• Eucalyptus biodiesel–diesel blends enriched with TiO₂ nanoparticles were experimentally tested in a four-cylinder diesel engine. • TiO₂ nanoparticles significantly enhanced combustion efficiency, reducing BSFC and increasing BTE compared to neat diesel fuel. • The optimized blend (EO30D70 + 100 ppm TiO₂) improved thermal efficiency by 9.77% and reduced CO, UBHC, and smoke emissions. • A hybrid ANN–GA model successfully optimized engine performance and emission characteristics with high prediction accuracy (R² ≈ 0.999). • Experimental validation confirmed the ANN–GA optimization results with a maximum prediction error below 2.76%. The depletion of fossil fuels due to increasing population and energy demand has intensified the need for sustainable alternative fuels. This study investigates the influence of titanium dioxide (TiO₂) nanoparticles on the engine and emission characteristics of a four-cylinder diesel engine fueled with diesel–eucalyptus biodiesel blends. TiO₂ nanoparticles were dispersed at varying concentrations to improve fuel properties, enhance combustion behavior, and mitigate exhaust emissions. The optimized blend (EO30D70TiO₂100 ppm) demonstrated a 9.77% improvement in thermal conversion efficiency and notable reductions in carbon monoxide (37.35%), unburned hydrocarbons (17.55%), and smoke emissions (16.68%) compared to neat diesel operation. A Taguchi design of experiments comprising 30 trials was employed to assess the combined effects of blend ratio and nanoparticle concentration. An artificial neural network integrated with a genetic algorithm was developed for multi-objective optimization, with the GA interfaced to the ANN-based objective function. Experimental validation of the optimized conditions revealed a maximum prediction error of 2.76%. The results highlight the effectiveness of TiO₂ nanoparticle-enriched eucalyptus biodiesel as a cleaner and efficient fuel option for diesel engine applications.
Belay et al. (2026) studied this question.