Abstract
This study developed a catalyst from poultry droppings for the synthesis of biodiesel from waste
cooking oil (WCO). Poultry droppings catalyst characterization was achieved using Brunauer-Emmett and Teller (BET) analysis, fourier transform infrared spectroscopy (FTIR), scanning electron microscope and energy dispersive X-ray (SEM-EDX), X-ray fluorescence (XRF), and Xray diffraction (XRD). Box-Behnken design (BBD) was used in designing the experiments. Response surface methodology (RSM) and artificial neural network (ANN) were compared to determine their performance in modelling and optimizing the process. The catalysts
characterization revealed CaO as the largest constituent and the presence of high surface area (286.322m2/g) and pore size (1.853nm). Optimum biodiesel yield of 90.4694% was achieved with a temperature of 43.92℃, reaction time of 120 minutes with a methanol/oil ratio of 6:1 and catalyst loading of 1 wt.%. RSM model was found to be very efficient with R2 value of 0.9464. Although, comparing with ANN, ANN performed better with a higher R2 value of 0.99669.