FUDMA Journal of Renewable and Atomic Energy
The journal covers diverse fields of renewable energy such as: Green (Renewable) Energy Sources and Systems (GESSs), such as Wind power, Hydropower, Solar Energy, Biomass, Biofuel, Geothermal Energy, Wave Energy, Tidal energy, Hydrogen & Fuel Cells, Li-ion Batteries and Capacitors, New Trends in Technologies, policies, strategies, applications for GESSs, GESSs for Electrical Vehicles and Components, Computational Methods for GESSs, Novel Energy Conversion Studies and designs in GESSs, Driving Circuits, control techniques, grid interactive and hybrid systems in Green Energy Systems. Renewable Energy Research and Applications for Industries, Artificial Intelligence Studies, Machine Learning for Renewable Energy Applications, Energy Savings, Sustainable and Clean Energy Issues, Public Awareness and Education for Renewable Energy, Thermoelectric Energy, Energy Conservation in Buildings, Computational Methods and Artificial Intelligence Studies in Renewable Energy Sources, Biomass Conversion Photovoltaic, Solar Thermal Applications, Desalination Solar and Low Energy Architecture, Climatology and Meteorology, Nuclear Meteorology, Geothermal Technology, Micro Grid . Others are; Nuclear Physics, Nuclear energy studies, Nuclear electronics, Nuclear power, Nuclear Reactors, Radiation-Bio Physics, Nuclear Chemistry. Applied Mathematics/Computational Dynamics, Mathematical modeling. Energy Economics. Waste management/waste to wealth.
Centre for Renewable and Atomic Energy Research , Federal University Dutsin-Ma, Nigeria.
INAA-Based Assessment of Elemental Contamination and Ecological Risks in Sediments Associated with Local Open-Site Fertilizer Blending Activities in Kankara, Northwestern Nigeria
Open-site fertilizer blending activities can release potentially toxic and environmentally relevant elements into surrounding sediments, posing risks to local agro-ecosystems through runoff, dust dispersion and subsequent accumulation. This study employed instrumental neutron activation analysis (INAA) to determine the concentrations of nine elements (As, Cr, Zn, Co, V, Mn, U, Th and Ba) and to evaluate associated ecological risks in sediments linked to such activities in Kankara Local Government Area, Katsina State, northwestern Nigeria. Six composite sediment samples (SS1–SS6) were collected, processed and analysed. Analytical accuracy was confirmed using the IAEA-158 marine sediment reference material, which yielded recoveries of 96.6–111.2 % and Z-scores within the acceptable range (|Z| ≤ 0.96). Marked spatial variation was observed, with elevated concentrations of V (up to 241 mg kg⁻¹), Mn (up to 2615 mg kg⁻¹), Cr (up to 106 mg kg⁻¹) and Ba (up to 890 mg kg⁻¹) at sites nearest the blending operations. Contamination factors and geoaccumulation indices indicated low to moderate enrichment for several elements at these locations, while the partial potential ecological risk index based on As, Cr and Zn ranged from 3.68 to 14.35, indicating low potential ecological risk under the adopted screening framework. The localised enrichment of Mn and V, however, warrants continued monitoring. The results provide a baseline for future assessments of fertilizer-related sediment contamination in the region and underscore the need for improved containment, dust suppression and routine environmental surveillance to minimise mobilisation of potentially toxic and environmentally relevant elements into adjacent sediments and the wider agro-ecosystem.
Copyright (c) 2025 FUDMA Journal of Renewable and Atomic Energy
Structural Properties of Manganese-Doped Zinc Selenide Nanoparticles Synthesized by High-Energy Ball Milling: An X-ray Diffraction and Raman Spectroscopic Study
The structural properties of manganese-doped zinc selenide (ZnSe:Mn) nanoparticles, with an average particle size of approximately 3.5 nm, were investigated using X-ray diffraction (XRD) and Raman spectroscopy. Samples were synthesized by high-energy ball milling for 15, 30, and 40 h, with Mn content kept at 0.3%. XRD analysis identified three coexisting mineral phases–stilleite (ZnSe), selenium (Se), and zincite (ZnO)–and confirmed a cubic zincblende structure for stilleite alongside hexagonal structures for selenium and zincite, consistent with Joint Committee on Powder Diffraction Standards (JCPDS) reference data. Crystallite sizes, calculated using the Debye–Scherrer equation, decreased with increasing milling time, ranging from 34.8 Å to 29.4 Å, indicating progressive lattice refinement during milling. Raman spectra, recorded using a 514 nm excitation laser (0.75 mW), revealed dominant vibrational bands at 416, 866, 1782, and 2874 cm⁻¹, attributable to Mn-related lattice modes. The combined XRD and Raman results confirm successful incorporation of Mn into the ZnSe lattice and demonstrate that high-energy ball milling is a viable, low-cost route for producing nanostructured diluted magnetic semiconductors with tunable structural properties.
Copyright (c) 2026 FUDMA Journal of Renewable and Atomic Energy
Evaluation of Ambient Gamma Radiation Levels and Associated Radiological Health Risks in Selected Block Industries of Dutsin-Ma Local Government Area, Katsina State, Nigeria
Ambient gamma radiation arising from naturally occurring radioactive materials (NORM) in geological formations and construction materials contributes to occupational radiation exposure in block-manufacturing industries. This study evaluated ambient gamma radiation levels and associated radiological health risks in seventeen selected block industries in Dutsin-Ma Local Government Area, Katsina State, Nigeria. Indoor and outdoor ambient gamma dose rates were measured in situ using a calibrated Bosean F-S 5000 Geiger-Müller radiation survey meter, while the geographical coordinates of each sampling location were recorded using a handheld Global Positioning System (GPS). Annual Effective Dose (AED) and Excess Lifetime Cancer Risk (ELCR) were estimated following the recommendations of the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR) and the International Commission on Radiological Protection (ICRP). Statistical analyses, including descriptive statistics, Shapiro–Wilk normality tests, paired-samples t-tests, and Pearson correlation analysis, were performed using IBM SPSS Statistics 26.0. The measured indoor and outdoor ambient gamma dose rates ranged from 0.1467–0.1900 µSv h⁻¹ and 0.1067–0.1967 µSv h⁻¹, with mean values of 0.165 ± 0.013 µSv h⁻¹ and 0.162 ± 0.027 µSv h⁻¹, respectively. Although these values exceeded the UNSCEAR worldwide average external terrestrial gamma dose rate, no statistically significant difference was observed between indoor and outdoor measurements (p > 0.05). The estimated annual effective doses remained well below the ICRP occupational dose limit of 20 mSv y⁻¹, while the corresponding ELCR values indicated low long-term radiological risk. The observed radiation levels are primarily attributable to naturally occurring radionuclides in construction materials rather than anthropogenic sources. Overall, the investigated block industries are radiologically safe under current operating conditions, providing valuable baseline data for environmental radiation monitoring, occupational health surveillance, and regulatory decision-making in Nigeria.
