Ultrasonic assisted stir squeeze casting of AA5456/Al2O3–SiC-Gr-MoS2 hybrid nanocomposites: Microstructure and strengthening analysis

This study explores the development of aluminum metal matrix hybrid nanocomposites (AMMHNCs) using AA5456 alloy reinforced with 2 wt % of SiC, Al2O3, graphite (Gr), and MoS2 nanoparticles (NPs) through ultrasonic-assisted bottom pouring stir-squeeze casting. The AMMHNCs were characterized using X-ray diffraction (XRD), scanning electron microscopy (SEM), and energy-dispersive X-ray analysis (EDX). XRD confirmed successful NPs incorporation, SEM showed a refined microstructure, and EDX demonstrated a uniform distribution of reinforcements. The study shows that adding NPs with higher intrinsic densities, like Al2O3 and MoS2, increases composite densities. The ASMHNC (AA5456 + Al2O3 + SiC + MoS2) sample exhibited the highest density. Conversely, incorporating lighter SiC and graphite NPs resulted in lower-density composites, as exemplified by the ASGHNC (AA5456 + Al2O3 + SiC + Gr) sample having the lowest density. Adding SiC and MoS2 NPs significantly increases the composites' hardness due to effective grain boundary strengthening, with the ASMHNC sample achieving a maximum hardness of 158.64 HV. The yield strength (YS) and ultimate tensile strength (UTS) of ASMHNC improved significantly by 51.02% and 35.32%, respectively, compared to the AA5456 alloy. The ASMHNC samples exhibited the highest compressive strength of 383.46 MPa, while the AA5456 alloy had the lowest (328.63 MPa). However, adding Gr-NPs slightly reduces YS and UTS and decreases elongation percentage, indicating a potential compromise in ductility and toughness. Fractography analysis identifies various fracture modes, including ductile, brittle, and fatigue, along with their distinct surface features, providing insights into the fracture mechanisms of the AMMHNCs. The research also examines the primary strengthening mechanisms contributing to the increase in YS, including thermal mismatch, the Orowan effect, the Hall-Petch effect, and load bearing. Five prediction models were established to estimate the YS of the developed hybrid nanocomposites. The Quadratic Summation and Arithmetic Summation methods effectively predict the YS of the prepared AMMHNCs, with predictions closely aligning with experimental results.