Assessment of mechanical, thermal, and sliding wear performance of chemically treated alumina‐filled biocomposites using machine learning and response surface methodology

Abstract This study examines how NaOH treatment and alumina filler affect the mechanical properties, water absorption, thermal degradation, and sliding wear of epoxy composites reinforced with pineapple leaf fiber. NaOH treatment greatly improved the composites' tensile, flexural, and impact strengths by strengthening the bond between the fiber and matrix. Furthermore, the incorporation of alumina filler further elevated the mechanical properties. The composite with 10% alumina showed peak values of 41.4 MPa in tensile strength, 63.8 MPa in flexural strength, and 37.6 kJ/m 2 in impact strength. Because hygroscopic parts were removed from the treated composites, they absorbed much less water. The 15% alumina composite had the lowest absorption at 18% after 192 h. Thermal degradation analysis showed that NaOH treatment improved thermal stability, with the 15% alumina composite having the highest char residue (15.3%) at 700°C. Sliding wear tests showed that alumina reinforcement significantly reduced specific wear rate (SWR) and coefficient of friction (COF). The improved 15% alumina composite had an SWR of 0.2598 × 10 −5 mm 3 /Nm and a COF of 0.103 when sliding at 120 cm/s, with a 45 N load and over 1500 m of distance. A scanning electron microscopy study found that untreated composites experienced severe abrasive wear, while treated and reinforced composites exhibited mild adhesive wear. The study shows that treating PALF composites with NaOH and adding alumina enhance their mechanical, thermal, and tribological properties, making them suitable for high‐performance industrial applications. Highlights Alumina filler improved tensile (41.4 MPa) and flexural strength (63.8 MPa). NaOH‐treated composites absorbed 18% less moisture, enhancing durability. Thermal stability improved, with 15.3% char residue at 700°C for 15% alumina. Optimized composite achieved the lowest wear rate (0.2598 × 10 −5 mm 3 /Nm). Artificial neural network and response surface methodology accurately predicted and optimized composite wear behavior.