Towards sustainable engine fuels: RSM-guided optimization of CNT-doped biodiesel/diesel blends for enhanced efficiency and reduced emissions

Due to the increasing global energy demand and the depletion of fossil-based resources, biodiesel has emerged as a promising alternative fuel owing to its physicochemical similarity to conventional diesel. However, its inherent limitations in engine performance and emissions have led to growing interest in nanoparticle-enhanced fuel formulations. This study investigates the influence of carbon nanotube (CNT) additives at varying concentrations (25, 50, 75, and 100 ppm) on the performance and emission characteristics of an optimized waste cooking oil (WCO) biodiesel/diesel blend (10% biodiesel + 90% diesel) under different engine loads (8, 12, 16, 20, and 24 Nm). Response Surface Methodology (RSM) was employed to model and optimize the multi-response system. Experimental findings revealed that CNT incorporation significantly improved brake thermal efficiency (BTE), brake specific fuel consumption (BSFC), and reduced carbon monoxide (CO) and hydrocarbon (HC) emissions, while slightly increasing nitrogen oxide (NO x ) levels. The RSM-based optimization identified 93.063 ppm CNT concentration and 16.850 Nm engine load as the optimal operating conditions, yielding a desirability score of 0.703. Under these conditions, the predicted responses were 291.937 g/kWh BSFC, 31.067% BTE, 0.227% CO, 389.178 ppm HC, and 283.843 ppm NO x . These results demonstrate the potential of CNT-enhanced biodiesel/diesel blends for cleaner combustion and improved engine efficiency. Furthermore, the integration of RSM provides a robust framework for multi-objective optimization in sustainable fuel research.