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Optimization and kinetic modelling of biodiesel produced from Ficus carica seed oil (a novel feedstock) using response surface methodology
Journal of Environment and Biotechnology Research, Vol. 10, No. 1, Pages 1-14, January 2021
Onyekachi Onyekwere, Abuchi Elebo, Francis U. Anumonye, Simon O. Ottah, Bando C. David, Jummai A. Tutuwa, Emmanuel O. Odiba, Nuraddeen M. Hassan
DOI: 10.5281/zenodo.4146868
VIEW FULL TEXT IN PDF
ABSTRACT
The seed oil of Ficus carica was subjected to transesterification reaction using KOH as catalyst and excess methanol to produce fatty acid methyl ester (biodiesel). The physicochemical properties of the fig seed oil and biodiesel was characterized using standard analytical methods. Similarly, the lipid composition was evaluated using gas chromatography coupled with flame ionization detector technique. The various functional groups present in the biodiesel were investigated using Fourier transform infrared spectroscopy. The results of the lipid analysis revealed that polyunsaturated fatty acids were the predominant fatty acid in the seed oil, while the FTIR analysis on the biodiesel, revealed the presence of O-H, C-H, C-O, C-C groups. The effects of process parameters such as temperature, catalyst concentration, reaction time and methanol/oil ratio were investigated using batch mode. The significance of these process parameters as well as their effects on the transesterification proficiency were established using full factorial central composite design and were optimized with the response surface (RSM) methodology. From the analysis, the feedstock gave an optimum yield of 90% when the temperature was at 60˚C for 50 min with 0.6 g of KOH catalyst and 6:1 methanol/oil ratio. The results of the physicochemical properties were compared with ASTM D6751 standards and the parameter values were in agreement with the standard. Thus, the study proved that fig seed oil is an efficient feedstock for biodiesel production. ______________________________________________________________
Optimization and kinetic modelling of biodiesel produced from Ficus carica seed oil (a novel feedstock) using response surface methodology
Journal of Environment and Biotechnology Research, Vol. 10, No. 1, Pages 1-14, January 2021
Onyekachi Onyekwere, Abuchi Elebo, Francis U. Anumonye, Simon O. Ottah, Bando C. David, Jummai A. Tutuwa, Emmanuel O. Odiba, Nuraddeen M. Hassan
DOI: 10.5281/zenodo.4146868
VIEW FULL TEXT IN PDF
ABSTRACT
The seed oil of Ficus carica was subjected to transesterification reaction using KOH as catalyst and excess methanol to produce fatty acid methyl ester (biodiesel). The physicochemical properties of the fig seed oil and biodiesel was characterized using standard analytical methods. Similarly, the lipid composition was evaluated using gas chromatography coupled with flame ionization detector technique. The various functional groups present in the biodiesel were investigated using Fourier transform infrared spectroscopy. The results of the lipid analysis revealed that polyunsaturated fatty acids were the predominant fatty acid in the seed oil, while the FTIR analysis on the biodiesel, revealed the presence of O-H, C-H, C-O, C-C groups. The effects of process parameters such as temperature, catalyst concentration, reaction time and methanol/oil ratio were investigated using batch mode. The significance of these process parameters as well as their effects on the transesterification proficiency were established using full factorial central composite design and were optimized with the response surface (RSM) methodology. From the analysis, the feedstock gave an optimum yield of 90% when the temperature was at 60˚C for 50 min with 0.6 g of KOH catalyst and 6:1 methanol/oil ratio. The results of the physicochemical properties were compared with ASTM D6751 standards and the parameter values were in agreement with the standard. Thus, the study proved that fig seed oil is an efficient feedstock for biodiesel production. ______________________________________________________________
Journal of Environment and Biotechnology Research
Volume 10, Number 1, 2021, pp. 1-14
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