Theses and Dissertations (Chemical Engineering)

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    Production of biodiesel from waste vegetable oil and methanol using industrial brine sludge waste from chloro-alkali as a nanocomposite heterogeneous catalyst
    (Vaal University of Technology, 2023-02) Muthubi, Shonisani Salvation; Shoko, L., Dr.; Rutto, H. L., Prof.
    Biodiesel production as a diesel engine fuel has increased substantially in recent years and is expected to rise more in the near future. Rapidly increasing biodiesel production necessitates efficient production processes that enable huge production capacities, simplified operations, high yields, and inexpensive feedstocks such as waste oils and animal fats. In this work, biodiesel was produced using waste vegetable oil (WVO) and Methanol (CH3OH) in the presence of a catalyst synthesized from industrial waste, primarily calcium carbonate (CaCO3). Fourier Transform Infrared (FTIR), Scanning Electron Microscope (SEM), and X-ray diffraction (XRD) were used to analyze the manufactured nano-particle catalyst. The optimum operating conditions for the highest biodiesel yield after applying the artificial neural network (ANN) approach was 96.41% yield at a temperature of 60°C, catalyst loading of 1% w/v, methanol to oil ratio of 1:5 w/w and reaction time of 80 min. The FTIR showed the presents of the CaO and NCC functional groups. Based on the SEM image, the catalyst produced was more porous, with small particle size. The XRD pattern indicates calcium oxide (CaO) and cellulose (NCC) nanoparticles. The ANN approach was suitable for predicting biodiesel with an overall correlation coefficient (of 0.990). Furthermore, the Response surface methodology (RSM) was used to determine the optimum operating conditions for the highest biodiesel yield. After applying the RSM methods using the CCD experimental design, the optimum biodiesel production was found at a temperature of 55°C, catalyst loading of 1.25% w/v, methanol to oil ratio of 1:5 w/w, and reaction time of 75 min with an average yield of 94.01%. The R2 of 0.963 was found for the mathematical models to predict biodiesel production.
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    Removal of oil and grease from industrial wastewater by using advanced oxidation process
    (Vaal University of Technology, 2022-05) Mthethwa, Sikhumbuzo Abednigo; Seodigeng, Tumisang, Prof.; Tshilenge, John Kabuba, Prof.
    The aim of this study was to removal of oil and grease from the wastewater sample from Fuel Firing Systems (FFS) refinery factory contaminated with the Fats Oil and Grease (FOG), Chemical Oxygen Demand (COD), Total Suspended Solid (TSS) and Total Organic Carbon (TOC). The wastewater sample was investigated using hydrogen peroxide. The sample was treated at the controlled flow rate in the ozonation reactor, this was done by bubbling the ozone through a stone diffuser at the ratio of 1 litre of wastewater sample and 2 mL of hydrogen peroxide on the first run. Each experiment run for 30 min each sample were taken 15 min time intervals for treatment of wastewater sample. The second run 1 litre of wastewater sample, 3 mL of hydrogen peroxide for 45 min treated. The third run 1 litre of wastewater 4ml of hydrogen peroxide for 60 min treated and lastly fourth experiment run with 1 litre of wastewater, 5 mL of hydrogen peroxide treated. All four test run with the common flow rate of 1500 nm3/h of ozonation with the capacity of ozone generator, the first run was 40% capacity, second run was 50% through the generator. The third run was 60% and fourth run with 70% through to ozone generator. During the reaction of ozone and hydrocarbon in wastewater few drops of hydrogen peroxide were added into the solution to speed up reaction at the same time pH was controlled. The results of the experiment shown in chapter 4 the different figures in a graph form, in figure 11 Chemical Oxygen Demand (COD) treated from the Lab and the graph shown is decreasing as per time interval. In Figure 12 results of Fat Oil and Grease (FOG) after treated, the graph shown decreased as well shown less pipe clogging in the systems. In figure 13 Total Suspended Solid (TSS) after treated from the Lab, the graph shown after 30 minutes decrease in addition of Hydrogen peroxide the results from the graph increase until the end. The pH graph shown start to decrease and increase after 30 minutes pH decrease toward neutral.
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    Investigation of sorbent characteristics used in low temperature dry flue gas desulfurization
    (Vaal University of Technology, 2022-04-22) Makomere, Robert Someo; Reynolds, Kelley, Dr.; Koech, Lawrence; Rutto, H. L., Prof.
    Coal is an efficient raw material for generating electric power. However, coal-fired power stations generate a great deal of emissions in the form of exhaust gases from the combustion of coal. The exhaust gases known as flue gas contain a significant amount of greenhouse gases (CO2, SOX, HF, Hg and NOX) that have led to detrimental effects on the environment. Sulphur oxides (SO2 and SO3) present in the exhaust gas stream facilitate acid rain formation while ozone layer depletion is accelerated by the presence of excess carbon dioxide (CO2). Flue gas desulphurization (FGD) is a post-combustion technology used to mitigate specifically SOX emissions from coal power plants. This is per pollution regulations set by air quality regulators for instance the Environmental Protection Agency (EPA). Dry FGD (DFGD) is a current subset of FGD systems that can be easily retrofitted to SO2-generating units at lower capital expenditures compared to wet and semi-dry FGD. In this study, sorbent utilization was tested using a modified nano Ca(OH)2-diatomite sorbent. The reaction occurred in a simulated packed bed reactor consisting of sorbent balls. Cellulose nanocrystals were employed as the precipitating support for Ca(OH)2 formation while diatomite material was used as the siliceous additive. The final sorbent manifested superior scrubbing (𝑌1) and conversion (𝑌2) efficiencies compared to the commercial grade Ca(OH)2. The highest scrubbing and conversion responses were achieved when a diatomite ratio of 0.25 was used. This research also explored experimental modeling using Artificial Neural Networks (ANN), a deep learning MATLAB fitting tool that can be trained to estimate final responses. The learning network using Levenberg-Marquardt (LM) algorithm was statistically compared to the Response surface methodology (RSM) technique to assess performance reliability. ANN was more precise in mapping the predicted responses with the actual experimental values achieving higher R2 values (𝑌1=0.993 and 𝑌1=0.9986) as opposed to those from RSM (𝑌1=0.9753 and 𝑌2=0.9771). Error analysis using RMSE and MSE justified the superior efficacy of the ANN model. The final part of this study evaluated the algorithms present in ANN which can present more acute predicted metadata. Levenberg-Marquardt (LM) and Bayesian Regularization (BR) were chosen and investigated based on their iterations (epochs), validity tests, R2 values, RMSE and MSE. Although the BR algorithm took much more computing time, the predicted and actual values were correlated more effectively compared to the LM training tool. However, both algorithms were reliable in forecasting the sulfation and reagent utilization responses, and hence can be used to model DFGD.
