Wear behaviour and statistical assessment of organomodified nanoclay reinforced glass fiber epoxy nanocomposites

This study seeks to optimize and evaluate the wear behavior of glass fiber-reinforced epoxy (G-E) nanocomposites incorporating organomodified montmorillonite (oMMT) nanoclay through a rigorous statistical modeling framework. Nanocomposites were prepared with different grades of oMMT (NC-I, NC-II, NC-III, NC-IV) and compared with neat G-E + NC-00 and unmodified NC-V composites. Structural characterization through XRD confirmed enhanced interlayer spacing (up to 5.04 nm for E + NC-III), indicating successful intercalation/exfoliation, while FTIR spectra verified the incorporation of epoxy chains within organoclay galleries. Dry-sliding wear behaviour was evaluated on a pin-on-disc tribometer as per ASTM G99-17 standards, with applied load (8.18-41.82 N), sliding velocity (0.25-2.44 m/s), and sliding distance (318-2177 m) as process variables. Among all tested systems, the G-E + NC-III nanocomposite consistently exhibited the lowest specific wear rate (9.54-40.29 × 10^{- 6} mm³/Nm), outperforming the neat matrix (10.11-43.33 × 10^{- 6} mm³/Nm) across all loading and velocity conditions. Response Surface Methodology (RSM) and Central Composite Design (CCD) were employed to reduce experimental runs and evaluate parameter interactions. ANOVA revealed that applied load was the dominant factor influencing wear, contributing 68.73% in G-E + NC-00 and 69.03% in G-E + NC-III composites, followed by sliding velocity (≈ 7%) and quadratic effects of AL² and SV² (≈ 12%). Regression models developed for both systems demonstrated excellent correlation with experimental data (R² = 96.4% for G-E + NC-00 and 95.65% for G-E + NC-III), with prediction errors ranging between 4.1% and 11.9%. Overall, the incorporation of oMMT nanoclay, particularly NC-III, significantly enhanced interfacial adhesion, promoted uniform dispersion, and reduced wear loss under varying tribological conditions. The statistical analysis confirms Response Surface Methodology (RSM) as a robust and effective approach for predicting wear performance and identifying optimal processing parameters. The optimized formulation (G-E + NC-III) exhibits strong potential for use in high-wear engineering domains such as automotive body panels, aerospace components, and structural assemblies, where the combination of lightweight construction and enhanced durability is critical.