Residual Stress Heterogeneity Controls Mechanical Stability in Isodense Amorphous Silica
Residual internal stress is widely recognized as a consequence of glass processing, yet its independent role in controlling the mechanical stability of amorphous SiO₂ remains unclear. Here, molecular dynamics simulations were used to investigate whether residual stress governs deformation in cold- and hot-compressed silica glasses with nearly identical recovered densities. Glasses prepared from paired parent configurations were matched within 0.5% in density, and their residual stress fields were characterized using hydrostatic, deviatoric, and spatial correlation analyses. Mechanical stability was evaluated through athermal quasistatic shear, uniaxial tension, and non-affine displacement analysis. Despite their similar densities, cold-compressed glasses exhibited broader residual stress distributions, approximately 60% higher hydrostatic stress variance, and a 78% longer stress-correlation length than hot-compressed glasses. High-stress regions preferentially nucleated irreversible atomic rearrangements, and incorporating residual stress significantly improved the prediction of mechanically active regions beyond conventional structural descriptors. Fixed-density stress-relief annealing reduced stress heterogeneity and increased yield strength while delaying irreversible deformation without appreciably altering the network topology. These findings identify residual stress heterogeneity as a preparation-dependent state variable governing the mechanical stability of amorphous SiO₂ beyond recovered density.
Copyright (c) 2024 FUDMA Journal of Renewable and Atomic Energy
Preparation-Path Memory Governs the Mechanical Response of Isodense Amorphous Silica
Recovered density is commonly used to describe the structural state of densified silica glass, although its ability to uniquely predict mechanical behaviour remains uncertain. Here, molecular dynamics simulations were performed to investigate whether different pressure–temperature histories produce mechanically distinct amorphous SiO₂ glasses despite nearly identical recovered densities. Reference, cold-compressed, and hot-compressed glasses were prepared under controlled conditions, followed by structural characterization using radial distribution functions, ring statistics, void analysis, and static structure factors. Mechanical behaviour was evaluated through small-strain elasticity, loading–unloading simulations, and non-affine displacement analysis. The cold- and hot-compressed glasses differed in recovered density by only 0.21%, yet retained distinct medium-range topologies. Relative to the cold-compressed glass, the hot-compressed glass exhibited a higher Young's modulus (85.4 ± 1.1 versus 82.6 ± 1.0 GPa), higher yield stress (7.48 ± 0.16 versus 7.05 ± 0.18 GPa), and approximately 31% lower residual strain. Irreversible deformation preferentially originated near strained small-ring environments, while incorporating ring topology and void connectivity substantially improved the prediction of mechanical response compared with density alone. These findings demonstrate that preparation-dependent medium-range topology is a key structural descriptor governing the mechanical behaviour of amorphous SiO₂ beyond recovered density.
Assessment of Natural Radioactivity and Radiological Hazard indices in Soil of Some Geological Formations in Sokoto Group of Sokoto Basin, Northwestern Nigeria
This study measured and assessed natural radioactivity and radiological hazard indices associated with the soil of some geological formations of Sokoto group of Sokoto basin. Total of twelve soil samples from Dange and Kalambaina geological formations were collected and analysed using gamma ray spectroscopy of Center for Energy Resarch and Development (CERD), Ile-Ife. Generally, samples from Dange formation recorded higher values than those from Kalambaina. The overall mean values for the soil samples from the study area were 55.5545±4.22 Bqkg-1, 120.2435±24.77 Bqkg-1and 1972.793±10.98 Bqkg-1 for the radionuclides 238U, 232Th and 40K respectively. These values are greater than worldwide average of 35 Bqkg-1, 30 Bqkg-1 and 400 Bqkg-1. Out of the seven radiological parameters evaluated only absorbed dose rate, radium equivalent and external hazard index with recorded values of 180.56 nGyhr-1, 1.02 and 377.43 Bqkg-1 are the only parameters with values slightly higher than their respective recommended safety limits. In the meantime, use of soil from the studied area may not pose any immediate health hazard to the populace, hence, can safely be used for building and farming activities while continuous radioactivity monitoring should be conducted for the entire Sokoto basin.
The Impact of Aerosols on Climate Forcing and Cloud Microphysics
Aerosols play a fundamental role in the Earth's climate system by influencing radiative forcing and modifying cloud microphysical processes. Despite significant advances in atmospheric science, aerosol–cloud interactions remain one of the largest sources of uncertainty in climate prediction due to their complex spatial and temporal variability. This study presents an integrated observational and modelling assessment of the impacts of natural and anthropogenic aerosols on climate forcing and cloud microphysics under different atmospheric conditions. Satellite observations from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO), together with ground-based measurements from the Aerosol Robotic Network (AERONET), were combined with simulations from the Community Atmosphere Model (CAM) to quantify aerosol radiative effects and aerosol-induced changes in cloud properties. The results indicate that sulfate aerosols exert an average cooling radiative forcing of approximately −0.8 W m⁻² whereas black carbon produces a warming effect of about +1.2 W m⁻². Increasing aerosol optical depth was associated with a 10–20% reduction in cloud droplet effective radius, resulting in enhanced cloud optical depth and suppressed precipitation formation. Climate model simulations further revealed that precipitation efficiency decreased by approximately 15% under heavily polluted conditions compared with relatively clean environments. Regional analyses demonstrated that anthropogenic aerosols strongly modify cloud properties over industrial regions, mineral dust acts as an efficient ice-nucleating particle in arid environments, and sea-salt aerosols exert comparatively weak radiative effects over marine regions. Strong agreement among satellite observations, ground-based measurements, and model simulations enhances the reliability of these findings. Overall, the study highlights the critical role of aerosol–cloud interactions in regulating the Earth's radiation budget and hydrological cycle and emphasizes the importance of accurately representing aerosol processes in climate models to improve future climate projections.