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    Biodiesel production using cellulose-supported calcium hydroxide heterogeneous catalyst. phosphate rock as a catalyst precursor
    (Vaal University of Technology, 2022-06) Kiprono, Janet Jematia; Rutto, H. L., Prof.
    Due to rising gasoline prices and growing worldwide worries about climate change and environmental pollution, the need for a clean, environmentally friendly fuel such as biodiesel has recently gained traction. This has demanded greater study into more efficient techniques to boost biodiesel production. The current study focuses on making and improving the efficiency of calcium hydroxide heterogeneous catalyst to be used in biodiesel manufacturing from waste cooking oil. Phosphate rock, a primary mineral mined in South Africa, containing the compound calcium carbonate in higher quantities, was used to prepare calcium nitrate, a useful compound in nature. Calcium nitrate was then reacted with cellulose nanoparticles and sodium hydroxide solution to obtain cellulose-supported calcium hydroxide catalyst through the co-precipitation method. Characterization techniques such as SEM and FTIR were used to confirm calcium hydroxide loading on the cellulose support material. The efficiency of the synthesized catalyst in the transesterification process was studied by varying the alcohol to oil ratio, amount of catalyst, the reaction temperature, reaction time, and the reusability cycles of the catalyst through one factor at a time method and response surface methodology. Artificial neuron network was later used in the prediction of biodiesel yield. High regression coefficient values were obtained, indicating the efficiency of artificial neuron network tool in the prediction of biodiesel. Calcined phosphate rock is also tested for use as a heterogeneous catalyst for biodiesel production. This is based on the fact that when calcium carbonate in the rock is subjected to extremely high temperatures, the carbonates undergo decomposition releasing carbon iv oxide gas thus forming calcium oxide. This oxide also proved to be an active catalyst for transesterification. The efficiency of this catalyst was also tested through one factor at a time and response surface methodology. Both cases obtained a higher biodiesel yield.
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    The synergistic effect of sewage sludge and bituminous coal co-pyrolysis on bio-oil production
    (Vaal University of Technology, 2023-03) Nkgabane, Baatseba Pearl; Rutto, H. L., Prof.; Osifo, P. O., Prof.
    The application of existing thermochemical conversion technologies for co-conversion of coal and sewage sludge offers a potential route for waste valorisation, reduction of air pollution from coal processing and cost savings. Although extensive research has been conducted and reported on thermogravimetric co-pyrolysis of different types of sewage sludge and coal, there are limited studies on their co-pyrolytic products yield and quality. As a result, the aim of this project was to investigate the potential synergistic effect of sewage sludge and coal co-pyrolysis on the derived co-pyrolytic products yield and organic fraction composition when heated at slow heating rates (<10 °C/min). Coal (BC) from the Highveld coal field in South Africa (SA), anaerobically digested sewage sludge (SS) from a Gauteng wastewater treatment plant in SA and their blended samples (classified as 10C, 30C, 50C, 70C and 90C with ratios of BC: SS as 10:90, 30:70, 50:50, 70:30 and 90:10, respectively) were prepared as feedstock for the test work. The pyrolysis of BC, SS and their blended samples was studied at atmospheric pressure, different final temperatures (520, 720 and 920 °C) and under Argon (Ar) atmosphere using the North-West University (NWU) modified Fischer assay setup and a thermogravimetric analyser (TGA). The BC sample was identified as a medium rank C bituminous coal with a mean random reflectance of 0.71, vitrinite composition of 5.6 vol.% and inertinite composition of 70.0 vol.%. The SS sample consists of higher contents of volatile matter (VM), oxygen (O), nitrogen (N), sulphur (S), hydrogen (H), a higher percentage ash yield (A) and lower contents of fixed carbon (FC), carbon (C) and a lower calorific value when compared to those of the BC. The TG analysis results for the blended samples showed that there exist synergistic interactions between the BC and SS particles that favoured the production of more char than the calculated one. This could be explained by the early release of volatile compounds from the SS sample that inhibit the release of volatiles from the BC sample. The SS and BC samples have different organic and inorganic compounds in their organic carbon matrix that decompose/transform at different temperatures. The NWU modified Fischer assay pyrolysis experiments using SS, BC and their blended samples showed that the final temperature has a large effect on the derived products yields and favoured the production of char over the other pyrolytic products. During individual SS and BC pyrolysis, increasing the temperature from 520 to 920 °C decreased the char yields, increased the pyrolytic gas and water yields whilst the bio-oil and tar yield remained almost constant. The lower BC tar yield (approximately 3 wt.%) in comparison to SS bio-oil yield (approximately 21 wt.%) could be due to its’ low VM (20.9 wt.%, dry basis) and a higher inertinite content. The co-pyrolytic char yields decreased with increasing temperature but increased with increasing amount of BC for all the blends. The highest co-pyrolysis char yield of 84.4 wt.% was achieved at 520 °C with the 90C blend. With regards to the organic fraction, increasing the temperature only had a significant effect on the 50C blend with the yield decreasing from 11.5 wt.% at 520 °C to 3.5 wt.% at 720 °C and remained almost constant for the other blends. The synergistic interactions between SS and BC particles that resulted in the production of a higher organic fraction than expected were dominant at 720 °C for the 30C sample. However, the highest organic fraction yield of 20.0 wt.% was obtained at 520 °C using the 10C blend. Gas chromatography and–flame ionization detection (GC-MS & GC-FID) and simulated distillation (Sim-Dis) analyses of the co-pyrolytic organic fraction indicated that there were insignificant differences in the composition of the 10C and 30C blends at 520 °C. However, the composition of the O-containing, N-containing organic compounds and aliphatic hydrocarbons significantly decreased with increasing content of BC in the blended samples from 30C to 70C. Synergistic interactions resulted in increased aliphatic hydrocarbons, PAHs, naphtha fraction and decrease in light vacuum gas oil fraction.
