Theses and Dissertations

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Activation of the p53 pathway in combination with photon irradiation for the treatment of neurological tumour cells
(2026-05-19) Maluleka, Musa; Nemangwele, Fhulufhelo; Fisher, Randall; Engelbrecht-Roberts, Monique
Medulloblastoma (MB) and glioblastoma (GB) are highly aggressive brain tumours for which treatment outcomes remain poor, particularly due to intrinsic and acquired resistance to radiotherapy. Molecular determinants, especially TP53 status, play a critical role in regulating tumour cell proliferation, cell-cycle control, and DNA damage response following irradiation. This study investigated the biological effects of the MDM2 inhibitor AMG232 in combination with photon irradiation in TP53- wild-type and TP53-mutant MB and GB cell lines, with the aim of assessing whether AMG232 enhances radiosensitivity in a TP53-dependent manner. Cell proliferation, cell-cycle distribution, and DNA damage were assessed using growth assays, flow cytometry, and H2AX foci analysis, respectively. The findings showed that TP53 status strongly influenced cellular responses to treatment. TP53-wild-type cell lines demonstrated clearer growth control following AMG232 treatment, consistent with activation of functional p53 signalling. In contrast, TP53- mutant cell lines showed slower growth, inconsistent cell-cycle regulation, and weaker responses to AMG232, indicating limited recovery of p53 function. Cell-cycle analysis revealed that AMG232 induced a stronger and more sustained G0/G1 arrest in TP53-wild-type cells, supporting activation of the canonical p53–p21 axis. TP53-mutant cells displayed only partial or transient G0/G1 accumulation, suggesting the involvement of p53-independent stress responses rather than effective checkpoint enforcement. H2AX foci analysis confirmed a dose-dependent induction of DNA DSBs following photon irradiation across all cell lines. AMG232 treatment was associated with increased persistence of H2AX foci, particularly in MB cell lines, indicating impaired or delayed DNA repair. Residual foci at later time points reflected the predominance of error-prone non-homologous end joining, especially in G0/G1-arrested cells. In GB cell lines, DNA repair efficiency remained limited irrespective of treatment, highlighting intrinsic radioresistance. This study demonstrates that AMG232 enhances radiosensitivity primarily by prolonging DNA damage signalling and reducing DNA repair capacity, with effects that are most pronounced in TP53-wild-type cell lines. These findings highlight the importance of TP53 status in determining the therapeutic efficacy of MDM2 inhibition combined with photon irradiation and support the potential for molecularly guided treatment strategies in aggressive brain tumours.
Open Access
Analysis of the peak power of a photovoltaic array system under outdoor conditions at Vuwani Region of Limpopo Province
(2014-01-10) Nekhubvi, Vhutshilo 1st Mountaineer; Sankaran, V.
An attempt has been made to test the performance of a solar array under the outdoor condition. Experimental investigations have been made to find its suitability for the rural Limpopo for the small scale electricity generation. This research is also geared towards the testing of validity of the data provided by the manufacture as the commercially available PV modules are rated at standard testing conditions (STC). A 450W ground mounted photovoltaic (PV) system has been designed and installed at the Vuwani Science Resource Centre in Vuwani region, Limpopo Province, South Africa which has geographical coordinates: 23°07'51"S , 30°04' 28"E. It is well known that the performance of PV system is dependent on system configuration and weather conditions. The instruments and data acquisition packages have been installed to record some of the main parameters such as peak power and air temperature. The estimated data of solar radiation are used in the present work. The photovoltaic array was connected to the maximum power point tracking (MPPT) charge controller to record daily peak power value produced by the photovoltaic array system. In addition to this, for the testing purposes the DS I-V curve tracer was used to take the electrical current and voltage (I-V) curves of the photovoltaic array installed for normal mode as well as the disturbed mode .The peak power data of the PV system over a period of ten months of operation is recorded, analyzed and the results obtained are discussed. It is noted that the PV system designed and installed is suitable for the chosen location.
Open Access
Analysis of the solar radiation data and the determination of regression coeffients for Vhembe Region, Limpopo Province
(2012-12-11) Mulaudzi, Tshimangadzo Sophie; Sankaran, V.; Lysko, M. D.
An attempt has been made to determine the regression coefficients from sunshine hours for the Vhembe Region, Limpopo Province. Parameters such as horizontal average daily extraterrestrial solar radiation (H0) and daily possible sunshine hours (N) were computed. Horizontal average daily global radiation data and daily actual sunshine hour data for the five stations in this study were obtained from Agricultural Research Council (ARC) and South African Weather Services (SAWS). The plots of monthly average daily relative sunshine hours t0 ) versus clearness index(.!!...) were N Ho drawn to determine the values of a and b of Angstrom - Prescott linear equation (where N,, and H represent the actual sunshine hours (in hours) and global solar radiation on the horizontal surface (in MJ) respectively. The variables a and b are the regression coefficients. The results obtained are discussed. From the computations, the values of a and b for Vhembe Region are calculated and the results obtained are compared with the regression coefficients for different countries. The regression coefficients from a station with the best correlation of the coefficients were used to compute the estimated average monthly horizontal global solar radiation for the other four stations and the results compare favourably with our data.