Evaluating Film Reject Rates in Medical Imaging: A Five‑Year Cross‑Sectional Study from Nigeria
Film Reject Analysis (FRA) is a critical quality control tool in medical imaging, offering insight into image quality and patient radiation exposure. This study assessed reject rates, causes, and examinations most frequently associated with rejected films. A total of 591 rejected radiographs were retrospectively reviewed over five years (2018–2022) at Sandaji Lafia Medical Center, Nasarawa State, Nigeria. Rejections were categorized into overexposure, underexposure, patient motion, incorrect positioning, artifact, collimation, fog, and incorrect patient identification. Data were analyzed using descriptive statistics, and graphs were generated with Python (version 3.8) employing Matplotlib and Seaborn libraries. Annual reject rates were 11.23% (2018), 4.54% (2019), 3.52% (2020), 9.89% (2021), and 5.71% (2022). Rates in 2019 and 2020 fell within the WHO recommendation of ≤5%. Overexposure and underexposure were the leading causes, highlighting the need for radiographer training and equipment quality assurance. These findings provide a benchmark for departmental performance and emphasize the importance of systematic FRA in improving diagnostic accuracy and patient safety.
Steady State Thermal Modeling and Heat Flux Analysis of Zinc–Calcium–Aluminosilicate (ZCAS) Glass-Ceramic Using COMSOL Multiphysics
So, a three-dimensional steady-state thermal analysis of zinc–calcium–aluminosilicate (ZCAS) glass, basically a silicate-based material that people often value because it has strong thermal stability and structural reliability in engineering, also optical applications, was performed using the finite element method in COMSOL Multiphysics version 6.2. The Heat Transfer in Solids interface was selected to handle the steady-state heat conduction equation with mixed boundary conditions, meaning two isothermal surfaces plus the other boundaries were thermally insulated, but you know not all of them, just the remaining ones. The ZCAS glass itself was described as a homogeneous and isotropic solid, with density 2500 kg·m⁻³, thermal conductivity 1.20 W·m⁻¹·K⁻¹, and specific heat capacity 750 J·kg⁻¹·K⁻¹. A tetrahedral mesh, with 42,857 elements and 85,742 nodes was used, and yeah the mesh seemed to behave nicely. The computed results indicate a pretty smooth, almost monotonic temperature distribution with a maximum temperature difference of 17.2 K over the whole domain. The conductive heat flux vectors follow the main temperature gradient quite well, with a peak size around 860 W·m⁻², so this is in line with Fourier’s law of heat conduction. Then, a three-dimensional cut-line temperature profile shows a linear trend, which matches the analytical one-dimensional steady-state solution, and the relative errors stayed under 2.5%. Also, when integrating the normal total energy flux over the surfaces, the inlet gives 103.8 W and the outlet gives +103.8 W, so the energy imbalance is less than 0.7%. That basically confirms steady-state energy conservation, which you want to see of course. Overall, once the thermal model was checked, it suggests ZCAS glass maintains stable and predictable heat conduction behaviour even under moderate thermal gradients. These results back up that ZCAS glass is suitable in general, whether it comes from high-purity oxides, or from more sustainable waste-derived precursors, like recycled silica and calcium-rich waste streams, for optical components, electronic packaging, and thermal-resilient structural setups.
Defect Engineering Strategies for High-Performance Tin-Based Perovskite Solar Cells: Interface Defect Analysis of Hole and Electron Transport Layers Using SCAPS-1D Simulation
Tin-based perovskite solar cells (TPSCs) are emerging as attractive lead-free alternatives to conventional lead-based perovskite solar cells due to their low toxicity, good carrier mobility, small bandgap, and great optical absorption. However, the existence of bulk and interfacial imperfections severely limits the photovoltaic performance and long-term stability of TPSCs. Here, SCAPS-1D simulation was used to systematically design defects and study the densities of interfacial defects between the absorber layer and several hole transports layers (HTLs) such as CuI, CuAlO2, CuSbS2, MoS2, CuO and Cu2O. The photovoltaic properties of FTO/WS2/MASnI3/HTL/Au device designs were thoroughly studied under the influence of interface defect density in the range of 1012 to 1020 cm-3. In addition, the effects of the defect density of the absorber layer and the defects of the ETL/absorber interface were also studied. The results demonstrate that CuSbS2 and CuAlO2 have better defect tolerance with maximum power conversion efficiencies (PCEs) of 24.16% and 22.83%, respectively, while CuO and CuI show severe performance loss at high defect densities. The CuSbS2 and CuAlO2-based devices showed exceptional stability against changes in interface defects, implying enhanced interfacial charge extraction and lower non-radiative recombination losses. From the absorber defect analysis, it was shown that the increase in the bulk defect density has a severe impact on open circuit voltage, (Voc) fill factor (FF) and power conversion efficiency (PCE) which is suppressed due to Shockley-Read-Hall recombination. The results emphasize the importance of interface engineering and the choice of suitable transport layers for enhancing the efficiency and stability of lead-free TPSCs.