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    Sludge reduction in an activated sludge wastewater treatment process
    (Vaal University of Technology, 2022-10-21) Seretlo, Manana Alinah; Apollo, Seth, Dr.; Tshilenge, John Kabuba, Prof.
    Sludge process reduction activated sludge (SPRAS) is usually the preferred treatment method at wastewater treatment plants (WWTPs) and for waste activated sludge (WAS), with the advantage of effective sludge reduction. However, the recalcitrant compounds such as pollutants and solids present in the wastewaters are removed by SPRAS process and enhanced sludge reduction with no increment of chemicals, thus yielding the required quality of effluent for reuse. The sludge treatment techniques such as thickening, dewatering, digestion, and final disposal are complex and costly. The cost of dealing with WAS accounts for 30-50% of wastewater treatment total costs (WWTPs). The technology has been successfully implemented in China, with outstanding results. Four SPRAS plants in China, each with a capacity of 20 000 m3/day, have successfully treated municipal sewage to a reusable quality with no zero-sludge production. The cost of wastewater treatment has significantly decreased due to the implemented technology. Moreover, South Africa has harmonized with the SPRAS technology; three SPRAS package pilot plants have been installed. The plants are located in Eastern Cape towns of Cradock and Kirkwood and Free State's Glen Agricultural College. Comparing the activated sludge process, which is commonly used in South Africa for treating municipal sewage, the SPRAS units have demonstrated more remarkable performance. Therefore, the study aims to evaluate the performance of the SPRAS technology, which is installed at Glen Agricultural College in Free State province, South Africa. The installation aims to ensure that the SPRAS system operation is sufficient to produce consistently high-quality treated water for reuse and near-zero sludge discharge and reduce operating costs. SPRAS technology installed at Glen Agricultural College in Free State province, South Africa, produces the sludge yield of the SPRAS plant of 0.026 kg TSS/kg COD which was much lower than the sludge yield of a conventional activated sludge process of 1.2 kg TSS/kg COD. Therefore, the SPRAS plant can achieve > 95% sludge reduction with ultra-Violet (UV) disinfection of the treated wastewater reduced the E. coli concentration to < 10 counts/100 mL which suggest that the treated wastewater can be safely reused in agriculture without adverse infections. The power consumption of SPRAS plant is 1.2 kWh/m3, which is comparable to that of MBR. However, MBR incurs additional cost of sludge handling while SPRAS achieves zero sludge discharge.
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    Chitosan modification with cellulose - gelatin to remove heavy oil from wastewater
    (Vaal University of Technology, 2022-08-30) Fundji, Wato Nathan; Igberase, Ephraim, Dr.; Tshilenge, John Kabuba, Prof.
    In this study, Chitosan was modified with cellulose and gelatin for the removal of Cu2+, Fe2+, and Pb2+ from oily wastewater. Membranes were prepared and characterized using Fourier Transform Infrared spectroscopy (FTIR), Scanning Electron Microscopy (SEM), and X - Ray Diffraction (XRD). Their changes and permeabilities were studied and showed that pH values slightly changed. The effects of pH solution and conductivity were investigated. Adsorption study was performed to remove the heavy metals. The results revealed that the highest % removal of Cu2+ was 96.62 (pH = 7.52 and conductivity = -12 mV), of Fe2+ was 97.95 (pH = 6.30 and conductivity = +68 mV) and of Pb2+ was 98.86 (pH = 10.58 and conductivity = -170 mV) for the 12: 2: 2 ratio and for the other ratio, results were quite similar. To analyse the impacts of experimental factors, experiments were developed using Central Composite Design (CCD) based and the Response Surface Methodology (RSM). R2 values were 0.99, 0.99 and 0.98 correspondingly to the analysis of variances of Cu2+, Fe2+, and Pb2+, respectively while using the 12: 2: 2 ratio but for the other ratio, results were almost the same. In interpreting the experimental data, the quadratic models were significant and appropriate. For all models, the variations between experimental and predicted values of % Removal were insignificant. The resulting 3D response surface graphs allowed for a paired investigation of variable influences upon every response model. This study aimed to develop a new chitosan membrane as a film-forming material with a lower acid content and improved mechanical properties in order to remove heavy oil from wastewater.
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    Use of industrial brine sludge waste from chlor-alkali industry as a source of sorbent for semi-dry flue gas desulphurisation
    (Vaal University of Technology, 2022-07-25) Chepkonga, Bilha J.; Koech, L., Dr.; Rutto, H. L., Prof.
    Stringent antipollution laws have been established to regulate SO2 emissions into the ecosystem. Most power plants in South Africa are fitted with flue gas desulphurisation systems to scrub sulphur dioxide from flue gas(es). Second, to wet scrubbers, spray dry scrubbers (SDS) are gaining prominence due to the generation of a dry product, low water consumption, the robustness of the equipment and high efficiency achieved. Nevertheless, an expensive sorbent (hydrated lime) utilized in SDS raises the overall operational cost of the technique. This study explores the use of sludge generated by a chlor-alkali industry as an alternative source of hydrated lime. Prepared sorbent is then used in a laboratory-scale spray dry scrubber to perform desulphurization test. Characterization techniques sorbent and desulphurisation products was conducted using Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), thermogravimetric analysis-derivative thermogravimetry and scanning electron microscopy(SEM). The effect of process parameters on desulphurisation efficiency and sorbent conversion was investigated. The SO2 removal efficiency of 88.54% was achieved at an inlet temperature of 120°C, sorbent particle size of -45μm, and a Ca:S ratio of 2.5. Calcium conversion decreased with an increase in the Ca:S ratio. Sorbent conversion of 65% was achieved at a gas inlet temperature of 120°C, Ca:S ratio of 1.0 and sorbent particle size of -45μm. The effects of process variables on desulphurisation efficiency using central composite design were also studied. Analysis of numerical optimization revealed that maximum desulphurisation efficiency of 92 % was achieved for particle size of (45-106)μm, an inlet temperature of 140°C, and a Ca:S ratio of 2.0. ANOVA showed that the most significant parameter is Ca:S. A quadratic model was developed to predict desulphurisation efficiency, R2 = 93.47%. Additionally, the effects of highly soluble additives on the performance of prepared hydrated lime in a spray dry scrubber were investigated. The order of additive performance is NaOH> NH4Cl > NH4NO3 > NaCl > Urea. All the investigated additives but urea enhanced the removal efficiency of SO2 above baseline. SO2 content in the model flue gas was reduced by 92.06% and calcium conversion of 54.59% was achieved with 10wt.% Ca(OH) and 8wt.% NaOH which is 45% higher in comparison to the pure sorbent.