Embargo
Automation of the γ-ray spectrometry setup of the Environmental Radioactive Laboratory at NRF-iThemba LABS
(2026-05-19) Maluleke, Vuako; Nemangwele, Fhulufhelo; Nkadimeng, Edward K.; Ndabeni, Ntombizikhona B.
Environmental γ-ray spectrometry plays a critical role in radioactivity monitoring, radiation protection, and nuclear safety assessments. Conventional spectrometric analysis relies heavily on manual peak identification and expert interpretation, which can be time-consuming and subjective, particularly when dealing with complex environmental samples and varying measurement geometries. This thesis presents the development of an automated and physics-inspired machine learning framework for γ-ray spectrometry, aimed at improving the accuracy, efficiency, and robustness of radionuclide identification at the Environmental Radioactivity Laboratory (ERL) of NRF-iThemba LABS. The primary objective of this research was to integrate domain-specific knowledge from nuclear spectroscopy with advanced machine learning techniques to enable reliable automated analysis of γ-ray spectra. To achieve this, γ-ray spectral data were acquired from five selected radionuclides under controlled experimental conditions, including different counting geometries and known activity concentrations. The resulting dataset captured both the statistical and physical characteristics of detector responses, providing a solid foundation for model training and evaluation. Data preprocessing, feature handling, and visualization were carried out using Python and ROOT, ensuring consistency and reproducibility throughout the analysis pipeline. Two physics-inspired deep learning models, namely Convolutional Neural Networks (CNNs) and Kolmogorov-Arnold Networks (KANs), were developed and optimized for γ-ray spectral classification. These architectures were specifically designed to extract meaningful spectral features by exploiting the physical structure of γ-ray interactions, including peak shapes, Compton continua, and energy-dependent detector responses. By embedding physical intuition into the learning process, the models demonstrated strong generalization capabilities when exposed to previously unseen spectra. The performance of the proposed deep learning models was systematically compared with traditional machine learning algorithms, including k-Nearest Neighbours, Artificial Neural Networks, Support Vector Machines, Random Forests, Decision Trees, and AdaBoost. Evaluation metrics such as accuracy, recall, and area under the receiver operating characteristic curve revealed that the CNN and KAN models consistently outperformed conventional approaches across all radionuclides and geometries. Traditional algorithms exhibited limitations in handling spectral complexity and variability, underscoring the advantage of deep learning methods for high-dimensional nuclear spectroscopy data. To facilitate practical deployment, a Gradio-based interactive dashboard was developed, enabling real-time γ-ray spectrometry analysis. The dashboard allows users to upload spectra and receive immediate radionuclide identification results, along with visual feedback on spectral features and model confidence. This interface enhances accessibility and operational efficiency, bridging the gap between advanced machine learning models and routine laboratory workflows. Overall, this research demonstrates that physics-inspired deep learning provides a powerful and reliable approach to automated γ-ray spectrometry. The proposed framework represents a significant advancement in environmental radioactivity analysis and establishes a foundation for future extensions involving additional radionuclides, higher-resolution detectors, and adaptive learning strategies for real-world monitoring applications.
Embargo
Commensal searches for radio transients variables in the data from Mhongoose Large Survey Project
(2025-09-05) Tshilengo, Vhuthu Miranda; Woudt, P. A.; Maluta, N. E.
The MeerKAT radio telescope in South Africa, a precursor to the mid-frequency component of the Square Kilometre Array (SKA1-Mid), offers exceptional sensitivity and a wide field of view, making it ideal for exploring time-domain radio astronomy. This dissertation presents the use of MeerKAT images from three different fields of the MHONGOOSE Large Survey Project (LSP) to identify radio transient and variable sources. Each of these three fields consists of 10 different epochs spanning time scales of order one month to over 1 year. The MHONGOOSE survey operates at a central observing frequency of 1.28 GHz. I made use of South African Radio Astronomy Observatory (SARAO) Science Data Processing (SDP) images of the MHONGOOSE observations, with source detection and variability analysis conducted via the Transient Pipeline (TraP) software on the Inter-University Institute for Data Intensive Astronomy (IDIA) cloud. The light curves generated by TraP enabled the calculation of variability parameters: the reduced weighted chi-square (χ2) of a fit that assumes constant brightness represented by the symbol (ην) and the coefficient of variation (Vν). Analysis of ten epochs across the fields of NGC 1566, NGC 5068, and NGC 1371 led to the identification of 31 variable sources. All variable sources identified in this study are associated with known objects listed in existing multi-wavelength catalogues and are classified as active galactic nuclei (AGNs). One radio transient was found in the NGC 1566 field “SRC76717”, which is associated with a nearby flaring M dwarf located at a distance of 48 pc (Doyle et al., 2019).
