Influence of operating variables on the transesterification of waste cooking oil to biodiesel over sodium silicate catalyst: A statistical approach

This study examined the use of surface response methodology to investigate the influence of operating variables on the transesterification of waste cooking oil (WCO) to biodiesel over sodium silicate catalysts. The individual and interactive effects of three variables namely, reaction time, reaction temperature and amount of catalyst was evaluated using full 23 (+1) factorial design. The conversion of WCO to biodiesel was achieved through the transesterification reaction over the catalyst at a methanol-to-oil molar ratio of 6:1 in a batch reactor. Physicochemical properties of the sodium silicate catalyst were obtained using Fourier transform infrared spectroscopy (FT-IR) for surface chemistry, thermo-gravimetric analysis (TGA) for thermal stability, N2 physisorption test for Brunauer–Emmett–Teller analysis and scanning electron microscopy (SEM) for morphology. The reaction temperature, reaction time and weight of the catalyst (expressed as a percentage of the amount of WCO) were varied to understand their effect on the yield of biodiesel via response surface methodology (RSM) approach. The BET analysis showed a surface area of 0.386 m2/g for the catalyst. Results from the transesterification reaction reveal that change in catalyst weight percentage had no considerable effect on the biodiesel yield and that there was no mutual interaction between the reaction time and catalyst weight percentage. The results also conveyed that the reaction temperature and reaction time were limiting conditions and a slight variation herein altered the biodiesel yield. The transesterification of WCO produced 57.92% maximum FAME yield at the optimum methanol to oil molar ratio of 6:1, catalyst weight of 2.5%, reaction time of 240 min and a reaction temperature of 64 °C. The variance ratio, VR < Fvalue obtained from the cross-validation experiments indicate perfect agreement of the model output with experimental results and also testifies to the validity and suitability of the model to predict the biodiesel yields.