FACULTY OF PHYSICAL SCIENCES

With the consistent improvement in information Technology, especially artificial intelligence, many sectors have benefited from it. Education has an immense role to play in the quality of the individuals who will drive the world to the next stage in each generation. The implementation of AI in education aims to equip the student with a plethora of resources from which information and knowledge can be attained. Though it boasts about potential to revolutionize the educational sector, the danger of over reliance on it still exists, aside from that, role of a teacher isn't one that should be replaced by AI, because human interactions are a necessary part of being a human being as outlined by UNESCO. The report emphasizes the need to discourage students from using generative AI as a shortcut to completing tasks, assignments, and even projects. The aim of teaching students is not for them to just produce answers but to learn how to produce them by working hard and dedicating themselves to the pursuit of knowledge. This is the goal that the educational institutions hope to achieve, and creating a system that would increase the chances of achieving that goal should be embraced and utilized.

The work embraces the use of inorganic geochemistry for stratigraphic study. In order to further ascertain the sediments provenance, paleo-redox, tectonic settings, and sandstone classification, ditch cutting samples from the X-well on the Niger Delta Basin were collected. According to the geochemical results, the trace element ratios of V/Cr and U/Th indicated an oxic environment for deposition. The source of the sediments was felsic rock, as shown by bivariate plots of Ni vs Tio2, La/Sc vs Th/Co, and trace elemental ratios of Th/Sc, Th/Co, Cr/Th, and La/Sc.The graphs of K2O/Na2O versus SiO2 and Log (K2O/Na2O) versus Log (SiO2/Al2O3). were dominated by the passive margin zone. The sediments were classified by various chemical sandstone classification systems as sublitharenite, Fe-rich sand, and very little quartzarenite.

This research work is aimed at establishing and testing for existing relationship between the Nigerian Gross Domestic Product (GDP) and the indicators of the Nigerian Stock Market. Market capitalization and All Share Price Index are used as proxies for stock market indicators. Annual data set from 1996 to 2024 are used in the research work. The relationship is explored both in the general sense using multiple linear regression analysis and in the period-based (period of global financial crisis and period of no global financial crisis) using
dummy regression analysis. Detailed analysis of the data using the multiple linear regression analysis revealed a strong significant multiple linear relationship among the response and the predictor variables with a coefficient of multiple determination, R2 of about 0.707 which explains about 93% of the total variations in the response variable. The result from the dummy regression analysis shows even a stronger linear relationship among the predictor variables and the response variables with R2 of about 0.93 which explains about 93% of the
total variation in the response variable Y. The coefficient of the dummy variable is significantly different from zero which point to the need to analyse the variables based on the two economic period. It also represent the average decrease in the response variables Y as a result of the global financial crisis given the indicators of the Nigerian stock market.

This study investigates the subsurface stratigraphy of Benin City, Edo State, Nigeria, using 2D Electrical Resistivity Imaging (ERI) techniques. The research aims to delineate geological formations, assess groundwater potential, and map subsurface layers critical for geotechnical and hydrogeological applications. Data were acquired along two traverses using the Wenner-Schlumberger array, revealing distinct layers with resistivity values ranging from 762 Ωm to 9940 Ωm, corresponding to topsoil, dry sand, and compact silty materials.
The analysis identified three subsurface layers, with depths extending to 54.3 meters and lateral extents up to 130 meters. Stratigraphic mapping provided detailed insights into the thickness, composition, and distribution of geological units. The results demonstrated a strong correlation between resistivity values and known geological formations, enabling the identification of aquifers and their potential water-bearing properties. These findings are crucial for urban planning, infrastructure development, and environmental management.
This study underscores the efficacy of ERI techniques in subsurface investigations, offering a reliable approach for mapping stratigraphy and evaluating groundwater resources. The integration of resistivity data with geotechnical insights provides a comprehensive framework for sustainable development in urban areas, ensuring better decision-making for future infrastructure and environmental projects.

Maternal mortality continues to pose a significant public health challenge in Sub-Saharan Africa, with Nigeria ranking among the countries with the highest burden. The death of women during their reproductive years not only disrupts family structures and causes emotional distress but also places an increased strain on healthcare systems and impedes national economic and developmental progress. In alignment with the United Nations Sustainable Development Goals (SDGs), particularly the goal focused on reducing maternal mortality, this study investigates the application of Artificial Intelligence (AI) in maternal healthcare through the development of a predictive ensemble model for maternal mortality in Delta State, Nigeria. The objective was to accurately classify maternal health risks, enabling the early identification of high-risk pregnancies and facilitating timely clinical interventions that can reduce preventable maternal deaths. Maternal health data were collected from three healthcare centers across Delta State, Nigeria. Nine supervised machine learning algorithms were employed, including Linear Support Vector Machine (SVM), Gaussian Naïve Bayes, Multilayer Perceptron (MLP), Decision Tree, Random Forest, Gradient Boosting Decision Tree (GBDT), Extreme Gradient Boosting (XGBoost), Light Gradient Boosting Machine (LightGBM), and Categorical Boosting (CatBoost).