2D Electrical Resistivity Imaging for Groundwater Contamination at Zobe Dam Irrigation Farming Site, Dutsin-Ma, Katsina State
Polluted aquifers can result in poor drinking water quality, reduced crop yields, and serious health hazards. This study aim to investigate groundwater contamination due to frequent and indiscriminate use of fertilizers at the Zobe dam irrigation farming site using 2D Electrical Resistivity Imaging (ERI). The survey was conducted along two profiles using ABEM SAS4000 terrameter employing the dipole dipole array with an interelectrode spacing of 5 m and a total lateral spread of 200 m. The 2D resistivity data were processed and interpreted using RES2DINV software. The interpreted resistivity sections revealed significant lateral and vertical variations in subsurface materials, indicating heterogeneous soil and groundwater conditions, the 2D resistivity models showed resistivity varying from 17.8 Ωm to 8629 Ωm to a maximum depth of about 13.4 m and 28.7 Ωm to 359 Ωm to a maximum depth of about 6.76 m for both profile one and two respectively. Regions with resistivity values < 20 Ωm are interpreted as leachate plumes originating from the decomposition of buried remains, suggesting possible areas of groundwater contamination or increased pore fluid conductivity, likely influenced by agricultural return flow and infiltration from irrigation activities. Conversely, higher resistivity zones correspond to less saturated or more competent geological formations. The result revealed that the subsurface is composed of distinct lithological layers with the low resistivity values observed in the topsoil layer suggesting the presence of clayey and possibly contaminated materials influenced by irrigation and fertilizer application and also provides valuable insights into the extent and possible pathways of contamination within the study area, which can support sustainable groundwater management and agricultural planning in the region.
Environmental Radiotoxical Dosimetry of Soil Samples of Selected Locations in Federal College of Education (Technical) Gusau Zamfar State
Naturally occurring radioactive materials (NORMs) in soils constitute an important source of environmental radiation exposure and may pose potential health risks to populations occupying affected environments. This study presents a baseline radiological assessment of soils within the Federal College of Education (Technical), Gusau, Zamfara State, Nigeria, providing essential reference data for future environmental monitoring and radiation protection in an institutional setting. Twenty soil samples were collected from strategically selected locations across the campus and analyzed using gamma-ray spectrometry with a NaI(Tl) detector to determine the activity concentrations of 40K,226Ra, and 232Th, as well as associated radiological hazard indices. The mean activity concentrations of 40K, 226Ra, and 232Th were 390.09, 22.68, and 30.29 Bq kg⁻¹, respectively. These values are below the corresponding global average values reported by UNSCEAR, indicating low natural radioactivity within the study area. Radiological hazard assessment showed mean values of 95.67 Bq kg⁻¹ for radium equivalent activity (Raeq), 44.41 nGy h⁻¹ for absorbed dose rate, 0.258 for the external hazard index (Hex), and 0.319 for the internal hazard index (Hin). The average annual effective dose equivalents were 0.222 mSv y⁻¹ for indoor exposure and 0.055 mSv y⁻¹ for outdoor exposure. Excess lifetime cancer risk values remained within internationally accepted safety limits. The measured radiological parameters were generally lower than the recommended thresholds established by the United Nations Scientific Committee on the Effects of Atomic Radiation (UNSCEAR), the Organisation for Economic Co-operation and Development (OECD), and the International Commission on Radiological Protection (ICRP). These findings indicate that the soils within the study area do not present significant radiological health concerns. The study establishes a valuable baseline radiological database for educational institutions in Zamfara State and contributes to ongoing environmental radiation surveillance in regions influenced by diverse geological and anthropogenic activities.
Profitability Analysis of Wheat (Triticum aestivum) Production in Kano State, Nigeria
The study was conducted in Kano state, the overall aims of this study was to analyze the profitability of wheat production in Kano state. Multi-stage sampling procedure was employed for the study to select three out of seven Local Government Areas for this study. The L.G.As selected for this study were Kura, Bunkure and Bagwai. A total of 274 wheat farmers were interviewed. The data for this study were analyzed using descriptive statistic and farm budgeting techniques. The descriptive statistics results show the dominance of male farmers among wheat producers with a mean age of 46.01 years this shows that wheat producers are still agile and active in production, the Mean farming experience of the farmers was 15.17 years indicating that wheat production is an age-long venture in the study area and majority of the respondents obtain their production inputs directly from the market. However the Cost and returns associated with the use of different resources by the wheat farmers in the study area was determine through the use of Farm budgeting techniques, the total revenue for the production of wheat was ₦ 1,265,097.90 per hectare, while the total cost was ₦ 684,273.98 per hectare, given a Net Farm Income of ₦ 580,823.92 per hectare, indicating that wheat production is profitable in the study area. However, the result shows that 92% of the farmers agreed that High cost of production include inputs (labour, seed, fertilizers, and herbicides) was ranked first and most important constraint wheat farmers faced in the process of wheat production.
Geospatial Analysis of Urban Development Extent in Kwara South District, Kwara State
Urban development in Kwara South District, Kwara State are linked to socio-economic and political transformations in recent times, par­ticularly during two key periods: These transformations align with broader trends in post-socialist and rapidly urbanizing regions, where economic restructuring often precipitates the large-scale conversion of agricultural land into built-up areas. This study analyzed the present spatial extent of urban development in Kwara South, taking the direction of development into consideration. Landsat 8 (OLI) imagery of 2024 was obtained from the United States Geological Survey and classified using Maximum Likelihood Classifier (MLC) into five (5) LULC classes; cropland, built up, vegetation, bareland and water bodies. The built-up area which represent urban development was extracted (mapped) and the ‘Calculate Geometry Tool’ was used to calculate the areas of the selected polygons (in km2 and corresponding percentage) in each LGA across the study area to determine the spatial extent. The result of this study revealed the spatial extent of urban development to stand at about 9% (527.21km2), with Offa LGA accounting for more than 33% of the built up areas. Oyun LGA followed with 22%, Irepodun approximately 20% and Ifelodun 12.15%. Conversely, Oke Ero and Isin are the LGAs with least urban development in the study area with 3.57% and 2.29% respectively. The result highlights the significantly spatial extent of urban development in Offa LGA, indicating a higher rate of physical development than all other LGA in the study area. These findings will adequately supports informed planning, particularly in regions under­going accelerated land use transformations, a pattern common in fast-growing urban areas globally.
