FACULTY OF PHYSICAL SCIENCES

Perovskite materials made of lead telluride (PbTe) have gained a lot of attention from researchers because of its potential uses in photovoltaics, optoelectronics, and thermoelectrics. They cannot, however, be fully utilized in device applications due to issues such as structural instability, mechanical constraints, electronic flaws, and suboptimal optical performance. In order to solve these problems, we comprehensively examine the structural, mechanical, electronic, and optical characteristics of PbTe perovskite using first-principles density functional theory (DFT) computations. Through the analysis of elastic constants, and formation energies, our study unveils the basic stability criteria. The mechanical resilience of the material is assessed by evaluating its mechanical properties, such as bulk modulus, shear modulus, and Poisson's ratio. Additionally, the nature of bandgap engineering and defect tolerance can be understood through the use of density of states and electronic band structure simulations. The dielectric function and absorption coefficient are examples of optical response functions that are calculated to maximize light-harvesting efficiency. Our findings point to potential strain engineering and doping techniques to improve PbTe's stability, electrical performance, and optical activity, hence increasing its suitability for use in next-generation energy and optoelectronic applications.

This project work is focused on the volumetric estimation of Agbeju Field, Niger Delta using 3Dseismic data and well logs. Data used for this project include 3-D seismic data in SEG-Y format and suites of five well logs (Agbeju 01, Agbeju 02, Agbeju 03, Agbeju 04 and Agbeju X01). 9 major faults and 24 minor faults were delineated on the seismic data. The lateral extent of 3 hydrocarbon bearing reservoirs were delineated and mapped as blocks (Sand A, Sand B and Sand C) and evaluated showing the petrophysical values across the reservoirs having average porosity of 0.32, average pay thickness of 98.46ft, average net-to-gross ratio of 0.84, and average water saturation of 0.625. From prospect identification, the area of the drilled prospects within the reservoirs ranges from 452.8634 acres – 1196.512 acres. The estimated volumes of hydrocarbons within the drilled prospects is given by Gas initially in place for Sand A (554MMSCF), Sand B (163MMSCF) and Sand C (258MMSCF) and Oil initially in place for Sand B (22.4MMBBL) and Sand C (83.93SMMBBL). The result of the characterization of these reservoirs shows good productive sands with fair to good hydrocarbon saturation of 0.375, with sufficient hydrocarbon volumes necessary for field development and production.

This study analyzed the concentrations of hydroquinone in various skin-lightening creams obtained from Ring Road, Benin City, Edo State, Nigeria. Ten cream samples were purchased locally, and hydroquinone levels were determined using UV spectrophotometry at a wavelength of 302 nm. A seven-point calibration curve was prepared to quantify the hydroquinone content in each sample. The results showed that hydroquinone concentrations ranged from 0.0030% to 0.0466%, with Caroline cream containing the highest concentration (0.0466%), while Cussons Baby cream had the lowest (0.0030%). When compared with regulatory standards set by NAFDAC, FDA, and EMA, all detected hydroquinone concentrations were found to be below the permissible limit of 2%. However, the presence of hydroquinone in these products, even at low levels, raises concerns about potential long-term exposure risks, especially for individuals who frequently use multiple skin-lightening products. To mitigate these risks, this study recommends stricter regulatory enforcement, clearer product labeling, standardized formulations, and increased public awareness regarding the effects of hydroquinone. Further research should focus on evaluating cumulative exposure risks and identifying safer alternatives for skin-lightening formulations.

Student academic advising is very important for development of students in different institutions of learning but it always involves a time-consuming effort when the traditional system is employed. A web based academic advising system has been implemented in this study in order to solve the issues between students and the academic advisers, by making advising more convenient, taking complaint from students, evaluating and generating reports, suggesting possible answers to the students’ questions. The researcher surveyed the existing procedures as utilized by many institutions and then implemented a computerized solution in order to enhance their overall advising experience. The researcher presented an outline of the design and implementation of a computerized e-Academic Advising System as a web-based application. The researcher built a model that the academic staff can access to follow-up the students’ complaints and suggestions. Also, the students can register academic complaints, seek advice and more from the system. The e-Academic advising web-based system is developed and implemented with HTML, CSS and "PHP" as a Web framework which runs via the structured query language (SQL) as a Database engine

