Browsing by Author "Aderibigbe, F.A."

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    Effects of Processing Conditions of Cassava Starch
    (2006) Solomon, B.O.; Aderibigbe, F.A.; Anozie, N.A.; Betiku, E
    Different procedures for hydrolyzing raw cassava starch were studied, namely: acid, acid-enzyme and enzyme-enzyme hydrolysis. The effects of temperature, initial cassava starch concentration, acid concentration and time on acid hydrolysis using dilute hydrochloric acid were investigated. In addition, the effect of initial cassava starch concentration and time on acid-enzyme hydrolysis with HCl/fungalmyl/amyloglucosidase and HCl/termamyl/amyloglucosidase as well as the enzyme-enzyme hydrolysis with fungalmyl/amyloglucosidase and termamyl/amyloglucosidase were also investigated and the local optimum operating conditions and the yield from the three methods were compared. The results showed that in acid hydrolysis the local optimum operating conditions were: 15% cassava starch concentration, 0.5M HCl, at 70 oC and 10 h operating time which produced 32.5 g/l reducing sugar concentration and dextrose equivalent (DE) of 22. The acid-enzyme hydrolysis with HCl/fungalmyl/amyloglucosidase, using 30% initial cassava starch concentration and total effective operating time of 50 h, produced 72 g/l reducing sugar concentration and DE of 24.8 and was the better of the two acid-enzyme hydrolysis studied. The best procedure was the enzyme-enzyme hydrolysis with termamyl/amyloglucosidase using 30% initial cassava starch concentration, which produced 152 g/l reducing sugar concentration and DE of 50.9. The total effective operating time was 60 h.
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    Evaluation of Predictive Capability of Artificial Neural Network and Multiple Linear Regression: A Case Study of Lipid Extraction from Microalgae using Quaternary Solvents
    (Published by Department of Civil Engineering University of Ilorin, Ilorin, 2019) Mustapha, S.I.; Aderibigbe, F.A.; Mohammed, I.A.
    Abstract: Thiresent study was carried out to evaluate the performance of artificial neural network (ANN) and multiple linear regression (MLR) as modelling tools for predicting the lipid yield obtained from microalgae using quaternary solvent mixtures. The MLR models were developed using two different mathematical softwares viz. Microsoft excel (model 1) and Polymath (model 2). The augmented simplex lattice design under the mixture methodology of the Design Expert software was used to generate the design of experiments used in this study. A comparison of the models developed using ANN and MLR for the extraction process was carried out based on pertinent statistical parameters. Although the results from both MLR models were very close, the calculated values of coefficient of determination (R2) of 0.9934 and the average absolute deviation (AAD) of 2.4789 for the ANN model when compared with values obtained from the MLR (R2 = 0.9898 and AAD = 2.9821 for model 1) and (R2 = 0.9898 and AAD = 2.9825 for model 2) showed that the ANN model was more accurate and precise than the MLR models. The actual maximum lipid yield of 19.4 wt% lipid g-1 DCW was obtained at solvent mixture in the volume ratio of 1:5:1:1 for chloroform, methanol, ethanol, and dichloromethane respectively.
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    Optimisation of CaO-Al2O3-SiO2-CaSO4-based catalysts performance for methanolysis of waste lard for biodiesel production using response surface methodology and meta-heuristic algorithms
    (FuelProcessingTechnology: ElsevierB.V., 2022-02) Ajalaa E.O.; Ehinmowob, A.B.; Ajalaa, M.A.; Ohirob O.A.; Aderibigbe, F.A.; Ajao, A.O.