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    Production of biodegradable plastic from starch/PVA/glycerol/cellulose blends
    (Vaal University of Technology, 2022-06) Lipharama, Mashudu; Focke, W. W., Prof.; Rutto, H. L., Prof.
    Most municipal waste consists of packaging waste, mainly petroleum-based plastics that are not biodegradable. There is a need to develop biodegradable plastics that naturally degrade after use. This research aims to develop a biodegradable polymer blend of starch/PVA/glycerol/cellulose that exhibits thermal and mechanical properties suitable for packaging purposes. Starch is an abundant biopolymer used to make bioplastics because of its thermoplastic properties. It is of great interest due to its attractive properties such as uncomplicated chemical structure, cost efficiency; biodegradability; availability and renewability. Polyvinyl alcohol is a white crystalline powder biocompatible with starch and is said to improve the thermal and mechanical properties of starch-based materials. It is also known for its remarkable film-forming ability, chemical resistance, and mechanical properties. Cellulose is the most plentiful, ubiquitous, and stable biopolymer. It is reported that plastics composed of cellulose nanocomposites have better physical and mechanical properties than traditional plastics due to the reinforcement provided by the nano-dimensional particles. Plasticizers are used as processing additives to aid in processing, and water and glycerin work best for starch-PVA blends. The samples were prepared using a solvent casting process. The samples were then stored at room temperature in a large airtight plastic container and conditioned to 75% relative humidity. Characterization Thermogravimetric analysis (TGA), Fourier Transform Infrared (FTIR), X-ray diffraction (XRD), Scanning Electron Microscopy (SEM), tensile tests, water absorption and solubility, were performed. Incorporating Hydroxyethyl cellulose (HEC) into cast samples improved the thermal stability of corn starch by 28%. The ultimate tensile strength (UTS) and elongation at the break of the Hi-Maize sample increased by 150% (i.e. from 0.46-1.15 MPa) and by 7.7 % with the addition of PVA. The corn starch samples had better thermal and mechanical properties and also retrograded more slowly than the dextrin samples.
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    Solar photocatalytic degradation and adsorption of emerging pharmaceutical contaminants in wastewater
    (Vaal University of Technology, 2014-09-15) Akach, John Willis Juma Pesa; Onyango, Maurice S., Prof.; Aoyi, Ochieng, Prof.
    Pharmaceutical pollutants in wastewater have become an increasing concern in recent years. Adsorption and photocatalytic degradation of pharmaceutical pollutants have proved to be very efficient in the removal of pharmaceutical contaminants. In this study, a composite catalyst of powdered activated carbon (PAC) and TiO2 bound by silica xerogel (CTS composite) was synthesized and characterised using SEM, XRD and XRF. The composite catalyst was then used to adsorb and photodegrade the pharmaceuticals sulfamethoxazole (SMX), diclofenac (DCF) and carbamazepine (CBZ) in a three phase fluidised bed photocatalytic reactor using sunlight to activate the TiO2. The solar radiation intensity at the Vaal University of Technology and the hydrodynamic behaviour of the reactor were also investigated. Additionally, the effect of catalyst composition and loading, hydrodynamics and solution characteristics on the adsorption and photodegradation of the substrates was investigated. It was found that the solar radiation intensity varied with the hour of day, weather and seasons of the year. SEM showed that the porosity of the composite catalyst increased with increase in the PAC loading and a decrease in the silica xerogel loading. The XRD results showed that the silica xerogel and the PAC did not alter the composition of the P25 TiO2. XRF showed that the method used in the preparation of the substrates resulted in the desired composition of the catalyst. The optimum CTS composition was 60% silica xerogel loading and 10% PAC/TiO2 ratio. The best mass of the composite catalyst was 1.5 g/l. Using the optimal composite composition resulted in over 90% removal of the substrates with low residual solution turbidity of less than 3.5 formazin attenuation units (FAU). The optimum hydrodynamic condition was obtained when the reactor inclination angle and superficial air velocity were 75° and 0.014 m/s, respectively. However, a reactor inclination angle of 75° and a superficial velocity of 0.007 m/s gave the best adsorption and photodegradation of the substrates. Reducing the initial concentration of the substrates resulted in an increase in the efficiency of removal of the substrates. The adsorption and photodegradation of SMX was observed to increase with a decrease in pH and was maximum at pH 4. The adsorption of SMX and DCF was found to follow the Langmuir isotherm model. These results show that the use of the synthesised composite catalyst in the fluidised bed reactor provided a stable and efficient system capable of long term use. The results from this work also show that this system can be used for the removal of pharmaceutical substrates at low concentrations.
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    Flue gas desulphurization by spray dry scrubbing
    (Vaal University of Technology, 2022-03) Koech, Lawrence; Everson, R. C., Prof.; Hattingh, B. B., Prof.; Neomagus, H. W. J. P., Prof.; Rutto, H. L., Prof.