Embargo
Comparative Assessment of Grid-Tied and Isolated PV/Hybrid Energy System for Grid-Connected Facilities: Case of Masia Development Centre and Vuwani Science Centre Energy Systems
(2025-09-05) Muronga, Shandukani; Tinawro, D.; Mulaudzi, T. S.
The study underscores the significance of a sustainable energy system for national progress, particularly highlighting the increasing adoption of solar photovoltaic (PV) in South Africa. Solar PV integration into the current power generation systems offers financial and ecological benefits, but determining the optimal configuration, especially in areas with an existing utility grid, is challenging. A walk-through energy audit was conducted at the Masia Community Development Centre and the Vuwani Science Centre to establish accurate energy demand profiles. Using the Hybrid Optimisation Model for Multiple Energy Resources (HOMER), the study analysed load characteristics for two sites: the Masia Community Development Centre and the Vuwani Science Centre. Results show that grid-connected (GC) systems outperform off-grid (OG) systems in technical and economic terms, as evidenced by their lower net present cost (NPC) and levelized cost of energy (LCOE) values, alongside higher power output. However, GC systems’ reliance on grid electricity, often derived from non-renewable sources, increases greenhouse gas emissions. Among the evaluated configurations, the Photovoltaic-Grid-Converter (PV/Grid/Conv) architecture emerged as the most cost-effective, delivering low NPC, LCOE, and operating costs of R1,852,811.00, R1.63, and R20,878.56, respectively, for Masia, and R2,969,068.00, R1.07, and R83,039.74 for Vuwani. When scaled to Masia’s total facility demand, values reached R15,768,780.00 NPC, R1.90 LCOE, and R365,062.00 operating costs. Despite its efficiency, the PV/Grid/Conv system struggles with nighttime supply. It is vulnerable to load shedding, suggesting the advantage of incorporating PV/Battery/Grid/Converter (PV/Batt/Grid/Conv) systems for enhanced reliability in critical applications. The off-grid (OG) systems remain vital for remote locations where grid extension is impractical, enabling sustainable electrification, reduced fossil fuel dependence, and greater energy independence. This analysis offers valuable guidance for energy planners and system designers, balancing economic performance, environmental impact, and reliability in PV system deployment.
Open Access
Comparison and evaluation of empirical and machine learning models in estimating global solar radiation in Limpopo province
(2023-10-05) Murida, Thalukanyo Witney; Mulaudzi, T. S.; Maluta, N. E.; Mphephu, N.
This study investigated the performance of machine learning techniques as compared to the empirical models to forecast the global solar radiation in Limpopo regions. The machine learning techniques used in this study are Support Vector Machines, Random Forest, and Artificial Neural Network, and the empirical models used are the Clemence and Hargreaves- Samani models. To assess the efficiences of the machine learning models against the empirical models, the researchers calculated and compared the models performance evaluation using statistical equations such as Coefficient of determination, Mean Square Error, Mean Absolute Error, and Root Mean Square Error. Calibaration was done to improve performance of the empirical models. The present study found that machine learning techniques perform better than the empirical models when estimating the global solar radiation in the selected Limpopo regions.
Open Access
Computational study of low index surface of an anatase TiO2 doped with ruthenium (Ru) and strontium (sr) for application in Dye sensitized solar cells
(2019-05-18) Nemudzivhadi, Hulisani; Maluta, N. E.; Maphanga, R. R.
Titanium dioxide (TiO2) is considered to be an ideal semiconductor for photocatalysis because of its high stability, low cost and safety towards both humans and the environment. Doping TiO2 with different elements has attracted much attention as the most important way of enhancing the visible light absorption, in order to improve the efficiency of the dye sensitized solar cells (DSSCs). In this study, first principle density functional theory was used to investigate electronic and optical properties of bulk anatase TiO2, undoped, and ruthenium (Ru) and strontium (Sr) doped anatase TiO2 (1 0 0) surface. Two different doping approaches i.e., substitutional and adsorption mechanisms were considered in this study. The results showed that absorption band edges of Ru and Sr-doped anatase TiO2 (1 0 0) surface shift to the long wavelength region compared to the bulk anatase TiO2 and undoped anatase TiO2 (1 0 0) surface. Also, the results revealed that the band gap values and the carrier mobility in the valence band, conduction band and impurity energy levels have a synergetic influence on the visible-light absorption and photocatalytic activity of the doped anatase TiO2 (1 0 0) surface. Furthermore, according to the calculated results, we propose the optical transition mechanisms of Ru and Sr-doped anatase TiO2 (1 0 0) surface. Thus, we conclude that the visible light response of TiO2 can be modulated by doping with both Ru and Sr. However, Sr-doped system shows higher photocatalytic activity than the Ru-doped system. The study has successfully probed the interesting optical response mechanism of TiO2 (1 0 0) surface.
Open Access
Density functional theory study of adsorption of cronconate dyes on TiO2 Anatase (010) and (100) surfaces
(2019-05-18) Ranwaha, Tshifhiwa Steven; Maluta, N. E.; Maphanga, R. R.