Determination of Production Cross-Section of Zn-65 Using NIRR-1
The unique decay modes of 65Zn, including both its positron emission and electron capture, places it as an important theragnostic radioisotope with emerging application in nuclear medicine, cancer therapy and other similar applications. Comprehensive study of its cross section is therefore of essence in its production technology design and clinical application, especially as it relates with the analysis of its purity and yield. Hence, for this and other emerging radioisotope of interest, a clear protocol needs to be established as part of expanding the overall utilization of Research Reactors to cover this important area of need. In this work, Nigerian Research Reactor 1 (NIRR-1), a Miniature Neutron Source Reactor (MNSR), has been utilized in the determination of the neutron induced cross section of 64Zn at thermal energy region. The measurement of the cross section for the production of 65Zn radioisotope via 64Zn(n,γ)65Zn nuclear reaction was carried out at the recator facility at Ahmadu Bello University (ABU), Zaria and shown to be suitable in establishing the protocol for the possibility of expanding utilization of NIRR-1 to medical radioisotope production with the right technical efforts. The thermal neutron cross section obtained for the 64Zn(n,γ)65Zn reaction, given as 1.98E+03 mb, is more than all available retrieved data but within the same order of magnitude and with a standard deviation uncertainty of 98.99495 to 893.0759 when compared with extant studies retrieved from the IAEA standard measured cross section data library. The result indicates promising prospect for the exploration of NIRR-1 for medical radioisotope production.
Cross-section, Radioisotopes, Thermal neutron, Production Cross-section, NIRR-1
Spatial Distribution of Natural Radionuclides and Statistical Analysis of Radiological Hazards in Relation to Soil Classification in Katsina State
This study assessed the influence of soil type on the distribution of naturally occurring radionuclides and the associated radiological hazards in southern Katsina State, Nigeria. A total of 25 soil samples were collected from six dominant soil types - Acrisols, Arenosols, Cambisols, Lixisols, Luvisols, and Leptosols - and analyzed using gamma-ray spectrometry for activity concentrations of 226Ra, 232Th and 40K. Radiological hazard parameters including absorbed dose rate (DR), annual effective dose (AED), and hazard indices were evaluated. The mean activity concentrations were 31.46 ± 3.53 Bq/kg for 226Ra, 91.38 ± 5.08 Bq/kg for 232Th, and 312.93 ± 7.10 Bq/kg for 40K. While 40K and 226Ra levels were below global averages, 232Th exceeded the recommended limit. The absorbed dose rate ranged from 46.12 to 107.58 nGy/h, and AED values ranged from 56.54 to 132 µSv/y, all below the global threshold of 480 µSv/y. Hazard indices remained under unity, indicating negligible radiological risk. Statistical analysis using one-way ANOVA revealed significant variation (p = 0.03843) in AED among the soil types, with Leptosols showing the highest mean dose rate (224.5 µSv/y), suggesting a greater radiological contribution. An R² value of 0.4379 indicated a moderate correlation between soil type and AED variability. Additionally, soil pH ranged from 6.15 to 6.51, indicating generally acidic conditions. A moderate negative correlation was found between pH and the activity concentrations of 226Ra and 232Th, while 40K showed a strong positive correlation with pH. The findings contribute critical baseline data for environmental radiation monitoring and suggest that soil type significantly influences dose rate distribution. These insights are vital for land-use planning, environmental safety, and public health risk assessment in Katsina State.
Radioactivity, Soil type, Soil pH, ANOVA
Evaluation of Kaduna Municipal Solid Waste (MSW) as an Alternative Source of Energy
Kaduna metropolis generates significant quantities of municipal solid waste (MSW), with an average Higher Heating Value (HHV) of 21.18 MJ/kg, indicating strong potential for energy recovery. This study evaluates the techno-economic feasibility of converting MSW into electricity, with emphasis on calorific value assessment and household energy supply potential. Laboratory analysis of waste samples collected from Goni Gora and Kakau dumpsites revealed HHV values of 23.24 MJ/kg and 19.11 MJ/kg, respectively. Waste generation was projected using a compound annual growth rate (CAGR) model based on a 2025 baseline population of 1.26 million and a per capita generation rate of 0.497 kg/person/day. The organic fraction (52%) was incorporated into the energy estimation model, and sensitivity analysis (±10% and ±20%) was performed to account for variability in waste generation. Results indicate that Kaduna MSW could generate up to 700 GWh/year of electrical energy under ideal conditions. However, this represents theoretical energy potential; assuming a typical conversion efficiency of about 30% for waste-to-energy systems, the net electrical output is significantly lower. The energy generated has the potential to supply electricity to about 73,000 to 175,000 households annually. The findings demonstrate that MSW represents a viable supplementary energy resource capable of contributing up to 16% to 20% of Kaduna’s electricity demand while improving environmental sustainability.
Municipal solid waste (MSW), Waste-to-energy (WtE), Higher heating value (HHV), Energy recovery, Kaduna metropolis, Household electrification.
Wind Profile Analysis and Wind Turbine Selection for a Low-Wind Site: A Case Study of Lokoja, Nigeria
This study presents a comprehensive assessment of wind energy potential and turbine performance in Lokoja, Nigeria, a region characterized by low to moderate wind speeds. Wind speed data at 10 m height, obtained from the Nigeria Meteorological Agency (NiMet) were statistically analyzed using Weibull distribution to model the site’s wind profile, forming the basis for simulating the performance of ten wind turbine models ranging from 10 kW to 6 MW. Evaluation criteria included cut-in speed, annual energy production (AEP), capacity factor, and levelized cost of energy (LCOE).Results showed that turbines with low cut-in speeds (≤2.5 m/s) are more suitable for Lokoja’s wind regime. Among all models, the Enercon E-115/3.000 demonstrated the highest cost-efficiency, with a capacity factor of 0.124 and an estimated LCOE of $0.085/kWh (₦136.61). Mid-sized turbines like the Polaris P62-1000 and Envision EN-82/1500 also showed balanced performance for decentralized applications. In contrast, smaller turbines such as the Bergey Excel 10 and Aircon 10S were found to be economically unviable due to low energy yield and high unit cost. This study provides a critical, data-driven framework for turbine selection in Nigeria's underexplored inland low-wind regions, supporting the country's goals for renewable energy diversification and rural electrification. It is recommended that small to medium sized turbine with ultra- low cut-in-speed be prioritized for deployment in Lokoja.