    Post combustion sulphur dioxide (SO2) emission is a major problem facing coal-based power plants. Increased awareness of the detrimental effects of SO2 on human health and the environment has prompted increased pressure to equip power plants with flue gas desulphurization (FGD) systems. FGD is a commercially proven technology for removal of SO2 from flue gas which is considered as a significant pollutant to the environment. Spray dry scrubbing (SDS) process represents a type of semi-dry FGD which is a low-cost retrofit SO2 control technology that could be used in already existing coal-fired power plants. This study explored the experimentation on the performance of a laboratory-scale spray dryer involving flue gas desulphurization (FGD). The experimentation involved test done to investigate the effects of spray characteristics i.e., inlet gas phase temperature, approach to saturation temperature, and calcium to sulphur ratio on SO2 removal efficiency using hydrated lime as a sorbent. Results indicated improved SO2 removal efficiency with increasing the stoichiometric ratio and decreasing the temperature and approach to saturation temperature. An absorption efficiency of SO2 beyond 90% was achieved at a stoichiometric ratio of 2.5. A high degree of conversion of calcium was realized at low stoichiometric ratios with a maximum utilization of 94% obtained at a stoichiometric ratio of 1.5. This study also investigated the interaction effects of independent variables on SO2 absorption using response surface methodology. By analyzing the influence of stoichiometric ratio, inlet gas phase temperature, slurry solid concentration and slurry pH, a predictive quadratic model was developed correlating the independent variables and SO2 removal efficiency. Although all independent variables had impact SO2 removal efficiency, stoichiometric ratio was found to have the largest influence. The recommended optimal conditions for SO2 absorption were inlet gas phase temperature of 140℃, stoichiometric ratio of 2, slurry solid concentration of 8% and slurry pH of 10 to achieve 90% SO2 removal efficiency. An investigation into performance of relevant spray dying FGD sorbents was carried by evaluating different sorbents namely: hydrated lime, limestone and trona. Results show that trona had better performance characteristics with the highest SO2 absorption efficiency when compared to hydrated lime and limestone under the same operating conditions. The analysis of the desulphurization product revealed that trona has better sorbent conversion and utilization in comparison with limestone and hydrated which contained high concentration of unreacted sorbent in the desulphurization product.
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    Application of nonwoven microfiltration membrane on activated sludge final effluent: improving wastewater quality for re-use
    (Vaal University of Technology, 2022-04) Masala, Murendeni Shonisani; Topkin, James; Tshilenge, J. Kabuba, Prof.
    Water scarcity is one of the biggest problems that South Africa is facing currently, as a results it limits economic and social development. The application of membrane technology in wastewater treatment for re-use is one of the alternatives to reduce the demand of water in domestic, agricultural and industrial sectors. The primary aim of this study was to improve effluent wastewater quality prior to disinfection for re-use. This was done by diverting biological nutrient removal (BNR) clarifier effluent to a pilot nonwoven membrane filtration unit. The physical barrier provided by this unit, together with the effect of aeration within this system, provided particulate, physicochemical, and microbial removal. Monitoring of water quality was attained from the BNR clarifier effluent, and the nonwoven membrane permeate. Water quality trends against the standards were analysed for compliance with a water use license (WUL), and the removal efficiency for the permeate was also determined. The Single Factor Pollution Index (Pi) was used to determine the extent of pollution in the BNR clarifier effluent and the permeate, while the Water Quality Index (WQI) was utilised to determine the suitability of water derived from the BNR clarifier effluent and the permeate for re-use. Water Use Licence standards were utilised to determine the Water Quality Index of the BNR clarifier effluent and the permeate. Results for the BNR clarifier effluent showed that the physicochemical water quality parameters comply with the limits however, electrical conductivity (EC) and microbial water quality Escherichia coli (E. coli) were exceeded. Permeate results indicated that physicochemical and microbial parameters were compliant with the limits of the WUL. E. coli reduction was the highest with a removal efficiency of 90%, followed by chemical oxygen demand (COD) at 25%, NH4N at 22%, NO3 at 12.6%, PO4 at 7.8%, suspended solids (SS) at 6.3%, and the lowest was EC at 5.2%. The Single Factor Pollution Index has revealed that the BNR clarifier effluent water quality is medium polluted and the permeate water quality is slightly polluted. The WQI results for the BNR clarifier effluent showed good water quality and the water can be re-used for domestic, irrigation, and industrial purposes, while permeate WQI results indicated excellent water quality and the water can be re-used for drinking, domestic, irrigation, and industrial purposes. Outstanding permeate water quality improvement was observed on E. coli counts improving from 4974.48 counts/L to 294.33 counts/L. The standard of E. coli according to the WUL at Waterval WCW is 500 counts/L. The results indicate that nonwoven membrane filtration can improve microbial contamination and decrease the demand of chlorine for disinfection of wastewater final effluent. The nonwoven membrane filtration can decrease the water scarcity gap in South Africa for direct water reclamation by improving effluent wastewater.
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    Application of neural network techniques to predict the heavy metals in acid mine drainage from South African mines
    (Vaal University of Technology, 2022-04) Maliehe, Andani Valentia; Osifo, P., Prof.; Matjie, H., Dr.; Tshilenge, John Kabuba, Prof.
    Acid mine drainage (AMD) refers to acidic water generated during mining activities and is characterised by a low pH, high salt content, and the presence of heavy metals. To treat water sources contaminated with AMD, sampling and laboratory analysis will have to be done for each water source to determine the concentrations of heavy metals. This process is time-consuming, high in cost and may involve human error or negligence. The application of neural network (NN) techniques to predict the heavy metals in AMD from South African mines has been presented. Four specific objectives were pursued in this dissertation. The first one was to identify AMD and analyse for heavy metals in the AMD. Heavy metals that were identified and found to be in high concentrations in the AMD sample from Sibanye Western Basin AMD Treatment Plant are Zn, Fe, Mn, Si, and Ni. The other objectives of the study were to determine the input, output, and hidden layers of the NN structure (application of NN); (2) to find the appropriate algorithm to train the NN, and to compare the NN results (outputs) with the measured concentrations of major heavy metals sampled (targets). The Backpropagation Neural Network (BPNN) model had three layers which included the input layer (pH, SO42−, and TDS), the hidden layer (five neurons) with a tangent sigmoid transfer function (tansig) and the output layer (Cu, Fe, Mn, and Zn) with linear transfer function (purelin). The predictions for heavy metals (Zn, Fe, Mn, Si, and Ni) using the NN method focusing on a BP forward pass (feed-forward backpropagation NN) with ten different algorithms were presented and compared with the measured data. The mean square error (MSE) value was calculated for ten algorithms and compared to identify the one that is most appropriate for the prediction process and the model by having the lowest value. It was determined that the Levenberg-Marquardt back-propagation (trainlm) algorithm resulted in the best fitting during training because it resulted in an MSE value of 0.00041, meaning the error was very low when this algorithm was used.
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    Production of adsorptive material from modified nanocrystals cellulose for industrial application
    (Vaal University of Technology, 2022-05) Banza, Musamba Jean Claude; Seodigeng, Tumisang, Prof.; Rutto, Hilary Limo, Prof.