Currently the dye sensitized solar cells have attracted more attention due to their low cost, transparency and flexibility. These types of solar cells use the dye molecule adsorbed on TiO2 semiconductor in Nano architecture with the role of absorbing photons, in recent research attempts are being made to shifts the absorption spectral of TiO2 to visible and near infrared–region of solar spectrum to achieve maximum photo absorption which yields to an increase in the efficiency of the dye sensitized solar cells. In the current study, density functional theory (DFT) was used to model two croconate dyes (CR1 and CR2), one with an electron donating methyl group (CR1) and the other with an electron –withdrawing caboxyl group (CR2). The geometric, electronic and optical properties of these dyes were compared. The adsorption behaviour of the two dyes on (010 and 100) anatase TiO2 surfaces were investigated in this study by employing first principle calculation based on DFT using a plane-wave pseudo potential method. The generalized gradient approximation (GGA) was used in the scheme of Perdew-Burke Ernzerhof to describe the exchange -correlation function as implemented in the CASTEP package in Material Studio of BIOVIA. The adsorption results shows a spontaneous electron injection followed by efficient regeneration of the oxidized dye molecules by the electrolyte and strong binding ability of CR2 to the TiO2 surface, but also shows a comparable binding strength of CR1. The results of this study will help in the design of high efficient dye for DSSCs.
Open Access
Density functional theory study of copper zinc tin (Cu2ZnSnS4) with Calcium and Barium
(2020-08-24) Mlotshwa, Thokozane Mxolisi; Maluta, N. E.; Maphanga, R. R.; Kirui, J. K
The sun is the most important source of renewable energy today. Producing energy from sunlight using cheap, abundant and non-toxic materials is considered a major challenge in the field of solar-electrical energy conversion. Fossil fuel combustion, depletion of non-renewable sources, global warming and environmental degradation are some of the push factors towards clean, non-toxic and environmentally friendly methods of producing electrical energy. To harvest solar energy, a thin film solar cell composed of the Cu2ZnSnS4 (CZTS) semiconductor is a candidate, which can harvest useful amounts of energy. Some of its advantages are the optical direct band gap and high absorption coefficients. In this study, CZTS is investigated as a material for solar cells using first principle method. Thus, structural, electronic and optical properties of pure CZTS and doped CZTS (112) surface were investigated using the density functional theory as implemented in the Cambridge Serial Total Energy Package code. Alkali earth metals, Calcium (Ca) and Barium (Ba) were adsorbed on the CZTS (112) surface using the adsorption locator module. The results suggest that doping with barium rather than calcium could improve the photocatalytic activity on the CZTS based solar cells. Doping using different elements yielded improved optical and electronic properties of the CZTS based solar cells.
Open Access
Density functional theory study of TiO2 Brookite (100), (110) and (210) surfaces doped with ruthenium (RU) and platinum (Pt) for application in dye sensitized solar cell
(2018-05-18) Dima, Ratshilumela Steve; Maluta, E.N.; Maphanga, R. R.
Since the discovery of water photolysis on a TiO2 electrode by Fujishima and Honda in 1972, TiO2 has attracted extensive attention as an ideal photocatalytic material because of its excellent properties such as high activity, good stability, nontoxicity and low cost. Hence, it has been widely used in the fields of renewable energy and ecological environmental protection. However, as a wide band gap oxide semiconductor (Eg = 3.14 eV), brookite TiO2 can only show photocatalytic activity under UV light irradiation (λ < 387.5 nm) that accounts for only a small portion of solar energy (approximately 5 %), in contrast to visible light for a major part of solar energy (approximately 45 %). Therefore, effectively utilizing sunlight is the most challenging subject for the extensive application of TiO2 as a photocatalyst. Due to the unique d electronic configuration and spectral characteristics of transition metals, transition metal doping is one of the most effective approaches to extend the absorption edge of TiO2 to the visible light region. This method of doping either inserts a new band into the original band gap or modifies either the conduction band or valence band, improving the photocatalytic activity of TiO2 to some degree. In this work, the structural, electronic and optical properties of doped and undoped TiO2 (100), (110) and (210) surfaces were performed using first principle calculations based on DFT using a plane-wave pseudopotential method. The generalized gradient approximation was used in the scheme of Perdew-Burke-Ernzerhof to describe the exchangecorrelation functional as implemented in the Cambridge Sequential Total Energy Package code in the Materials Studio of BIOVIA. The metal dopants shift the absorption to longer wavelengths and improves optical absorbance in visible and near- IR region. The un-doped (210) surface showed some activity in the visible and near IR region.
Open Access
Determination of global solar radiation using temperature-based model for different climate conditions for Limpopo Province of South Africa
(2022-07-15) Mathebe, Sampie Mphagala; Maluta, N. E.; Mulaudzi, T. S.
