Performance and evaluation of calcined limestone as catalyst in biodiesel production from high viscous nonedible oil

Biodiesel production by transesterification of rubber seed oil (RSO) using calcium oxide (CaO) derived from calcined limestone as a heterogeneous catalyst is presented in this study. Optimization of process parameters affecting the conversion of RSO to biodiesel is done by design of experiments (DOE) and an effective comparison of two different optimization methods, namely, response surface methodology (RSM) and artificial neural networks (ANN) is presented. A high conversion of 95.2% was obtained at 12:1 methanol: Oil molar ratio, 4 (wt%) catalyst and 5 hr of reaction time. The proposed design model of RSM is found to fit well with the predicted conversion and with molar ratio and reaction time as the significant process parameters affecting the conversion. Best validation performance of 8.8991 occurred at epoch 4 with a mean square error (MSE) of 1.55 in ANN model trained with Levenberg-Marquardt algorithm. By comparing the predicted coefficient of determination, R-2, values of 0.8452 obtained by using RSM, and 0.9939 obtained by using ANN for biodiesel conversion, it is concluded that ANN model is the best model for predicting the percentage conversion of RSO to biodiesel with minimum error between experimental and predicted values.