    Water is the essence of life, yet it is progressively polluted by dyes, heavy metal ions, food additives, medicines, detergents, agrochemicals, and other toxins from industrial, municipal, and agricultural sources. Among the different wastewater treatment technologies, adsorption is a technique that, when used in conjunction with a welldesigned system, produces high-quality treated water at a reasonable cost. For water treatment, activated carbon is the most often employed adsorbent. Its manufacture, on the other hand, is energy demanding, costly, and creates greenhouse emissions. As a result, finding low-cost alternative adsorbents from industrial and agricultural waste and biomass has attracted a lot of interest. In this context, developing sustainable platforms for wastewater treatment using sustainable nanomaterials such as cellulose nanocrystals (CNCs) is a unique technique with a low carbon footprint. CNCs, which are made by hydrolyzing pulp fibers in sulfuric acid, are rod-like nanomaterials with a lot of remarkable qualities including high specific surface area, high specific strength, hydrophilicity, biodegradability, and surface functionalization. These characteristics, as well as their accessibility, make them suitable candidates for water treatment applications. However, because of their great colloidal stability and nano-dimensions, extracting these CNCs after usage in water treatment is difficult. To overcome this problem, including these CNCs into nanocomposite systems that can be readily separated after usage in batch and continuous water treatment processes is a great concept. Furthermore, pure CNCs have low selectivity towards a wide range of water pollutants, necessitating surface functionalization to provide this selectivity. As a result, this thesis investigates the extraction of CNCs from millet husk waste and waste papers, the development of CNC-incorporated nanocomposites and evaluation of their adsorption characteristics using batch and fixed bed column adsorption studies, and (ii) the evaluation of the selective adsorption characteristics of surface functionalized CNCs and their ability to tailor the nanocomposites' characteristics for use in water treatment applications. The response surface methodology, artificial neural network, and adaptive neuro-fuzzy inference systems were also applied to model the removal of heavy metal ions. The first part of the research (cellulose nanocrystals extraction and optimization) The cellulose nanocrystals were extracted from millet husk residue waste using a homogenized acid hydrolysis method. The effects of the process variables homogenization speed (A), acid concentration (B), and acid to cellulose ratio (C) on the yield and swelling capacity were investigated and optimized using the Box Behnken design (BBD) method in response surface methodology. The numerical optimization analysis results showed that the maximum yield of CNCs and swelling capacity from cellulose was 93.12 % and 2.81 % obtained at homogenization speed, acid concentration, and acid to cellulose ratio of 7464.0 rpm, 63.40 wt %, and 18.83 wt %, respectively. ANOVA revealed that the most influential parameter in the model was homogenization speed for Yield and acid concentration for swelling capacity. The TGA revealed that cellulose had greater heat stability than CNCs. The functional groups of CNCs and cellulose were identical according to the FTIR data. When compared to cellulose, the SEM picture of CNCs is porous and shows narrow particle size with needle-like shape. The XRD pattern revealed an increase in CNC intensity. The second part of the research (CNCs modification for selective removal) A novel type of recyclable adsorbents with outstanding adsorption capability was produced using CNCs with succinic anhydride and EDTA. and their adsorption properties were studied in detail utilizing batch adsorption experiments of Chromium (VI) in aqueous solution. The effects of several factors on Cr (VI) adsorption were examined, including contact duration, adsorbent dose, starting concentration, pH, and temperature. The cellulose nanocrystals treated with succinic anhydride and EDTA possessed a needle-like form, high porosity, and a narrow particle size distribution. The carboxylate transition of the carboxyl group of cellulose was verified by FTIR. XRD analysis of particles after modification revealed the presence of additional phases, which were attributed to succinic anhydride and EDTA modification. A spontaneous exothermic adsorption process was validated by the observed thermodynamic characteristics. The best model for describing adsorption kinetics and mechanism was a pseudo-second order kinetic and intra-particle diffusion model. The Langmuir adsorption isotherm was seen in equilibrium adsorption data, with a maximum adsorption capacity (qmax) of 387.25± 0.88 mgL-1. We showed that the removal effectiveness of Cr (VI) maintained at 220± 0.78 mg.g-1 after 6 adsorption-desorption cycles, and that the CNC-ALG hydrogel beads are excellent adsorbents for the selective removal of Cr (VI) from wastewaters. The third part of the research (modeling of removal of heavy metal ions using RSM, ANN and quantum mechanism studies) The effects of contact time , pH, nanoparticle dose, and beginning Cd2+ concentration on Cd2+ removal were examined using the central composite design (CCD) technique. The performance and prediction capabilities of Response Surface Methodology (RSM) and Artificial Neural Network (ANN) modelling methodologies were explored, as well as their performance and prediction capacities of the response (adsorption capacity). The process was also described using the adsorption isotherm and kinetic models. Statistical data, on the other hand, revealed that the RSM-CCD model beat the ANN model technique. The optimum conditions were determined to be a pH of 5.73, a contact time of 310 minutes, an initial Cd2+ concentration of 323.04 mg/L, a sorbent dosage of 16.36 mg, and an adsorption capacity of 440.01 mg/g. The spontaneous adsorption process was well characterized by the Langmuir model, and chemisorption was the dominant regulator. The binding energy gaps HOMO-LUMO were used to find the preferred adsorption sites. The fourth part of research (optimization of removal using ANN and ANFIS) An artificial neural network and an adaptive neuro-fuzzy inference system were utilized to predict the adsorption capability of mix hydrogels in the removal of nickel (II) from aqueous solution. Four operational variables were evaluated in the