    The CaO-Al2O3-SiO2-CaSO4-based solid catalysts developed from calcium carbide residue (CCR) was investigated for biodiesel production using waste lard in optimisation and regeneration studies. The catalysts were synthe sized by calcination of the CCR at the temperature of 500, 700 and 900 ◦C and sulphonation, to give Cat500, Cat700 and Cat900 respectively. The catalysts were studied to optimise the biodiesel yield from waste lard using combinations of response surface methodology (RSM) and meta-heuristic algorithms such as particle swarm optimisation (PSO), genetic algorithm (GA) and firefly algorithm (FA). The process parameters investigated were methanol: oil molar ratio (6–12 w/w), reaction temperature (50–60 ◦C), reaction time (1–4 h), catalyst quantity (5–15 % (w/w)) and catalyst type (Cat500, Cat700 and Cat900). The study revealed that the 12:1 MeOH: oil molar ratio, 59.97 ◦C reaction temperature, 1 h reaction time, 5% (w/w) catalyst quantity and Cat500 catalyst type gave biodiesel yield of 96.35%. The performance of the meta-heuristic algorithms based on the optimisation output compared well with that of the RSM. This study concludes that the catalyst developed from the CCR can be regenerated after the ninth cycle of usage and re-utilised for efficient biodiesel production.
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    Removal of Lead and Chromium from Aqueous Solution onto Flamboyant (Delonix regia) Pod Activated Carbon.
    (Published by Faculty of Engineering and Technology, University of Ilorin, Ilorin., 2017) Mustapha, S.I.; Adewoye, L.T.; Aderibigbe, F.A.; Alhaji, M.H.; Adekola, M.I.; Tijani, I.A.
    BSTRACT: The contamination of water by potentially toxic elements is considered a global problem. It calls for a safe, economic and technological approach in order to curb and prevent the devastating effect of the menace on both human and the aquatic life. In the light of this background, the adsorption potential of flamboyant pod activated carbon (FPAC) for the removal of chromium and lead from aqueous solution was studied. The effect of contact time, pH, initial concentration as well as adsorbent dosage on the removal efficiency of both metal ions was investigated via batch adsorption. Characterization of the FPAC adsorbent was done using Brunaur Emmett Teller and Fourier transform infrared spectroscopy. The maximum adsorption capacity Qe was found to be 34.48 and 16.13 mg/g for Pb (II) and Cr (VI), respectively. The Langmuir isotherm model showed a better fit to the equilibrium data than the Freundlich isotherm model. The mechanism of adsorption for both metal ions onto the FPAC agrees well with pseudo second order kinetic model. The results showed that FPAC has excellent adsorption properties and thus can be used as an effective low-cost adsorbent for the removal of lead and chromium ions from aqueous solution.
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    Valorization of Sugarcane Bagasse for Hydrogen-Rich Gas Production using Thermodynamic Modeling Approach
    (Faculty of Engineering and Technology, University of Ilorin, Ilorin, 2022) Mustapha, S.I.; Mohammed, I.A.; Aderibigbe, F.A.; Adewoye, L.T.; Omoarukhe, F.O.; Sowole, A.O.
    Hydrothermal gasification also known as supercritical water gasification (SWG) has been considered a promising approach for converting wet biomass such as sugarcane bagasse into high-quality syngas. This study presents the thermodynamic modeling of the hydrothermal gasification of sugarcane bagasse using Aspen Plus. The effects of process parameters on the composition and yield of product gases were also investigated. It was found that the effect of temperature and biomass concentration were significant in the production of hydrogen-rich gas, while less impact was observed with pressure. The hydrogen gas (H2) produced with the highest mole fraction (56.70 mol%) and yield (103.26 kmol/kg) was obtained at 750°C and low biomass concentration of 10 wt%, while the lowest yield (1.52 kmol/kg) and mole fraction (2.45 mol%) of H2 were obtained at 450°C and high biomass concentration of 50 wt%. Findings from this study also showed that the highest net calorific value (17.55MJ/kg) was reached at 450˚C and 50 wt% of biomass concentration. This study would help to consolidate research on hydrothermal gasification of sugarcane bagasse and optimization of experimental processes and also serve as an important benchmark in the utilization of biomass as a clean energy source for future projects.