The research mainly focused on the determination of global solar radiation using temperature-based model by Hargreaves and Samani for the Northern regions of Limpopo Province of South Africa. The daily maximum and minimum temperature data measured at the following six (6) stations were used: Ammondale, Mutale, Nwanedi, Roedtan, Sekgosese and Xikundu for the period 2008 – 2010. The values of empirical coefficient Kr for the Inland stations of South Africa were computed and used as an input to the model. The observed and calculated global solar radiation data were compared on the basis of the statistical error tests that is mean bias error (MBE), the mean percentage error (MPE) and the root mean square error (RMSE). Based on the statistical results the model was found suitable to estimate monthly average daily global solar radiation for the regions listed above and elsewhere with similar climatic conditions and areas where the radiation data is missing or unavailable. Hence, the study will also help to advance the state of knowledge of global solar radiation to the point where it has applications in the estimation of monthly average daily global solar radiation across.
Open Access
Development of a mathematical model for predicting bio-slurry temperature and subsequent gas production rate for underground brick-built biogas digester using ambient air temperature forecast
(2022-11-10) Nekhubvi, Vhutshilo 1st Mountaineer; Tinarwo, David; von Blottnitz, Harro
Background: Heat energy is essential for the anaerobic digestion of organic materials such as household, human or agricultural waste. Many developing countries have witnessed efforts to implement anaerobic digestion technology for biogas production as a strategy to enhance energy supply and poverty eradication in rural communities. Underground, brick, and mortar built fixed dome type digesters are the most deployed small-scale biogas technology in sub-Saharan Africa (SSA) countries such as Rwanda, Ethiopia, Tanzania, Kenya, Uganda, Burkino Faso, Cameroon, Benin, Senegal, and South Africa despite their relatively high initial costs. They have a long lifespan and no moving or rusting parts involved. The basic design is compact, saves space, is well insulated, and does not need additional heating, hence suitable for developing countries. The technology is labour-intensive that involves digging the pit and constructing the structure from underground, thus creating local employment. Unlike prefabricated biogas digesters, underground, brick, and mortar-built fixed dome type digesters are more robust than the latter, with minimal gas pipes corrosion experienced. However, little literature on this type of digesters' actual field operation and performance within the SSA context is available. The end-user must know what needs to be done and what the system's outcome is supposed to be. Besides determining parameters like total solids, volatile solids, carbon-nitrogen ratio, hydrolysis rate, organic loading rate, and hydraulic retention time, the temperature inside the digester becomes one of the metrics to evaluate the anaerobic digestion process. The digestion temperature critically affects the biogas yield, considering all other conditions unchanged. Knowing the operational temperature, one can estimate the maximum specific growth rate of the microorganisms and the biogas production rate. Prediction models for the internal operating temperature of these digesters under local conditions typical of Limpopo province of South Africa, where most of these digesters have been installed, are still lacking. To ordinary users in rural areas, the prediction of the possible 'duration of use,' for example, the duration of continuous cooking, is essential. However, regardless of fulfilling all other operational requirements to predict daily gas production, internal digester temperature remains the missing link to having a complete set for a quick and easy gas yield estimation. Aim of the study: The overall objective was to develop a locally applicable model for predicting the bio-slurry operating temperature of underground brick-built domestic size biogas digesters. The work established a correlation of ambient air temperature with the slurry temperature inside the digester using a heat transfer mechanism through the media between the fermenting slurry and the ambient air. Methodology: A thermodynamic study of a small-scale fixed-dome Deenbandhu biogas digester model was performed by monitoring the digester's temperature and surroundings. The K-type chromium-nickel temperature sensors with a sensitivity of 41 μV/°C and a response time of 0.8 s in liquids were positioned at the centre of the digester to measure the slurry temperature. Another temperature sensor was placed 2.0 m above the ground to measure ambient air temperature. The sensors were connected to the data logger and programmed to record temperature readings every second, automatically averaged hourly and daily. The soil surface heat flux was computed using Fourier's law of heat conduction to strengthen the model. Results: The average daily bio-slurry temperature of the digesters ranged between psychrophilic and mesophilic ranges. The results show a strong correlation between bio-slurry and ambient air temperature. A strong correlation was obtained between the measured and predicted temperature of the fermenting slurry inside the digester with a ()Pr|t|>value less than 2e-16 ***, showing that the model is most significant. A Q-Q plot was also used to measure the importance of each observation to the regression. Conclusion: The developed models can accurately estimate the bio-slurry temperature inside the digester using local ambient air temperature data. The set equation adds value as input to the research of small-scale household biogas digesters. Furthermore, the biogas production rate was calculated using data on predicted slurry temperature. It was found that the biogas production rate is satisfactory, given the condition of the study area. The biogas production rate varies from as low as 0.18 m3m-3d-1 during the cold month to 0.48 m3m-3d-1 during the warmest month. Temperatures above 20 ℃ were more conducive to a high biogas production rate.
Open Access
Estimation of Global Solar Radiation from SAURAN stations using air temperature-based models Hargreaves and Samani and Clemence models
(2020) Shabangu, Charlotte Beauty; Maluta, N. E.; Mulaudzi, T. S.
