Optimization study of corn oil methanolysis using NaOH-modified mesoporous Gamma-Alumina

Abstract

The conventional one-variable-at-a-time optimization technique is faced with so many challenges that include inability to simultaneously optimize all variables and many experimental runs are required to optimize the reaction parameters. To solve these problems Response Surface Methodology (RSM) is introduced. In the present study number of NaOH-modified mesoporous gamma alumina catalysts were prepared using 5 to 25% NaOH by wet impregnation method. The catalysts were characterized using Fourier Transform Infra-Red (FTIR), Nitrogen Adsorption Analysis (BET), Basic Back Titration and Field Emission Scanning Electron Microscopy with energy-dispersive X-ray (FESEM-EDX). The surface area decreased while the number of basic sites increased with the increasing amount of NaOH doping. The optimization of corn oil methanolysis was performed using RSM analysis by Box-Bahnken Design (BBD). From the optimization results all parameters were found to be influential on the methanolysis experiment, with the most influential variable being molar ratio followed by amount of NaOH doping and reaction time. Very high R² (0.9989), the agreement between Predicted R² (0.9948) and Adjusted R² (0.9978), as well as the high Adequate Precision of 96.833 signified the fitness of the model. This was further confirmed by the good agreement between experimental (96.1%) and the predicted conversion (98.9%), under suggested experimental condition by the model.