Industrial waste valorization for sustainable self-healing epoxy vitrimer hybrid composites: Taguchi optimization and machine learning-based performance prediction

This study investigates the development of sustainable self-healing vitrimer composites reinforced with recycled carbon fibers (rCF), waste cotton textile fibers (WCTF), and graphene nanoplatelets (GNP). The rCF, WCTF and GNP were in the range of 20–30%, 10–20%, and 0.5–1%, respectively, and an orthogonal design (L9) was used to create the optimal composition and curing temperature of the reinforcement. The formulation with 30% rCF, 10% WCTF, and 1% GNP, cured at 160°C exhibits high tensile strength of 138 MPa, flexural strength of 208 MPa, and an impact strength of 42 kJ/m² with a strength retention of 92% after saltwater aging. Dynamic mechanical analysis revealed a storage modulus of 5.2 GPa and a glass transition temperature of 132°C, indicating enhanced thermomechanical stability. FESEM, optical microscopy, and XRD analyses confirmed improved fiber–matrix interfacial bonding, reduced void content, and effective crack closure after healing. Taguchi and ANOVA analyses identified recycled carbon fiber content as the dominant factor affecting tensile (50.65%), flexural (49.82%), impact (36.52%), and strength retention (46.87%) properties, whereas GNP content primarily governed healing efficiency (42.63%). Machine learning models verified excellent predictive performance, with average R² values of 0.979 and 0.989 for XGBoost analysis. The results determine the potential of waste-derived reinforcements and vitrimer technology for high-performance, self-healing, and environmentally durable composite applications.