Faculty of Engineering

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Start date: 2023Subject: search.filters.subject.Chemical engineering

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    Comparative studies of machine learning models for predicting higher heating values of biomass
    (Institution of Chemical Engineers (IChemE), 2024-06-29) Adekunle Akanni Adeleke; Adeyinka Adedigba; Steve Adeshina; Peter Pelumi Ikubanni; Mohammed S. Lawal; Adebayo Isaac Olosho; Halima S. Yakubu; Temitayo Samson Ogedengbe; Petrus Nzerem; Jude A. Okolie
    This study addresses the challenge of efficiently determining the higher heating value (HHV) of biomass, a crucial parameter in large-scale biomass-based energy systems. The conventional method of measuring HHV using an oxygen bomb calorimeter is time-consuming, expensive, and less accessible to researchers, particularly in developing nations. To overcome these limitations, we employed four machine learning (ML) models, namely Random Forest (RF), Decision Tree (DT), Support Vector Machine (SVM), and Extreme Gradient Boosting (XGBoost). These models were developed by using proximate and ultimate analysis parameters as input features. Up to 200 datasets were compiled from literature and used for the ML models. Our results demonstrate the effectiveness of all ML models in accurately predicting the HHV of biomass materials. Notably, the XGBoost model exhibited superior performance with the highest R-squared (R2) values for both training (0.9683) and test datasets (0.7309), along with the lowest root mean squared error (RSME) of 0.3558. Key influential input features identified for HHV prediction include carbon (C), volatile matter (Vm), ash, and hydrogen (H). Consequently, this research provides a reliable alternative for predicting HHV without the need for costly and time-intensive experimental measurements, facilitating broader accessibility in biomass energy research.
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    Synthesis and Characterization of Eggshell-derived Hydroxyapatite for Dental Implant Applications
    (EDP Sciences, 2023-01-01) Jamiu Kolawole Odusote; Adekunle Akanni Adeleke; Peter Pelumi Ikubanni; Peter Omoniyi; Tien-Chien Jen; G. Odedele; Jude A. Okolie; Esther Titilayo Akinlabi
    Hydroxyapatite (HAp) production from eggshells for dental implant purposes involved a novel approach utilizing a wet chemical precipitation technique. The eggshells, finely ground to a size below 250 μm, underwent calcination at a high temperature of 900°C for 2 hours. This thermal treatment facilitated the conversion of calcium carbonate into calcium oxide (CaO) while eliminating any organic components in the eggshell. To initiate the synthesis of HAp, a solution comprising 0.6 M phosphoric acid was added to the CaO dispersed in water. The resulting mixture was allowed to undergo aging at different time intervals ranging from 0 to 24 hours, promoting the formation of HAp. Subsequently, the HAp particles were oven-dried at 100°C for 2 hours to remove residual moisture. Finally, the dried particles were sintered at 1200°C in a muffle furnace to achieve the desired properties for dental implant applications. XRD peaks at 25, 33, 40, and 50° confirm the synthesized material as HAp. Vibrational modes of phosphate (PO43-), hydroxyl (OH-), and carbonate (CO32-) groups indicate carbonated HAp. Synthesized HAp holds potential for biomedical applications.
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    Biomethane and propylene glycol synthesis via a novel integrated catalytic transfer hydrogenolysis, carbon capture and biomethanation process
    (Elsevier, 2023-06-16) Jude A. Okolie; Omoarukhe, Fredrick, O.; Epelle, Emmanuel, I.; Ogbaga, Chukwuma, C.; Adekunle Akanni Adeleke; Okoye, Patrick, U.
    A novel conceptual design for the co-production of biomethane and propylene glycol from integrated catalytic transfer hydrogenolysis (CTH), biogenic CO2 capture and biomethanation reaction was presented in this study. Furthermore, process economics and environmental impact study was performed to appraise the feasibility of the proposed design. The minimum selling price (MSP) of propylene glycol produced considering the overall cost of biomethane as co-product is 1.41 U.S.$/kg. However, if the cost of biomethane was not considered or if the biomethane produced is not enough to yield a yearly revenue then the MSP would increase to 1.43 U.S.$/kg. The MSP of biomethane for the integrated process was 148 U.S.$/MWh. The MSPs of propylene glycol and biomethane were comparable with those of the business-as-usual technology. Factors such as hydrogen donor solvent cost, catalyst cost, electricity price and equipment purchase cost influenced the MSP. Environmental assessment studies showed that the standalone CTH had a higher overall carbon footprint (carbon emissions of 3.7 MM tonnes/yr.). This could be attributed to the consumption of CO2 derived from the process streams via biomethanation process.