Box-Bahnken Design Biodiesel Prediction Model from Corn Oil using Na-Modified Alumina Beads

Objective: To overcome the problems of one-variable-at-a-time traditionally used for optimization, Response Surface Methodology (RSM) is employed due to its being less time consuming and inexpensive. Methods/Statistical Analysis: In the present study a number of Na/Al-beads solid base catalysts were prepared by supporting different amount of NaOH adopting the method of wet impregnation. The characterization methods for the catalysts were Fourier Transform Infra- Red (FTIR), X-Ray Powder Diffraction (XRD) and basic back titration. Findings: Increasing the amount of NaOH doping results in an increased in the number of basic sites. The catalysts were then used for optimization study of methanolysis of corn oil using four level factorial Box-Bahnken Design (BBD) RSM analysis. The variables studied are the amount of NaOH doping (15-25 g), catalyst loading (3-10 %), oil: methanol molar ratio (1:6-1:15) and duration of reaction (1-3 h). The results revealed that all parameters are influential on the methanolysis experiment, with the most influential variable being the molar ratio. The highest yield of 96.2% was obtained from the model using 20% NaOH doping, 10% catalyst loading, 1:15 molar ratio and 2 hours reaction time. Applications/Improvements: Interestingly when a methanolysis reaction was performed under suggested conditions from the model, a yield of 96.3% was obtained which agree with the predicted value of 97.9% indicating the fit of the model.