Abstract
Experimental parameters influencing the transesterification of rubber seed oil (RSO) to biodiesel using alumina (Al2O3) impregnated on calcined eggshells (Al2O3/calcined eggshells) were studied in the present work. Parameters were optimized using response surface methodology (RSM) and artificial neural network (ANN). A conversion of 98.9% was observed for RSO at optimum conditions of 12:1 methanol: oil molar ratio, 3 (wt%) catalyst concentration and 4 (h) of reaction time. A significant quadratic model with molar ratio as the most influencing process parameter and a coefficient of determination, R2, of value equal to 0.9379 is observed from RSM analysis. Best validation performance of 5.8595 at epoch-1 and R2 value equal to 0.9740 was observed from ANN modeling. On comparing RSM and ANN models, it is concluded that ANN is a better tool for predicting the conversion of RSO to biodiesel with minimum error.
Highlights
Fossil fuels cause ecological problems, and result in environmental degradation (Poonam Singh and Anoop 2011)
Heterogeneous base catalysts derived from solid waste shells, alkaline and alkali earth metals are a better replacement over homogeneous catalysts in biodiesel production by a transesterification process (Syazwani et al 2017; Niju et al 2014a, b, c; Girish et al 2013; Chouhan and Sarma 2011; Trisupakitti et al 2018)
A comparison of two design models, response surface methodology (RSM) and artificial neural networks (ANN), in biodiesel production from high viscous rubber seed oil (RSO) using modified heterogeneous solid base Al2O3/eggshells as catalyst is the novel part of the present research work
Summary
Fossil fuels cause ecological problems, and result in environmental degradation (Poonam Singh and Anoop 2011). A high free fatty acid (FFA) content in the oil feedstock leads to soap formation during biodiesel production process by base-catalyzed transesterification. Under such circumstances, acid esterification is the only pre-treatment step used to reduce the FFA content to less than 2 (Thodinh et al 2016). A comparison of two design models, response surface methodology (RSM) and artificial neural networks (ANN), in biodiesel production from high viscous RSO using modified heterogeneous solid base Al2O3/eggshells as catalyst is the novel part of the present research work. Synthesized biodiesel was analyzed by Fourier transform infrared spectroscopy (FTIR), 1H-NMR (nuclear magnetic resonance), and gas chromatography–mass spectrometry (GC–MS) techniques
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