Wind Energy, Weibull Distribution, Turbine Performance, Low Wind-Site
Geo-Investigation for Gold Mineralisation Veins in Part of Kushaka Schist Belts, Niger State Nigeria, using an integrated approach
The research attempt to delineate the exact position and depth to gold loads within sheets 164_Minna on latitude 9.30’ to 10.00 North and longitude 6.30’ to 7.00 East at the terminal end of Minna-Kushaka schist belt. The research employed magnetic, radiometric and very low frequency methods. Eight structural lineaments labelled F1 to F8 where mapped from magnetic data, these structures resulted from the deformation of the basement metamorphic rocks when intrude by volcanic intrusions. Majority of these faultiness area trending in the NE-SW direction. The Hydrothermal altered zones was investigated using K/eTh ratio, K_deviation and F_parameter derived from the Radiometric data, Regions with values Potasium-ratio_Thorium (K/Th) ranging from 0.3 – 0.5 %/ppm, K_deviation from 7.3 to 60.6 and F_Parameter from 0.8 to 1.3 respectively were delineated as having being considerably altered. A comprehensive analysis of these results, was used to produce a ternary image in which the delineated region of hydrothermal altered zones appearing in whitish and grey colour located around Minna and Tudun-Fulani, Shakwatu, Shekwata, Gunnu, Sarkin- Pawa, Shiroro, Gunni and Fuka villages. Euler analysis determine the of depths deposits ranging from 5 to 88 metres. Coincidentally mining activities are currently in progress around Shakwatu, Shekwata, Asha, Sarkin- Pawa which falls within the regions delineated. In view of the above, the study recommends the exploration for gold mineral along the profiles VLF A, VLF B, VLF C, VLF D, VLF E, VLF F, VLF G, VLF H, VLF I, VLF J and VLF K respectively. The highest hydrothermal signature correlates with biotite gneiss zones intruded by quartz schist, typical hosts for orogenic gold. The research indicated that location of potentials correlate to the region where exploration is currently going on and beyond, findings from this study can support safer and more efficient resource extraction with minimal environmental impact.
Effect of Chord Length on the Aerodynamic Performance of VAWTs with NACA 0015 Airfoil at Low Wind Speeds.
The aerodynamic performance of Vertical Axis Wind Turbines (VAWTs) in low-wind regions is strongly influenced by blade geometry, with chord length playing a key role in optimizing energy capture. Despite their low performance challenges, VAWTs remain a viable option for harnessing wind energy in urban and low-wind-speed environments. The NACA 0015 airfoil has been widely recommended by many studies for its effectiveness under such conditions. However, few studies have specifically investigated the impact of chord length on the performance of VAWTs using the NACA 0015 airfoil, despite numerous optimization efforts. This study investigates the influence of blade chord length on the aerodynamic performance of VAWT employing the NACA 0015 airfoil under low wind speed conditions, specifically 3m/s and 4m/s. Using 2D transient CFD simulations with the SST k-ω turbulence model, three chord lengths (0.1 m, 0.2 m, and 0.3 m) were assessed over a Tip Speed Ratio (TSR) range of 2.0 to 4.5. The findings from this study showed that chord length plays a dominant role in the performance of a VAWT in low wind regimes. While the configuration with 0.1m chord length generated the maximum power coefficient (Cp) of 0.395 during the 4m/s wind speed, the 0.2m chord length configuration produced a more stable performance with a peak Cp of 0.371. At a wind speed of 3m/s, the configuration with 0.3m chord length displayed signs of deteriorating performance due to an excessive increase in solidity. The findings provide insight into optimal chord sizing for small-scale VAWTs operating in urban low-wind environments, supporting design decisions for decentralized wind energy systems.
Evaluating Time Series and Machine Learning Approaches for Forecasting Inflation in Nigeria
Inflation forecasting is crucial for economic planning, policy formulation, and financial decision-making. This study evaluates the performance of various forecasting models for inflation in Nigeria, including Autoregressive Integrated Moving Average (ARIMA), Support Vector Machines (SVM), Random Forest (RF), and Artificial Neural Networks (ANN). These models were selected for their proven effectiveness in macroeconomic forecasting and their ability to capture both linear and non-linear trends. Monthly inflation data from 2000 to 2024 were obtained from the Central Bank of Nigeria (CBN) and the National Bureau of Statistics (NBS), enabling a comprehensive analysis of long-term inflation trends. The performance of the models was assessed using Mean Squared Error (MSE), Root Mean Squared Error (RMSE) and Mean Absolute Percentage Error (MAPE). Results indicate that standalone ARIMA performed poorly, with high error metrics (MSE: 13.35, RMSE: 11.42, MAPE: 37.74%), highlighting its limitations in capturing non-linear inflation patterns. In contrast, machine learning models, particularly ANN (MSE: 1.758, RMSE: 1.694, MAPE: 0.059%), significantly outperformed ARIMA. Hybrid models demonstrated superior performance, with ARIMA-ANN achieving the best results (MSE: 0.611, RMSE: 0.755, MAPE: 0.054%), underscoring the effectiveness of combining statistical and machine learning techniques. While hybrid models, particularly ARIMA-ANN, offer a robust framework for inflation forecasting, their computational complexity and risk of overfitting require careful optimization. The study also assesses model efficiency to ensure practical applicability for economic decision-making. The findings provide policymakers with a reliable forecasting tool to mitigate inflation volatility, optimize monetary policy, and enhance economic stability. This research concludes that hybrid modeling, despite its complexity, provides more accurate and reliable predictive insights, making it a valuable tool for economic planning and policy formulation.