Knowledge of the amount of solar radiation available in a location is important for solar energy systems, architectural designs, agronomy, and installation of pyranometers. Some developing countries do not have good quality meteorological stations that can directly measure global solar radiation. Thus, several empirical methods were developed to estimate global solar radiation. This study uses two temperature-based models which are Hargreaves - Samani and Clemence models. Four selected stations from the Southern African Universities Radiometric Network (SAURAN) for this study are University of KwaZulu–Natal, Howard college (KZH), University of Stellenbosch (SUN), Nelson Mandela University (NMU) and University of Venda (UNV). A three-year (2014-2016) temperature data for each station were sourced from SAURAN. The performance of the two models was validated using statistical analysis that is, Mean Percentage Error (MPE), Mean Bias Error (MBE), Root Mean Square (RMSE), Coefficient of Determination (R2) and t-statistical value (t). Both models obtained acceptable values of MBE, MPE, RMSE, R2 and t in KZH, NMU and UNV stations. Both models achieved the best values of MBE from 2014 to 2016, ranging from -0.0099 to 0.0147 in KZH station, followed by NMU with MBE values ranging from - 0.0293 to -0.0014, -0.0104 to 0.0330 for SUN station, 0.0241 to 0.0245 for UNV station. The models achieved MPE values between ± 10 % in all the stations. The R2 values for both models are close to 1, while the t-statistic values of one, which is less than critical value, was achieved by the models from all selected stations. This suggests that both models have got capacity to estimate global solar radiation in all the selected areas of study. However, the higher values of MBE and RMSE also revealed high level of overestimation by the models in SUN station. Therefore, this study has found evidence that both Hargreaves - Samani & Clemence models can be best recommended for estimating global solar radiation in KZH, NMU and UNV stations and areas with similar climatic and meteorological conditions.
Open Access
Evaluation of the regression coefficients for South Africa from solar radiation data
(2019-09-20) Mulaudzi, Tshimangadzo Sophie; Maluta, N. E.; Kirui, J. K.
The knowledge of solar radiation in this dispensation is crucial. The lack of grid lines in the remote rural areas of South Africa necessitates the use of solar energy as an alternative energy resource. Solar radiation data is one of the primary factors considered for the installation of renewable energy devices and they are very useful for solar technology designers and engineers. In some developing countries, estimation of solar radiation becomes a challenge due to the lack of weather data. This scenario is also applicable to South Africa (SA) wherein there are limited weather stations and hence there is a dire need of estimating the global solar radiation data for all climatic regions. Using a five year global solar radiation (𝐻) and bright sunshine (𝑆) data from the Agricultural Research Council (ARC) and South African Weather Service (SAWS) in SA, linear Angstrom – Prescott solar empirical model was used to determine regression coefficients. MATLAB interface was used whereby the linear regression plots were drawn. Annual empirical coefficients of 22 stations were determined and later the provincial values. The range of the regression coefficients, a and b were 0.216 – 0.301 and 0.381 – 0.512 respectively. The 2006 estimated global solar radiation per station in a province calculated from the modified models were compared with the observed and statistically tested. The root mean square errors were less than 0.600 MJm−2day−1 while the correlation relation ranged from 0.782 – 0.986 MJm−2day−1. The results showed the regression coefficients performed well in terms of prediction accuracy.
Embargo
First principle study of Nax[TiyZnzMnw]O2 as a cathode material for sodium-ion batteries
(2025-09-05) Ranwaha, Tshifhiwa Steven; Maluta, N. E.; Maphanga, R. R.
