In the recent times, biodiesel production from various non-edible oil sources has received a lot of attention. Karanja oil is chosen mainly due to its availability and low cost. It is a nitrogen fixing tree cultivated to enhance soil quality. Transesterification of Karanja oil to biodiesel using a basic solid modified heterogeneous catalyst has been discussed in the present study. Aluminum nitrate Al(NO 3 ) 3 impregnated on calcined marble (Al(NO 3 ) 3 /calcined marble), prepared by wet impregnation method (25%), is used as a modified heterogeneous base catalyst. Surface morphology of the synthesized catalyst is determined using a scanning electron microscope (SEM) analyzer and the composition of various elements present in the prepared catalyst is analyzed using energy dispersive spectrometer (EDS analyzer). 67.56 (wt/wt) of calcium oxide (CaO) is observed for calcined marble and 78.19 (wt/wt %) of CaO has been noticed for impregnated catalyst (Al(NO 3 ) 3 /calcined marble). A maximum biodiesel yield of 96.5% and a conversion of 97.43% was obtained at an optimum methanol:oil molar ratio of 9:1 (mol/mol), 4 (wt %) of catalyst concentration and 1.5 (h) reaction time respectively. The entire composition of formed biodiesel is determined using gas chromatography-mass spectrometry (GC-MS) analyzer and conversion of Karanja oil to biodiesel is measured using 1 H-nuclear magnetic resonance (NMR) analyzer.
In the present study, acid value optimization in continuous biodiesel production from high viscous nonedible rubber seed oil (RSO) is presented. Gradual reduction in acid value from 67.6 (mg KOH/g oil) (raw RSO) to 3.55 (mg KOH/g oil) (pretreated RSO) to 0.25 (mg KOH/g oil) (synthesized biodiesel) is detected at reaction conditions of 9:1 alcohol:feedstock (methanol:oil (molar ratio)) (mol/mol), 4 h of residence time, and 5 wt% (oil) of catalyst concentration. Optimization of experimental factors is studied using well‐known data‐based tools called response surface methodology (RSM) and artificial neural network (ANN), respectively. A significant second‐order quadratic model with alcohol:feedstock molar ratio (mol/mol) as most influencing experimental factor is observed from ANOVA analysis of RSM studies. A mean‐square error (MSE) of 0.001245 is observed with the best validation performance of 0.0014716 at epoch‐3 in ANN modeling. Comparing the coefficient of determination (R2) of value 0.8906 (from RSM studies) with the value of 0.99 (from ANN modeling) reveals that ANN is the best fit model with experimental value in acid value optimization of continuous biodiesel production from RSO.
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