Degradation of TIO₂ Antireflection Coatings: Thermal and Mechanical Stress Effects Over 35 Years
This study investigates the effects of 35 years of thermal and mechanical stress on titanium dioxide () antireflection coating, as well as the /GaAs interface. The analysis was conducted using the COMSOL Multiphysics environment, employing heat transfer in solids and structural mechanics models to evaluate key parameters under the temperature range of -40 to 140 and load of 10N, including the first principal stress, surface emissivity, /GaAs interface toughness, deformation gradient, and crack growth direction. The findings reveal that during the first five years under the specified thermal and mechanical boundary conditions such as surface-to-ambient radiation, fracture mechanic, convective heat transfer etc, the first principal stress at the coating surface and interface decreased to 0.07MPa and 0.08MPa, respectively, while the deformation gradient exhibited negligible changes. However, between 5 and 20 years, a sharp increase in stress was observed, with values rising to 0.14MPa at the surface and 0.19MPa at the interface. The significant deformation gradient resulted in a reduction of surface emissivity from 0.9 to 0.3 and a decline in interface toughness from 0.25MPa to 0.01MPa. A crack growth direction magnitude of 0.83% was detected, particularly at both the coating edges and interface. Between 20 and 35 years, both the stress and deformation gradient increased gradually, gesturing that the coating could no longer withstand additional stress at this stage. These results provide valuable insights into failure mode analysis during the practical stress testing of photovoltaic modules, aiding in the assessment of long-term performance and reliability. This study investigates the effects of 35 years of thermal and mechanical stress on titanium dioxide () antireflection coating, as well as the /GaAs interface. The analysis was conducted using the COMSOL Multiphysics environment, employing heat transfer in solids and structural mechanics models to evaluate key parameters under the temperature range of -40 to 140 and load of 10N, including the first principal stress, surface emissivity, /GaAs interface toughness, deformation gradient, and crack growth direction. The findings reveal that during the first five years under the specified thermal and mechanical boundary conditions such as surface-to-ambient radiation, fracture mechanic, convective heat transfer etc, the first principal stress at the coating surface and interface decreased to 0.07MPa and 0.08MPa, respectively, while the deformation gradient exhibited negligible changes. However, between 5 and 20 years, a sharp increase in stress was observed, with values rising to 0.14MPa at the surface and 0.19MPa at the interface. The significant deformation gradient resulted in a reduction of surface emissivity from 0.9 to 0.3 and a decline in interface toughness from 0.25MPa to 0.01MPa. A crack growth direction magnitude of 0.83% was detected, particularly at both the coating edges and interface. Between 20 and 35 years, both the stress and deformation gradient increased gradually, gesturing that the coating could no longer withstand additional stress at this stage. These results provide valuable insights into failure mode analysis during the practical stress testing of photovoltaic modules, aiding in the assessment of long-term performance and reliability.
Energy Efficiency and Carbon Emission Reduction in Institutional Lighting: A case study of Twin Theater Lecture Room.
Improper lighting conditions in educational institutions may impact both the health and working capacity of students. significant amount of energy consumption is generally attributed to lighting systems since most institutions are still utilizing non-efficient illuminants, including incandescent, tungsten halogen, and high intensity discharge light bulbs. This study aims to conduct a preliminary energy audit of the twin theatre building using physical survey by counting the numbers lamps, their wattage and the hours of usage. The lighting system integrating day lighting with weather conditions requires a simulation tool and to compare the power consumption with the base case and proposed case. Propose energy-saving strategies evaluate the impact on energy efficiency of lightings systems. Renewable Energy and Energy Efficiency Technology Screen (RET Screen) is a software used in this study to analyze greenhouse gasses. Energy consumption from the two scenarios was compared, and emission savings was evaluated. The preliminary energy audit utilized RET Screen to calculate base case energy consumption, considering lightings systems quantity, operating hours. The software RET Screen was used to develop the energy model and Greenhouse gas emissions reduction. The study case to be a Twin theater of a Kaduna state university main campus. and the electrical energy expenses decreasing by 10.512 kWh per year of the Twin theatre, which is over 75%. The greenhouse gases (GHG) emissions dropped by 149.8 kgCO2 eq. annually of the Twin theater which is about 47.3% This analysis supports the advantages of using LEDs instead of fluorescent lamps, also reduces GHG emissions despite the high lumen deterioration of LEDs.
The use of Internet of Things (IOT) in modern day agriculture
The agricultural sector plays a vital role in the global economy, underscoring the need for innovative technologies to boost productivity and sustainability. This study delves into the potential of Internet of Things (IoT) technologies in modern agriculture, with a focus on optimizing crop yields and resource allocation. By leveraging IoT-enabled devices, farmers can access real-time data on soil conditions, weather patterns, and crop health. This enables precise decision-making, reduces inefficiencies, and promotes sustainable agricultural practices. The study highlights the transformative potential of IoT in addressing pressing challenges in agriculture, including water scarcity, nutrient management, and pest control. The findings of this study suggest that IoT adoption can bridge the gap between traditional and smart farming, paving the way for more sustainable agricultural systems. Specifically, IoT technologies can benefit small-scale farmers by providing them with actionable insights and recommendations to improve crop yields and resource allocation. Overall, this study demonstrates the potential of IoT to revolutionize agricultural practices, promoting sustainability, productivity, and efficiency. By harnessing the power of IoT, farmers can adopt more precise and data-driven approaches to agriculture, ultimately contributing to a more food-secure future.
Comparative Analysis of GA-Optimised Decision Tree and Logistic Regression for Web Intrusion Detection
This study presents a comparative analysis of Decision Tree and Logistic Regression models, each Optimised through Genetic Algorithm (GA)-based feature selection, to enhance the accuracy of website intrusion detection. The study leverages the Thursday Morning Web Attack dataset from the Canadian Institute of Cybersecurity. The dataset, encompassing 170,366 records and 76 features, is specifically tailored to web-based attacks such as SQL injection, brute force, and Cross-Site Scripting (XSS). The GA is employed to iteratively refine feature subsets, enhancing model performance through selection, crossover, and mutation processes. Evaluation metrics, including accuracy, F1 scores, and ROC curves, are utilized to assess model efficacy. The findings reveal that GA optimization significantly improves the performance of the Decision Tree model, achieving notable advancements in classification metrics, especially for complex attack types like Brute Force and SQL Injection. While the Logistic Regression model also shows competitive results, it faces minor trade-offs in accuracy regarding XSS attack detection with GA optimization. This research addresses a critical gap in cybersecurity literature by systematically evaluating the effectiveness of GA-enhanced models in a comparative context. The insights gained lay the groundwork for future research on hybrid models and effective website intrusion detection.
