Microstructural, Magnetic, and Tribological Optimization of Nano‐ ZrO ₂ Reinforced Magnesium Matrix Composites Fabricated via Powder Metallurgy

Magnesium matrix composites (MMCs) are gaining increasing attention for producing material goods as well as aerospace, automotive, and defense applications due to their high specific strength, lightweight nature, and multifunctional performance. In this study, magnesium‐based composites reinforced with varying fractions (15%, 30%, and 45%) of nano‐ZrO 2 were fabricated through powder metallurgy and sintering, and their microstructural, electrical, magnetic, and tribological behaviors were systematically evaluated to suggest an economy material. Scanning Electron Microscopy (SEM) analysis confirmed a relatively uniform dispersion of ZrO 2 nanoparticles within the matrix, although minor microporosities at the reinforcement–matrix interfaces were observed. Density results indicated a steady increase with higher filler loading, with the Magnesium Zirconium alloy (MZ‐45) composite achieving the highest compactness. Electrical characterization revealed a decrease in conductivity from 11,895 S/m for pure Magnesium (Mg) to 1545 S/m for MZ‐45, accompanied by a corresponding rise in resistivity. Magnetic analysis demonstrated that saturation magnetization increased significantly from 3 emu/g in MZ‐15 to 14 emu/g in MZ‐45, while coercivity values decreased, confirming the composites' potential in soft magnetic applications. Tribological studies based on scratch testing showed improved wear performance, reduced delamination, and lower crack propagation across all reinforced samples compared to pure Mg, highlighting the role of ZrO 2 in strengthening interfacial bonding and enhancing damage resistance. Overall, the developed Mg–ZrO 2 nanocomposites exhibit an effective balance of structural integrity, enhanced magnetic responsiveness, and improved wear tolerance, positioning them as promising candidates for multifunctional applications in aerospace and automotive industries. Future investigations will emphasize process optimization, hybrid reinforcement strategies, and predictive modeling to further refine performance and establish their scalability for industrial deployment.