S.B. Al-Shammari, Jaber M. Asiri, Amirhossein Najafi, Behzad Hashemi Soudmand, Hassan Zohair Hassan, Fawwaz Hazzazi, Nejib Ghazouani
This study presents digital light processing (DLP)-fabricated acrylic–zirconium dioxide (ZrO 2 ) nanocomposites for dental restoration, highlighting an effective integration of AI-based particle size analysis, tribological testing, and multiple linear regression (MLR) modeling. XRD confirmed the retention of tetragonal ZrO 2 within the amorphous resin matrix, while SEM and automated image analysis revealed uniform nanoparticle dispersion with minor clustering at higher loadings. Mechanical and tribological tests showed significant improvements: Shore D hardness increased from 80.0 to 84.9 at 3 wt % ZrO 2, wear rate decreased by 58.3%, and the coefficient of friction dropped by 13.7% at 1 wt %. Thermal imaging indicated reduced surface temperatures during sliding, and worn-surface SEM displayed smoother tracks and less debris. MLR modeling accurately predicted wear and friction, demonstrating that hardness and nanoparticle content reduce wear, whereas surface roughness, temperature, and friction increase it, with optimized particle size further enhancing durability. This integrated approach differentiates the work from previous studies by quantitatively linking nanoparticle dispersion with tribological performance.