The fast-growing energy generation from renewable sources such as solar, wind, and waves is calling for reliable energy storage technologies with high energy density, high power, and low cost, because the energy harvested from these renewable energy sources is intermittent. Currently, the leading technology in energy storage is the lithium-ion battery (LIB), While lithium possesses numerous electrochemical advantages that make it a critical component in modern energy storage technologies, its continued viability is increasingly challenged by the rapid depletion of accessible lithium reserves and its uneven geographical distribution, which pose significant constraints on sustainable and equitable resource utilization. The development of electric vehicles and plug-in hybrid electric vehicles has raised everybody’s expectations as well as requirements for the materials employed. That is why there is an urgency to find alternative technologies which would replace LIBs. In search of alternative technology, sodium-ion batteries are a promising solution for large-scale electrochemical energy storage, owing to their low cost, materials abundance, good reversibility, and decent energy density. For sodium-ion batteries to achieve comparable performance to current lithium-ion batteries, significant improvements are still required in cathode, anode, and electrolyte materials. In this study, first- principles method based on the density functional theory was used to investigate the structural, electronic, mechanical and thermodynamics properties of Na intercalated electrode material NaxMnO2 electrode materials doped with Titanium (Ti) and Zinc (Zn) using random substitution doping method. The investigation was based on the effect of Na atom de-intercalation on the 2 X 1 X 1 NaxMn0.5Ti0.5O2 and 2 X 1 X 1 NaxMn 0.5Zn 0.5O2 supercells. The effects of dopants Ti and Zn on the NaXMnO2 stretch the lattice v parameters, resulting in volume expansion, this is because the atomic radii of the dopants are not the same as those of the host Mn. The electronic properties of the two doped systems show that the band gap is reduced by the effect of the dopants. The calculated elastic constants for the NaxMn0.5Ti0.5O2 and NaxMn0.5Zn0.5O2 bulk structures, as well as the NaxMn0.5Ti0.5O2 and NaxMn0.5Zn0.5O2 supercells, indicate mechanical stability for this compound as they meet the monoclinic structure mechanical stability criterion. In further investigation, the voltage window for the Ti-doped system was found to be between 3.410 V and 4.132 V. We found the voltage window for the Zn-doped system to lie between 2.221 V and 4.337 V. The calculated formation energies are negative, indicating that the material is thermodynamically stable and potentially amenable to synthesis under standard conditions. This inherent stability, coupled with favorable electrochemical characteristics such as appropriate voltage profiles, sufficient capacity, and adequate ionic conductivity, positions the material as a promising candidate for cathode applications in sodium-ion batteries. Furthermore, the cluster expansion formalism was used to investigate the NaxMnTiO2 and NaxMnZnO2 phase stabilities. The method determines stable multi-component crystal structures and ranks metastable structures by the enthalpy of formation while maintaining the predictive power and accuracy of first-principles density functional methods. The findings predict that all nickel-doped LMO structures on the ground state line are most likely stable. Relevant structures are NaMnO2, NaTiO2, NaTiMn2O2 and NaTi2MnO2 for NaxMnTiO2 CE-predicted structures and NaMnO2, NaZnO2, Na3Mn2ZnO6, Na6MnZn5O12, Na6Mn2Zn4O12, Na2MnZnO4 and Na5Mn4ZnO10 for NaxMnZnO2 CE-predicted structures. They were selected based on how well they weighed the cross-validation score (CVs) of 1.7 meV for NaxMnTiO2 CE-predicted structures and 1.9 meV NaxMnZnO2 CE-predicted structures, which is a statistical way of describing how good the cluster expansion is at predicting the energy of each stable structure. Although the structures have different symmetries and space groups, they were further investigated by calculating the structural, electronic, mechanical, and thermodynamical properties. The results show that all CE-predicted structures have a wide diffusion compared to the parent structure (NaMnO2). The reduction of band gap was also observed which give evidence that the structures are becoming metals and have an improved conductivity. The results showed that all the predicted structures met the stability requirements for monoclinic structures and were stable in terms of thermodynamics. For Ti-doped systems, the ductility was only observed on NaTiMn2O2 CE-predicted structure NaMnO2 doped with Zn found to be ductile which implies that these materials can bend without deformation, resulting in fewer cracks during battery operation. This study enhances the fundamental understanding of dopant-induced effects on NaMnO₂-based cathode materials, providing a prospective option to improve Na⁺ mobility, electrical conductivity, and structural stability. It presents a comprehensive analysis of the beneficial effects of Ti and Zn doping in the enhancement of sodium-ion battery performance. It provides the theoretical framework that underpins the development of advanced, cost-effective, economical, and thermally stable cathode materials which are crucial large-scale energy storage applications.
Open Access
First-principles study of Hematite (α-Fe2O3) surface structures doped with Copper (Cu), Titanium (Ti), nickel (Ni) and manganese (Mn)
(2023-05-19) Mabaso, Clarence Vusi; Maluta, N. E.; Maphanga, R. R.
Hematite has attracted research interest for many years due to its application in water splitting. Despite its attractive characters such as a reasonable optical band gap, the semiconductor is still faced with great uncertainty for the accomplishment of hematite based photoelectrochemical cells for water splitting. Doping with transition metals has shown to be a practical solution to overcome some of the limitations faced with hematite by modifying the energy band to improve its photo-electrochemical (PEC) activity. This study explored two surface structures of pure and transition metals (Ti, Cu, Ni and Mn) doped- α-Fe2O3 oriented in the directions (001) and (101). Calculations via the first principle using the density functional theory (DFT) were adopted, the results show that the doping of transition metals in α-Fe2O3 has an effect in modifying both the valence and conduction band edges. Specifically, doping Ti introduces more electrons in the conduction band and fills the unoccupied 3d states, which could improve the rate of charge transportation and likely enhance the electrical conductivity of α-Fe2O3. Doping with Mn, Ni, and Cu has effectively improved the absorption coefficient for α-Fe2O3 (001) and (101) surfaces, in the visible light region. The overall analysis of the results shows an opportunity for a successful photo-electrochemical water splitting application.
Open Access
Forecasting Minute Averaged Solar Irradiance Using Machine Learning for Solar Collector Applications
(2023-05-19) Nemalili, Ronewa Collen; Jhamba, I.; Kirui, J. K.; Sigauke, C.
