The effect of nickel (III) oxide nanoparticle addition on the performance and emissions of biodiesel and n-butanol fuels in a diesel engine

The global demand for clean and sustainable energy sources has accelerated the search for alternative fuels that can improve the efficiency of diesel engines while redu-cing their environmental impact. In this context, biodiesel, alcohol-based fuels, and nano-technology-driven fuel additives have emerged as promising solutions for cleaner combus-tion and higher performance. This study investigates the effects of adding Nickel (III) oxi-de (Ni₂O₃) nanoparticles at different concentrations (25, 50, 75, and 100 ppm) to biodiesel (B20) and biodiesel–n-butanol (B20But10) blends, with a comprehensive evaluation of engine performance, combustion behavior, and exhaust emissions. Experiments were car-ried out on a single-cylinder, four-stroke, water-cooled, direct injection (DI) diesel engine at four distinct load conditions (0.3, 1.0, 2.0, and 3.0 bar BMEP). Fuel characterization revealed that Ni₂O₃ addition increased density, kinematic viscosity, and cetane index, whi-le reducing lower heating value and flash point. Combustion analysis showed that Ni₂O₃ enhanced atomization and catalytic oxidation, strengthening the premixed combustion phase. Consequently, the maximum in-cylinder pressure (CPₘₐₓ) rose from 53.03 to 55.86 bar for B20 and from 52.21 to 55.45 bar for B20But10, while the maximum heat release rate (HRRₘₐₓ) increased to 29.45 J/°CA and 30.02 J/°CA, respectively. Regarding engine performance, brake thermal efficiency (BTE) improved with load; at full load it rose from 23.96% to 24.89% for B20 and from 23.89% to 24.94% for B20But10. Brake specific fuel consumption (BSFC) decreased from 0.331 to 0.309 kg/kWh for B20 and from 0.348 to 0.333 kg/kWh for B20But10. Emission analysis demonstrated meaningful reductions in CO, HC, NOₓ, and smoke opacity, while CO₂ emissions increased slightly due to more complete combustion. The presence of n-butanol and Ni₂O₃ together enhanced oxidation, resulting in greater CO and HC reductions for B20But10 compared to B20. Additionally, Response Surface Methodology (RSM) was employed to build second-order regression models for predicting and optimizing engine performance and emissions. The models ac-hieved high accuracy (R² = 90.9–99.9) with error margins between 2% and 6%. Five op-timization strategies were proposed to reflect different operational priorities. For example, the balanced Model 1 yielded optimum conditions of approximately 63 ppm Ni₂O₃ and 1.3 bar BMEP for B20 and 58 ppm and 1.3 bar BMEP for B20But10.