The Role of Perceived Value and Risk in USSD Mobile Banking Adoption
The adoption of Unstructured Supplementary Service Data (USSD) technology has significantly transformed mobile banking in Nigeria, offering cost-effective and seamless access to financial services. This study i[1]nvestigates the factors influencing the adoption of USSD mobile banking within the Katsina banking sector, using an Extended Technology Acceptance Model (TAM) as the analytical framework. A quantitative survey involving 120 valid responses from bank customers was analyzed using simple regression in SPSS. The findings reveal that perceived usefulness, perceived ease of use, perceived cost, and perceived efficiency are significant determinants of USSD mobile banking adoption. However, perceived risk did not exhibit a significant impact on user acceptance, indicating that customers generally view USSD banking as secure and reliable. The study underscores the importance of expanding USSD services to rural areas, where its low-cost, non-smartphone-dependent functionality can bridge financial inclusion gaps. Recommendations are provided for banks to enhance service delivery and accessibility in underserved regions, leveraging USSD's unique advantages. *Corresponding author contact: wabans05@yahoo.com. +234-7039213875
Robust LQR-Based Autopilot Design for Hybrid Energy Harvesting UAVs
The hybrid energy harvest light surveillance unmanned aircraft is designed to be powered with a wind energy fuel-cell. The fuel-cell will produce electrical energy through a regenerative chemical reaction. In the absence of this chemical reaction, energy will be extracted from the vertical gradients of the horizontal wind through a process known as dynamic soaring. For the safe operation of the UAV, stabilization and trajectory control are essential. These features are achieved with the aid of a robust flight control system (autopilot). Owning to the advantages of Linear Quadratic Regulator (LQR) over other controllers which include, its ability to handle Multiple INpute Multiple Output systems and its superior performanc when handling unceertainties and disturbances, it was employed for the design of the control system. The nonlinear simulation model that gives a good representation of the UAV in MATLAB/Simulink environment was developed taking into account the aerodynamic components in 6DOF of equation of motion, the propulsion and the gravity effects. Trimming, decoupling and linearization of the developed nonlinear model were carried out. In order to evaluate the performance of the LQR controller, the response of the system to perturbation was compared to that of the closed loop system with the LQR implemented. In the open loop case none of the states being measured returned to their original value after the introduction of disturbances for 2 seconds. For the closed loop control using the LQR, stability was achieved in the following states; Side velocity, Yaw Rate, Yaw angle, Roll rate and roll angle with their settling times being 36, 40, 41, 30 and 46 seconds respectively. Open loop responses of the models to various control inputs indicated the accuracy of the models. The linearized models were used to design the Autopilot system that has the tendency of stabilizing the UAV in the presence of any uncertainty. The closed loop systems were tested and the influence of different disturbances and the results indicated that the LQR base autopilot is robust enough to ensure safe flight of the UAV
Automated Solar Tracker Utilizing RTC Timing for Enhanced Photovoltaic Energy Generation
The problems of energy scarcity and global warming brought the interest of developing strategies for harnessing renewable energy resources. Solar energy is among the most promising sources of renewable energy. Solar trackers significantly improve a photovoltaic (PV) systems electricity production. In this research work, an automated solar tracker with data logger has been designed and constructed. This automatic tracking system consists of two parts: hardware and software. Hardware part includes voltage regulators; RTC timing device, LCD display, WIFI module, relay circuit and DC motors, while, the software part contained an Arduino programming codes used for tracking system and logging the measured solar PV data. The Atmega328 microcontroller contained in the Arduino board was used to receive the input analog signal from the RTC device which was converted to digital and gives the command to the DC motor to rotate the solar PV panel towards the sun direction. The tracker solar PV panel was tested, and it was found that the solar panel reached maximum power generated from the hour of 12:00 pm to 4:00 pm. A fixed PV panel of same size was also placed side by side and tested with the solar tracking system. The result from tracked PV panel shows an efficiency increase of about 33% over the non-tracking panel. These results indicated that the automatic solar tracker would be recommended for use in solar power generation because it increases the efficiency of the solar power generated, and it is cost-effective.
Genetic Algorithm-Based Feature Selection for Optimizing Website Intrusion Detection Model
The widespread use of the internet and digital platforms has made websites essential for communication, business, and accessing information. However, this reliance has also heightened cybersecurity concerns, as cyber-attacks on web applications pose risks such as data theft, malware installation, and redirection to malicious sites. Cybersecurity is increasingly leveraging machine learning and predictive analysis to proactively identify and mitigate potential web application attacks. Nonetheless, the key challenge in website attack prediction is identifying the most relevant features that balance accurate predictions with manageable computational overhead. While Genetic Algorithm-based feature selection techniques hold promise, their effectiveness should be evaluated on datasets containing common web attacks such as SQL injection, cross-site scripting (XSS), and cross-site request forgery (CSRF). Additionally, metrics beyond accuracy should be considered to assess their generalizability and overall performance. This research investigates the application of Genetic Algorithms (GA) for feature selection in website attack prediction using Decision Tree and Logistic Regression models. The algorithms were evaluated using accuracy and F1-score metrics. The findings revealed that feature selection using GA significantly reduces the number of features to up to 86.8% while maintaining or improving detection accuracy and reduced overfitting. This 86.8% reduction in features simplifies the model while saving resources. The findings highlight the potential of GA as a valuable method for feature selection in website attack prediction.
Optimization of TiO_2 Nanostructure Antireflection Coatings for Enhanced Optical Performance in GaAs Solar Cells
This study presents the effects of the various titanium dioxide nanostructures as anti-reflection coatings on solar cells. The study is conducted in the COMSOL Multi-physics environment where solar cell and titanium dioxide based antireflection coating are simulated. The optical properties of the solar cells with and without the coating were evaluated. Three different coating particles were used; cubic, spherical and pyramidal. The simulation results showed that the cubic nanostructure was found to be more effective, reducing the reflectance percentage from 25.5% without to 3.55% with the ARC at a dimension of 50 nm. The pyramidal nanostructure at same width and a height of 100 nm also demonstrated a reduction in reflectance to 9.9%. This result will definitely enhance the absorption capability of the solar cell whereby increasing its overall efficiency.
Antireflection, Coating, COMSOL, Nanostructure, Solar cell, Titanium dioxide