ANFIS model to determine their influence on the adsorption study, including starting Ni (II) concentration (mg/L), pH, contact time (min), and adsorbent dosage (mg/L) as inputs and removal percentage (percent) as the single output. In contrast, 70% of the data was employed to develop the ANN model, while 15% of the data was used in testing and validation. To train the network, feedforward propagation with the Levenberg-Marquardt algorithm was used. To optimise, design, and develop prediction models for Ni (II) adsorption using blend hydrogels, (ANN) and (ANFIS) models were employed for trials. The results demonstrate that the ANN and ANFIS models are viable prediction techniques for metal ion adsorption. The fourth part of research (mechanistic modeling and optimization of removal using ANN, RSM and ANFIS) An artificial neural network, response surface methodology and an adaptive neuro-fuzzy inference system were utilized to predict the adsorption capability of modified cellulose nanocrystals and sodium alginate for the removal of Cr (VI) from aqueous solution. Four variables such as time, pH, concentration, and adsorbent dose were evaluated to determine their influence on the adsorption study. To examine the viability of the models, five statistical functions ( RMSE, ARE, SSE, MSE, and MPSD) were applied. absorption mechanism was described via four mechanistic models (Film diffusion, Weber and Morris, Bangham, and Dummwald-Wagner models. Further statistical indices supported ANFIS as the best prediction model for adsorption compared to ANN and RSM. Film diffusion was identified as the rate-limiting process via mechanistic modelling. The sixth part of research (continuous fixed-bed column study) The hydrogel's technical feasibility for adsorption of Cu2+, Ni2+, +Cd2+, and Zn2+ ions from the packed bed column's produced AMD was assessed. The hydrogel was considered to have a high potential for significant interactions with dangerous metal ions. This characteristic, together with the adsorbent's availability, low cost, and efficient regeneration of the spent adsorbent, distinguishes it from the many other adsorbents described in the literature by other researchers. With a bed height of 25 cm, an influent metal ion concentration of 10 mg/l, and a flow velocity of 10 ml/min, the bed performed better. As a consequence, the breakthrough curve for the packed bed experiment shows that the breakthrough points were approached sooner by increasing the flow rate and influent concentration, and later by increasing the bed height. The experimental results were satisfactorily described by the BDST, Yoon–Nelson, and Thomas models. The hydrogels had a net-work structure and more homogeneous porosity, according to the SEM, TGA, XRD, and FTIR results for CNCs. The hydrogels revealed varied degrees of opacity and heavy metal ions absorption capacity depending on the temperature of the analysis. Diffraction confirmed the existence of crystalline structures and the presence of carboxyl and amide groups.
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    Hybrid light photocatalysis of aromatic wastes in a fluidized bed reactor
    (Vaal University of Technology, 2022-08) Akach, John Willis Juma Pesa; Tshilenge, John Kabuba, Prof.; Aoyi, Ochieng, Prof.
    The use of solar photocatalysis for the treatment of aromatic chemicals like phenol in wastewater has attracted significant attention due to the low cost of sunlight. However, sunlight is unreliable since its intensity fluctuates during the day. This drawback can be addressed by supplementing sunlight with artificial UV lamps when the solar intensity reduces. In this work, such a hybrid solar/UV lamp reactor, internally illuminated by the UV lamp and externally by sunlight, was designed. Phenol was used as the model pollutant and the nanophase Aeroxide P25 TiO2 was employed as the photocatalyst and fluidized by compressed air. The catalyst and bubble distribution in the reactor was analysed using computational fluid dynamics (CFD) while the Monte Carlo (MC) method was used to model the light distribution and reaction kinetics. Finally, a lamp controller was designed to specify the required UV lamp output as a function of the solar intensity. The CFD simulation using ANSYS CFX 17 showed that a fairly homogeneous distribution of the catalyst was achieved in the reactor. Consequently, accurate simulations of the light distribution could be achieved without considering the hydrodynamics. The MC models revealed that bubbles did not significantly influence light absorption at the optimum catalyst loading. This showed that air was a good medium for fluidization as it could provide good mixing and oxygen electron acceptor without negatively affecting light absorption. The forward scattering behaviour of the P25 TiO2 and the increase in light attenuation with catalyst loading was confirmed in this work. The optimum catalyst loading in the different reactor configurations was 0.15 g/L (tubular solar), 0.2 g/L (annular solar), 0.4 g/L (annular UV lamp), and 0.4 g/L (hybrid light). This resulted in experimental reaction rates of 0.337 mgL-1min-1 (tubular solar), 0.584 mgL-1min-1 (annular UV lamp), and 0.93 mgL-1min-1 (hybrid light). An analysis of the local volumetric rate of energy absorption (LVREA) and reaction rate profiles along the radial coordinate showed a non-uniformity which worsened with an increase in catalyst loading. The reaction order with respect to the volumetric rate of energy absorption (VREA) indicated that solar illumination resulted in a higher electron-hole recombination as compared to UV illumination. This, combined with the higher intensity of the UV lamp, resulted in a higher reaction rate under UV light as compared to sunlight, demonstrating that the UV lamp could be used to supplement sunlight. For a typical sunny day, a lamp controller was designed that could adjust the UV lamp output as a function of the solar intensity to maintain the reaction rate at a reference level while ensuring less energy consumption than an ON/OFF lamp controller. This work demonstrated the feasibility of hybrid solar/UV lamp photocatalysis reactor which could maintain the advantages of solar photocatalysis while mitigating its drawbacks.
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    Electrocatalytic degradation of industrial wastewater using iron supported carbon-cloth electrode via Electro-Fenton oxidation process
    (Vaal University of Technology, 2022-02) Emeji, Ikenna Chibuzor; Ama, O. M., Dr.; Osifo, P. O., Prof.