Challenges in utilising fossil fuels for generating energy call for the use of renewable energy. This study focuses on modelling and forecasting solar energy and optimum tilt angle of solar energy acceptance using historical time series data collected from one of the South African radiometric stations, USAid Venda station in Limpopo province. In the study we carried out a comparative analysis of Random Forest and Bayesian linear regression in short-term forecasting of global horizontal irradiance (GHI). To compare the predictive accuracy of the models, k-Nearest Neighbors (KNN) and Long short-term memory (LSTM) are used as benchmark models. The top two models with the best performances were then used in hourly forecasting of optimum tilt angles for harvesting solar energy. The performance measures such as MAE, MSE, and RMSE were used and the results showed RF to have better performance in forecasting GHI than other models, followed by the LSTM and the third best model was the KNN whereas the BLR was the least performing model. RF and LSTM were then used in modelling and forecasting the tilt angles of optimal solar energy acceptance and as thus, the LSTM outperformed the RF by a small margin.
Open Access
Investigation of covariability between energy fluxes and CO2 exchange over a semi-arid savanna (Kruger National Park) by Eddie Covariance Technique
(2024-09-06) Takalani, Lufuno; Mulaudzi, T. S.; Maluta, N. E.; Mateyisi, M.; Thenga, H.
South Africa faces climate change, natural disasters, and rising temperatures due to increased levels of carbon dioxide in the atmosphere, primarily caused by deforestation, burning fossil fuels, and releasing carbon dioxide into the atmosphere without additional carbon sinks. The gap in understanding lies in studying the connection between energy flows and Net Ecosystem Exchange (NEE) at the semi-arid savanna of Kruger National Park to gain a more detailed and accurate understanding of these processes, especially in semi-arid savannas that are susceptible to changes in environmental factors. By studying energy fluxes and NEE at Kruger National Park using the eddy covariance technique, the dissertation seeks to deepen our understanding of the mechanisms driving carbon exchange in semi-arid savannas and provide insights into the impact of environmental factors on ecosystem processes. The eddy covariance technique is a powerful tool that directly measures energy and carbon dioxide exchange between the land surface and the atmosphere. The study shows that the correlation between NEE and latent heat flux (LE) and net radiation (Rn) is generally the strongest, while ground heat flux (G) and sensible heat flux (H) have little impact on NEE. The dataset provides insight into the biometeorological and flow dynamics of the Skukuza ecosystem and how it responds to climate change. The study emphasizes the importance of considering seasonality, climatic variability, and precipitation when studying the surface energy balance and its components. The findings have implications for understanding the complex interactions between ecosystem processes and environmental factors.
Embargo
Investigation of Pd-Ti and Ni-Ti Multilayer Thin Films for Enhanced Hydrogen Storage Capacity
(2026-05-19) Nemukula, Enos; Nemangwele, Fhulufhelo; Mtshali, Christopher B.
The development of compact and secure storage solutions for hydrogen in solid-state materials presents significant challenges and demands. High-capacity storage technologies that operate effectively at low pressures and exhibit favourable kinetics in absorption and desorption are essential for hydrogen storage solutions. The slow kinetics of hydrogen adsorption and desorption present limitations in metal hydride storage. This investigation utilised advanced materials, specifically palladium-coated and nickel-coated metals, to explore potential enhancements in hydrogen adsorption and desorption. Palladium and nickel act as adsorption catalysts, thereby enhancing the kinetics of hydrogen diffusion into metal interstitial sites. This study examined the multilayers of Pd-Ti and Ni-Ti, which were synthesised and evaluated for hydrogen storage and the kinetics of absorption and desorption. The Pd/Ti/Pd/Ti and Ni/Ti/Ni/Ti multilayers were fabricated using an e-beam evaporator and annealed at different temperatures. Rutherford backscattering spectroscopy confirmed the formation of multilayers, consisting of pure palladium and nickel layers. The titanium layers in both systems exhibited a significant amount of oxygen contamination (up to 63 at.% in the Pd-based system and 61 at.% in the Ni-based system), which was picked from the deposition chamber as residual gases. Hydrogen profiling performed at iThemba LABS revealed a strong temperature dependence of the hydrogen absorption in the multilayers. For both the Pd-Ti and the Ni-Ti based systems, the hydrogen absorption peaked at 200 ◦C. For the Pd-Ti system, the average hydrogen concentration was 3.72 at.% and a total concentration of 51.34 at.%, while Ni-Ti multilayers showed a maximum absorption of 2.58 at.% and a total hydrogen uptake of 46.42 at.%. The hydrogen absorption declined at elevated temperatures, which was likely due to hydrogen embrittlement and structural degradation. X-ray diffraction confirmed the formation of titanium hydrides and tracked the phase transformation with temperature. Atomic force microscopy revealed changes in the surface roughness and morphology. The surface roughness showed the structural response to the hydrogenation temperature. The root mean square roughness for both samples showed a correlation with the total hydrogen content absorbed.