Enhancement of <scp>LM26</scp> Aluminum Hybrid Composites Performance Through <scp>SiC</scp> and Graphite Reinforcements Using Predictive <scp>ANN</scp> Modeling

ABSTRACT In the pursuit of lightweight, high‐strength materials for automotive and aerospace applications, the improvement of hybrid metal matrix composites (MMCs) has gained significant attention. This work investigates the mechanical and microstructural characteristics of LM26 aluminum alloy reinforced with varying weight percentages (2–8 wt.%) of silicon carbide (SiC) and graphite particles using the stir casting method. The aim is to enhance the performance of conventional aluminum alloys by incorporating the synergistic effects of ceramic (SiC) and solid lubricant (graphite) reinforcements. The mechanical properties, such as hardness, tensile, compressive, and flexural strength, were evaluated. Mechanical testing revealed that the composite with 6 wt.% reinforcement exhibited maximum performance, with tensile strength of approximately 300 MPa, compressive strength around 480 MPa, flexural strength near 310 MPa, and hardness reaching 162 BHN. Unlike prior studies focusing on single reinforcements, this research systematically explores combined SiC–graphite effects on LM26 composites. SEM indicated relatively uniform dispersion of reinforcements with minimal agglomeration, while EDS and XRD confirmed phase and elemental composition without deleterious phases. An artificial neural network (ANN) model was developed to accurately forecast mechanical properties from reinforcement composition, showing strong predictive capability. The findings provide quantitative benchmarks and enhanced understanding crucial for designing advanced LM26/SiC/graphite hybrid composites for structural, automotive, and aerospace applications.