The prospective use of lead(II) sulfide (PbS) perovskite in thermometric, optoelectronics, and photovoltaic have attracted a lot of interest. However, a number of issues, such as inadequate optical absorption, mechanical softness, suboptimal electrical characteristics, and structural instability, make practical use of it difficult. In this work, we thoroughly examine the structural, mechanical, electrical, and optical characteristics of PbS perovskite using first-principles density functional theory (DFT) computations. Our study reveals the fundamental stability requirements by analyzing formation energies and elastic constants. By analyzing the material's mechanical characteristics, including bulk modulus, shear modulus, and Poisson's ratio, the mechanical resilience of the material is evaluated. In order to maximize light-harvesting capabilities, optical characteristics such as the dielectric function and absorption coefficient are also investigated. We suggest doping, strain engineering, and defect passivation techniques to improve PbS's stability, mechanical strength, and optoelectronic efficiency in order to get beyond current restrictions. Our research provides important information for improving PbS-based materials for upcoming electrical and energy applications.

Access to healthcare is a fundamental human right, yet significant disparities persist in many regions, particularly in Nigeria and across Africa. These disparities are often influenced by race, ethnicity, and age, with underserved populations facing considerable barriers to receiving quality healthcare. This project focuses on geospatial analysis as a tool to assess and address healthcare access inequities. By leveraging geospatial technologies, this study seeks to map healthcare facilities, analyze spatial patterns of accessibility, and evaluate disparities in healthcare availability across diverse demographic groups. Using Geographic Information Systems (GIS) and publicly available data on healthcare infrastructure, population demographics, and socioeconomic indicators, the project identifies regions with inadequate healthcare coverage. Key variables, including proximity to healthcare facilities, density of healthcare providers, and transportation infrastructure, are analyzed in relation to demographic data such as race, ethnicity, and age distribution. Special attention is given to rural and peri-urban areas where healthcare infrastructure is typically sparse. This study also integrates statistical models to quantify disparities, providing actionable insights into how race and ethnicity intersect with geographic location to impact access to essential health services. In regions like Nigeria, where the healthcare system faces significant challenges, the project explores how these disparities disproportionately affect vulnerable populations such as ethnic minorities, elderly citizens, and children. The findings are expected to highlight areas of acute need, where targeted policy interventions could have the greatest impact. Moreover, the geospatial approach offers a data-driven framework for decision-makers, empowering them to allocate resources more effectively and design strategies to bridge healthcare gaps.

This study was carried out to evaluate the Equilibrium of the removal of 2-Chlorophenol from aqueoussolution onto bone char and the parameters that were studied were Concentration, Adsorbent dosage and Time. The bone char was obtained from by calcination process occurring at 500⁰C for 2hours. This char was characterized by using FT-IR, XRD,SEM/EDS and BET. Batch adsorption experiment was carried out to investigate the following variables, pH, Concentration and Adsorbent dosage. The morphology of the bone char showed fine hexagonal shaped particles and a have homogenous structure with rough edges also the presence of elements Carbon, Oxygen, Silicon, Phosphorus, Aluminum,Potassium andCalcium was observed. It was observed that as the concentration increased the amount adsorbed increased, the pH study showed that the adsorption capacity was highest at pH 7.3, lowest at acidic condition and followed by the basic condition. It revealed that cow bone char has good adsorption properties and could be utilized for the treatment of 2Chlorophenol in waste water

Cloud computing has revolutionized the way resources are allocated and utilized in the IT
industry. Efficient resource allocation is crucial for optimizing cost, performance, and reliability in cloud environments. This project aims to explore the various resource allocation strategies, challenges, and optimization techniques in the context of cloud computing. We will analyze different cloud service models and deployment models, and evaluate their impact on resource allocation. Additionally, we will develop a resource allocation algorithm and conduct experiments to assess its performance.

Numerical methods for solving initial and boundary value problems play a crucial role in various fields of science and engineering.The objective of this project is to present a numerical iterative method for solving initial and boundary value problems to ordinary differential equations . This iterative method is based on the use of the Euler's method and the finite difference method (FDM) in solving initial and boundary value problems respectively. The project begins with a comprehensive literature review on numerical methods for solving IVPs and BVPs, emphasizing the theoretical foundations and practical applications of Euler's and
Finite difference methods. The mathematical formulations and algorithmic procedures of both methods are discussed in detail, highlighting their similarities, and differences. Furthermore, the Euler's method and the finite difference method enables us to approximate the solutions of an ordinary differential equation at a given initial value problem and boundary value problem respectively.
Indeed, two numerical examples are provided to illustrate the effectiv
ness of the Euler's and Finite difference methods. Results obtained show that the numerical method is very effective and convenient for solving ordinary differential equations with initial and boundary value
problems.