics of PMMCs can be revealed through microstructure modeling and simulation, where finite element analysis can determine the tensile strength of composites with a deviation of only 0.62%. Alternatively, a machine learning-based artificial neural network may predict tensile strength with 95% accuracy utilizing a small quantity of data. In both instances, the errors in the anticipated outcomes are negligible and far less than the experimental flaws caused by human error, testing, and equipment inaccuracy. This review further highlights that numerical and computational analyses may be applied for characterizations (e.g., mechanical, morphological, and tribological) of PMMCs as a reliable approach to reduce expenses, test time, and save material resources compared to experimental measurements. Lastly, prospects, challenges, and future directions in the development of characterizations of PMMCs are provided prior to concluding remarks.