Department of Petroleum & Gas

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A Review of the Physical, Optical and Photoluminescence Properties of Rare Earth Ions Doped Glasses
(TRENDS IN SCIENCES, 2024-10-22) Serifat Olamide Adeleye; Adekunle Akanni Adeleke; Petrus Nzerem; Adebayo Isaac Olosho; Esther Nneka Anosike-Francis; Temitayo Samson Ogedengbe; Peter Pelumi Ikubanni; Rabiatu Adamu Saleh; Jude A. Okolie
Doping glasses with rare-earth ions have garnered significant attention among researchers worldwide. This interest stems from the widespread utilization of rare-earth ions to enhance the optical characteristics of host glasses and exploit the unique spectroscopic properties arising from their optical transitions in the intra-4f shell. Thus, this study reviewed the exceptional potential of rare-earth ion-doped glasses (REIs) in various applications such as solid-state lasers, photonic devices, communication optical fibers, and white light emission. Various methods for the fabrication of glass such as direct melt quenching, sol-gel, ion exchange, sputtering and co-doping techniques were reviewed extensively. The Specific focus was on the physical, optical and photoluminescence properties of glasses produced from glass formers co-doped with rare earth ions. The investigation centers on the comprehensive current applicability of REI-doped glasses. The review concludes based on the physical, optical and photoluminescence properties of rare earth ion-doped glasses that they are extremely useful in photonics, lasers, biomedical and optical communication applications.
CHARACTERIZATION OF WHEAT HUSK ASH AND CALCINED EGGSHELL AS POTENTIAL GLASS FORMER
(International Conference on Multidisciplinary Engineering and Applied Sciences, 2023-02-02) Serifat Olamide Adeleye; Adekunle Akanni Adeleke; Petrus Nzerem; Peter Pelumi Ikubanni; Ayuba Salihu; Adebayo Isaac Olosho
Numerous agricultural byproducts, such as rice husk and straw, bagasse from sugar cane, palm kernel shell, wheat husk and straw, corn cobs, etc, are highly desired for the production of renewable energy and are seen as potential raw materials for high-value products. Because they can be used to extract quality silica and Calcium oxide for borosilicate glass production, this research has demonstrated that these wastes have a significant end value. X-ray diffraction (XRD) spectroscopy, Fourier transform infrared spectroscopy (FT-IR), and X-ray fluorescence spectroscopy (XRF) were used to characterize the calcined waste eggshell and wheat husk ash for crystal type, compound identification, and chemical composition. The findings demonstrated that the amount of silica and calcium oxide obtained from agricultural waste could be a suitable alternative source for making glass, with calcined eggshells having a calcium oxide content of 91.7% and wheat husk ash having a silica content of 71.3%. The potential for utilizing the CaO and amorphous silica in the formation of glass is thus intriguing.
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.
Isolation, characterization and response surface method optimization of cellulose from hybridized agricultural wastes
(Scientifc Reports, 2024-06-21) Hauwa A. Rasheed; Adekunle Akanni Adeleke; Petrus Nzerem; Adebayo Isaac Olosho; Temitayo Samson Ogedengbe; Seun Jesuloluwa
This study explores the utilization of eight readily available agricultural waste varieties in Nigeria—sugarcane bagasse, corn husk, corn cob, wheat husk, melina, acacia, mahogany, and ironwood sawdust—as potential sources of cellulose. Gravimetric analysis was employed to assess the cellulose content of these wastes, following which two selected wastes were combined based on their cellulose content and abundance to serve as the raw material for the extraction process. Response Surface Methodology, including Box-Behnken design, was applied to enhance control over variables, establish an optimal starting point, and determine the most favorable reaction conditions. The cellulose extracted under various conditions was comprehensively examined for content, structure, extent of crystallinity, and morphological properties. Characterization techniques such as X-ray Diffraction, Scanning Electron Microscopy, and Fourier Transform Infrared Spectroscopy were employed for detailed analysis. Compositional analysis revealed sugarcane bagasse and corn cob to possess the highest cellulose content, at 41 ± 0.41% and 40 ± 0.32% respectively, with FTIR analysis confirming relatively low C=C bond intensity in these samples. RSM optimization indicated a potential 46% isolated yield from a hybrid composition of sugarcane bagasse and corn cob at NaOH concentration of 2%, temperature of 45 °C, and 10 ml of 38% H2O2. However, FTIR analyses revealed the persistence of non-cellulosic materials in this sample. Further analysis demonstrated that cellulose isolated at NaOH concentration of 10%, temperature of 70 °C, and 20 ml of 38% H2O2 was of high purity, with a yield of 42%. Numerical optimization within this extraction condition range predicted a yield of 45.6% at NaOH concentration of 5%, temperature of 45 °C, and 20 ml of 38% H2O2. Model validation confirmed an actual yield of 43.9% at this condition, aligning closely with the predicted value. These findings underscore the significant potential of combinning and utilizing agricultural wastes as a valuable source of cellulose, paving the way for sustainable and resource-efficient practices in various industrial applications.
Renewable Energy Conversion from Biomass
(International Conference on Multidisciplinary Engineering and Applied Sciences (ICMEAS-2023), 2023-11-01) Adekunle Akanni Adeleke ; Petrus Nzerem; Ayuba S.; Esther Nneka Anosike-Francis; Peter Pelumi Ikubanni; Adebayo Isaac Olosho; Abdulrasheed Ado; Adeiza Avidime Samuel; Jakada K.
The global impacts of fossil fuels have driven governments and companies to investigate other methods of energy production for the benefit of society. The utilization of biomass in energy validates the possibility to replace non-renewable sources of energy. Bioenergy is obtained from a wide variety of sources, including rice husks, bagasse, wood chippings, and sawdust. This article presents an examination of the techniques employed in the conversion of biomass into energy that is suitable for practical applications, ecologically friendly and also the rates at which biomass power is consumed worldwide.
Simulation Technology in Renewable Energy Generation: A Review
(International Conference on Multidisciplinary Engineering and Applied Sciences (ICMEAS), 2023-11-01) Adekunle Akanni Adeleke; Petrus Nzerem; Ayuba Salihu; Esther Nneka Anosike-Francis; Adebayo Isaac Olosho; Kpabep Kerein Kalenebari; Yuguda Abdullahi Muhammad; Waliyi Adekola Adeleke; Moses Oluwatobi Fajobi
The escalating energy consumption rates and the alarming environmental impacts associated with fossil fuel usage have driven global attention towards alternative energy sources. While nuclear power has emerged as one such alternative, concerns about past reactor accidents and the health effects of radiation release have limited its widespread adoption. Renewable energy, on the other hand, offers a promising solution with minimal environmental harm compared to nuclear power. However, the intermittent nature of renewable energy sources and their inability to consistently supply power present significant challenges for nations aiming to harness these abundant resources. To address these challenges, the integration of simulation technology into energy generation processes has proven instrumental. By employing simulation tools, it becomes possible to identify, control, and even eliminate factors that may hinder energy generation and efficiency. Furthermore, simulation technology enables accurate predictions of the expected energy output from renewable sources. This paper presents a comprehensive review of the recent advancements and applications of simulation technology in renewable energy generation. It elucidates how simulation technology has been successfully integrated into renewable energy systems and discusses its potential to enhance the efficiency of renewable energy generation.