This study examines the influence of Artificial intelligence on jobs: unemployment and displacement. It captures the implication of Artificial intelligence on the workforce as a whole. The Literature review of the study was segmented into three(3) sections namely; Conceptual review, Theoretical review, and Empirical review. Major Statistical tools of analysis used includes; data visualizations using histograms and the multinomial logistic regression. All tests done were conducted at the 0.05 level of significance. Major findings show that python, AI algorithms, certifications, problem solving, mathematics, and the other skills have a significant effect on getting an AI-related job. The study concludes that the impact AI has on jobs, is more on job loss as regards low-skilled workers, however AI has the ability to complement human workers, which will in turn lead o increased efficiency and productivity. Also as regards job displacement, it will affect mainly low-skilled and routine jobs.

Inventory control plays a critical role in optimizing operations, reducing costs, and ensuring efficiency in the manufacturing industry. This study explores the application of inventory control strategies in the manufacturing sector, using Guinness as a case study. It examines how effective inventory management techniques—such as Economic Order Quantity (EOQ), Just-in-Time (JIT), and Material Requirements Planning (MRP)—impact production efficiency, cost reduction, and overall supply chain performance. The research highlights the challenges Guinness faces in inventory control, including demand variability, stockouts, and holding costs, while also identifying solutions such as automation, real-time tracking, and data-driven forecasting. Findings suggest that implementing advanced inventory control mechanisms leads to improved operational efficiency, minimized waste, and enhanced profitability. This study provides valuable insights for manufacturers seeking to optimize inventory practices and maintain a competitive edge in the industry.

The Students Industrial Work Experience Scheme (SIWES) serves as a vital bridge between academic learning and practical industry exposure for undergraduate students. Despite its importance, students of the University of Benin often encounter significant challenges in securing suitable Industrial Training (IT) placements, largely due to limited access to reliable information on available opportunities, organizational requirements, and appropriate application procedures. This project presents the design of a web-based Industrial Training Placement System aimed at enhancing and streamlining the placement process for UNIBEN students.
The proposed system provides a centralized platform where students can access verified IT compliant organizations, review key information such as required skills, available roles, stipends, and organizational expectations, and submit placement applications conveniently. The Software Development Life Cycle (SDLC) methodology was adopted, guiding the structured development
process through requirements analysis, system modeling, interface design, and database structuring. The system is expected to significantly reduce the stress associated with manual placement searches, improve access to authentic placement information, and enhance the alignment between students’ areas of study and available industry opportunities. Future enhancements may
include integration with institutional systems and expansion into a mobile application for broader accessibility.

The growing complexity of student support services in higher education has created a need for intelligent systems that can provide academic, administrative, and emotional assistance efficiently. This project, titled Designing and Implementing an Autobot Mentor for Student Support, presents the development of an AI-driven chatbot that simulates human-like mentorship interactions using Natural Language Processing (NLP) and Machine Learning (ML) techniques. The system was designed following a three-tier architecture consisting of the presentation, application, and database layers, ensuring modularity, scalability, and ease of maintenance.The Autobot Mentor enables students to access 24/7 guidance through conversational engagement, offering responses to academic inquiries, administrative information, and motivational support. Python and Flask were used for implementation, while MySQL served as the database for storing interaction logs and user data. System evaluation focused on usability, accuracy, and responsiveness, and the results demonstrated that the chatbot achieved
high efficiency and user satisfaction, thereby validating its effectiveness insupplementing traditional mentorship.Overall, this study successfully achieved its objectives by developing a functional AI mentorship system that enhances communication between students and institutions. The Autobot Mentor stands as a scalable model for intelligent academic support systems in digitally transforming educational environments.

This study was design to investigate the adsorption capacity of ascorbic acidonorgano-bentonite clay by studying the adsorption capacity of organo-bentoniteclay. Kinetic parameters such as time and p H from the result obtained, amount adsorbed with time increase with increase with time until equilibrium was attained, while for p H increase in p H leads to increase in amount adsorbed while equilibriumwas attained at p H 8 to 10. From the result obtained it will be seen that adsorption capacity variedwithdifferent parameter