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    Experimental Investigation and Artificial Intelligence-Based Modeling of Novel Biodiesel Fuels Containing Hybrid Nanoparticle Additives
    (Mdpi, 2026) Uyar, Muhammed Mustafa; Demirpolat, Ahmet Beyzade; Citlak, Aydin
    This work investigates the influence of hybrid NiO-SiO2 nanoparticles on the engine behavior of biodiesel derived from waste sunflower oil and evaluates the experimental outcomes using a data-driven modeling approach. Biodiesel was produced via transesterification and doped with nanoparticles at concentrations of 50, 75, and 100 ppm. Performance and emission tests were conducted on a single-cylinder diesel engine operating at constant speed under varying loads. Specific fuel consumption, brake thermal efficiency, CO, HC, NOx, smoke opacity, and exhaust gas temperature were recorded and analyzed. The incorporation of nanoparticles improved combustion quality and contributed to substantial reductions in harmful emissions. The WSOB20 blend containing 100 ppm NiO-SiO2 provided the most balanced results, decreasing CO, HC, and smoke emissions by 39.50%, 39.40%, and 35.20%, respectively, relative to diesel fuel, while preserving competitive thermal efficiency. A linear regression model developed for CO prediction produced a low mean squared error (1.08 & times; 10(-5)), indicating strong predictive capability. The findings confirm that hybrid nanoparticle additives can enhance biodiesel performance while supporting accurate emission forecasting.
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    Experimental Investigation of Biodiesel Fuels Obtained by Enriching the Content of Vegetable and Waste Oils with Nanoparticles and Modeling of Data Obtained from the Produced Fuel Samples Using Artificial Intelligence
    (Mdpi, 2025) Demirpolat, Ahmet Beyzade; Uyar, Muhammed Mustafa; Citlak, Aydin
    The objective of this study is to investigate the effects of Mn2O3 nanoparticle additives on the performance and emission characteristics of biodiesel fuels produced from vegetable- and waste-based oils. Biodiesel fuels were synthesized via the transesterification process, after which Mn2O3 nanoparticles were blended in different concentrations (50, 75, and 100 ppm). The prepared fuels were tested in a single-cylinder diesel engine operating under constant speed and variable load conditions. Engine performance parameters such as specific fuel consumption (SFC) and thermal efficiency, along with emission indicators including CO, HC, NOx, smoke opacity, and exhaust gas temperature, were systematically analyzed. Additionally, the experimental findings were modeled and validated using the machine learning-based linear regression method. The addition of Mn2O3 nanoparticles significantly improved combustion and emission performance. Among all samples, the COB10+ 100 ppm Mn2O3 fuel exhibited the best overall performance, achieving a 37.50% reduction in CO, 38.8% reduction in HC, and 33.84% reduction in smoke (soot) emissions compared to conventional diesel. This fuel also demonstrated an increase in thermal efficiency comparable to that of diesel. The improvement in thermal efficiency was attributed to enhanced the in-cylinder temperature, reduced ignition delay, and shorter combustion duration. Furthermore, the use of waste-derived vegetable oils contributed to lower production costs and a reduction in environmental impact. The linear regression model yielded an optimum prediction accuracy with a mean squared error of 5.86 x 10(-6) for CO emission data. These findings indicate that Mn2O3 nanoparticles can effectively enhance the performance and sustainability of biodiesel fuels while maintaining economic and ecological advantages.
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    Investigation of performance and emission values of new type of fuels obtained by adding MgO nanoparticles to biodiesel fuels produced from waste sunflower and cotton oil
    (Elsevier, 2024) Uyar, Muhammed Mustafa; Citlak, Aydin; Demirpolat, Ahmet Beyzade
    Biodiesel was produced using the transesterification method from waste sunflower and cotton oil. As a result of the analysis of the new type of nanoparticle-added biodiesel fuels we produce, the parameters with a decrease in emissions are CO, HC, and smoke emissions. There is a partial increase in NOx emissions. In addition, nanoparticle addition made a positive contribution by increasing thermal efficiency. The produced MgO nanoparticledoped biodiesel fuel samples were compared with diesel fuel. As seen in these comparisons, nanoparticle additives contributed positively to reducing emission values. These improvements were observed as a 31.25 % reduction in CO in the WSOB5+ 100 ppm MgO fuel sample, 41.6% reduction in HC in the COB5+ 100 ppm MgO fuel sample and 36.92% reduction in smoke (soot) in COB5+ 100 ppm MgO fuel sample. A comparison was made between the fuel samples in our study, biodiesel produced from waste sunflower and cotton, and fuels produced with nanoparticle additives of 50, 75, and 100 ppm. It was observed that the most efficient fuel sample in terms of emission values and performance was COB5 + 100 ppm MgO nanoparticle additive fuel. The biodiesel fuel sample produced with COB5 + 100 ppm MgO nanoparticle additives provided a 3.25% improvement in thermal efficiency compared to biodiesel without additives. A positive effect on the heat transfer coefficient was observed as a result of the data on the new type of nanoparticle doped biodiesel. With the impact of this contribution, parameters such as positive contribution to in-cylinder temperature, ignition delay, and combustion time were positively affected in the same direction. Another positive effect of nanoparticle additive to biodiesel, thermal efficiency, increased by 1.1 % in the COB5 + 100 ppm MgO fuel sample. Depending on the decrease in emission rate, it was concluded that the nanoparticle additive added to the fuel greatly benefits the environment.