Energy-Aware Tribology of Nanoclay-Reinforced Biobased-Epoxy Integrating Taguchi Optimization, Machine Learning, and Surface Morphology

The dry sliding wear behaviour of nanoclay-filled bio-based epoxy composites was systematically investigated using a Taguchi L16 experimental design by varying nanoclay content (0–0.35 wt.%), normal load, sliding speed, and sliding time against an EN24 steel counterface. Wear loss, specific wear rate (SWR), frictional response, thermal rise, and energy-based descriptors were quantified, followed by mathematical and machine-learning (ML) based modelling. The results demonstrate that nanoclay addition significantly improves tribological performance up to an optimal content of 0.25 wt.%, beyond which wear instability increases. Compared with neat epoxy, the 0.25 wt.% nanoclay composite exhibited a reduction in steady-state coefficient of friction from ~0.53 to ~0.42, along with a 25–30% decrease in specific wear rate and the lowest energy-to-wear conversion efficiency, indicating more effective utilization of frictional energy. Taguchi analysis identified normal load as the dominant factor governing wear variation (~68% contribution), followed by sliding speed (~17%), while nanoclay content contributed ~5%. An energy-based wear model showed improved correlation with experimental wear volume (R² ≈ 0.93) compared to a classical Archard-type formulation. ML prediction using a random forest model with leave-one-out cross-validation achieved an R² ≈ 0.64 for SWR. Scanning electron microscopy (SEM) and atomic force microscopy (AFM) analyses confirmed a transition from severe abrasive wear in neat epoxy to stable tribofilm formation at 0.25 wt.% nanoclay, followed by heterogeneous debris-mediated wear at higher filler content. The observed reduction in wear loss and frictional energy dissipation supports sustainable materials innovation aligned with SDG 9 (Industry, Innovation and Infrastructure) and SDG 12 (Responsible Consumption and Production), while improved operational efficiency is consistent with SDG 7 (Affordable and Clean Energy).