    Human immunodeficiency virus (HIV) and acquired immune deficiency syndrome (AIDS) causes morbidity and mortality in infected patients. These epidemics are significantly reduced and treated globally with antiretroviral drugs (ARVDs). However, the eventual disposal of the ARVDs, either by excretion or otherwise, enables them to end up as emerging hazardous contaminants in our environment. Of all the available methods to remove ARVDs from our water bodies, electrochemical methods are reckoned to be one of the most effective. As a result, it is imperative to acknowledge the interactive behavior of these pharmaceuticals on the surface of the electrode. In this study, iron nano-particles were deposited on the carbon cloth electrode by electrodeposition using chronoamperometry techniques. The synthesized electrode was characterized using scanning electron microscopy (SEM), energy-dispersive x-ray spectroscopy (EDX), and x-ray photoelectron spectroscopy (XPS) microanalysis. The electrochemical characterization of the material was also carried out using cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS). The electrode's electrocatalytic activity toward the generation of hydrogen peroxide (H2O2) through a two-electron oxygen reduction reaction was assessed. Furtherance to this is the electrochemical degradation of nevirapine (NVP), lamivudine (LVD), and zidovudine (ZVD) in wastewater as a pharmaceutical model compound for organic pollutants in 50 mM K2SO4 electrolyte at a pH of 3. The SEM and EDX analysis showed the formation of iron nanoparticles within the matrix structure of the carbon cloth (CC) electrode. The XPS enlightened the presence of oxygen functional groups in the electrode's structure. EIS results are indicative that the modified electrode has a decreased charge transfer resistance (Rct)value as compared to the bare CC electrode. On the other hand, the CV result fosters good conductivity, enhanced current and large surface area of the modified electrode. More active and anchor sites were discovered on the iron-supported CC electrode which resulted in higher catalytic activity for the generation and accumulation of H2O2. The concentrations of “in-situ” generated H2O2 were found to be related to the current density supplied to the device after quantification. Although the accumulated H2O2 concentration appears to be low, it's possible that side reactions depleted the amount of H2O2 produced. As a result, the oxygen reduction reaction (ORR) through 2e- has a higher electrocatalytic activity with the improved iron assisted CC electrode than bare CC electrode. The electrochemical degradation studies conducted with the modified CC electrode by electro-Fenton process show a decrease in the initial ARVDs concentration (20 mg/L) as compared with the bare electrode. Their rate constants were 1.52 x 10-3 mol-1min-1 for ZVD, 1.20 x 10-3 mol-1min-1 for NVP and 1.18 x 10-3 mol-1min-1 for LVD. The obtained removal efficiencies indicate that the iron nanoparticle in the synthesised improves the degradation efficiency.
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    Biodiesel production and evaluation of heterogeneous catalyst using South African oil producing trees
    (Vaal University of Technology, 2014-01) Modiba, Edward Magoma; Osifo, Peter, Prof.; Rutto, Hillary, Dr.
    This study presents the use of sodium methoxide as a homogeneous catalyst and impregnated Perlite (potassium hydroxide/perlite) as heterogeneous catalyst for production of biodiesel using Baobab and Marula oil respectively. One factor at a time experimental design was used to study the effect of temperature, time, amount of catalyst and methanol to oil ratio on the transesterification of baobab oil using sodium methoxide as a catalyst. Response surface methodology was used to study the effect of temperature, time, amount of catalyst and methanol to oil ratio on the transesterification of marula oil using perlite as a catalyst. Biodiesel yield produced using sodium methoxide and baobab oil was 96% at 1 hr reaction time, 30 wt.% methanol to oil ratio, 1 gram of catalyst and 60°C reaction conditions. Biodiesel yield produced using perlite and marula oil was 91.38% at 3.55 hr reaction time, 29.86 wt.% methanol to oil ratio, 3.46 grams of catalyst and 70.41°C reaction conditions. Perlite catalyst was reusable for transesterification of marula oil while sodium methoxide was not reusable for transesterification of baobab oil. Baobab and Marula biodiesel fuel properties are comparable to American Society for Testing Materials standard (ASTM).
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    Synthesis of gelatin-cellulose hydrogel membrane for copper and cobalt removal from synthetic wastewater
    (Vaal University of Technology, 2021-04) Lukusa, Tresor Kabeya; Shoko, Lay, Dr.; Tshilenge, John Kabuba, Dr.
    Heavy metal ions are one of the most toxic materials in the environment. Adsorption is the most used process for the removal of heavy metals from wastewater. Much research has been conducted into processes to remove heavy metals using different adsorbents. Various adsorbents have been used to remove heavy metal ions from wastewater especially those that are harmful to mankind. Zeolite, clay, activated carbon and biopolymers are the most common adsorbents used. In this research, gelatin, and cellulose nanocrystals (CNCs) were used to synthesize a hydrogel membrane to remove Cu(II) and Co(II) metal ions from mining processes wastewater. The synthetic wastewater was prepared in the laboratory to conduct the experiments. Batch experiments were conducted to obtain the optimum conditions for the Cu(II) and Co(II) metal ions. The effect of parameters such as pH, ratio, contact time, and temperature were also determined. The optimum conditions obtained were 120 min contact time for both metal ions at the temperature of 30oC, pH 5 for copper and pH 7 for cobalt. The high removal of both metals ions was obtained using the ratio 3:1 (75% Gelatin and 25% CNCs) at the temperature of 303K. The maximum adsorption capacity of Cu(II) and Co(II) was 7.6923 mg/g and 10.988 mg/g, respectively. The high percentage removal of Cu(II) and Co(II) metal ions obtained was found to be 70.5% for Cu(II) at pH 5 and 74.5% for Co(II) at pH 7. The experimental data fit well to Pseudo-first-order kinetic and Freundlich isotherm models (KF= 1.89x103 mg/g for copper and 3.7x102 mg/g for cobalt) for both metal ions. The values of energy (E) from D-R model have shown that the adsorption of both metal ions was of physical nature (E<8kJ/mol) then confirmed by the thermodynamic results (ΔH°). The kinetic diffusion models have shown that the experimental data fit well with the film diffusion (R2= 0.977 and 0.989) for both metal ions at pH 5. Negative values of ΔG°obtained for both metal ions indicate that the adsorption process was spontaneous. The positive values of ΔH° obtained showed a physical adsorption process and also indicate that the adsorption process of both metal ions was endothermic. The positive values of ΔS° indicate an increase in randomness at the solid/solution interface during adsorption.
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    Development of sulfonated chitosan membranes modified with inorganic nanofillers and organic materials for fuel cell applications
    (Vaal University of Technology, 2021-07-06) Zungu, Nondumiso Petunia; Ofomaja, A., Prof.; Osifo, P. O., Prof.
    Fuel cell technology is a promising clean energy source compared to internal combustion engines and electricity generating plants which are associated with high emissions of greenhouse gases. The aim of this study was to modify chitosan into polymer electrolyte membranes suitable for use in PEMFC and DMFC fuel cells. Chitosan modification was done with 2-aminoethanesulfonic acid (2-AESA), dimethylformamide (DMF) and silica nanoparticles. The effect of the modification on the properties of the developed chitosan membranes was studied using FTIR, XRD, SEM-EDS and TGA. The performance of the membrane electrode assemblies was investigated. The formation of electrostatic interactions in the developed sulfonated chitosan membranes was confirmed via the Fourier transform infrared (FTIR) analysis, indicating a shift in the wavenumber of the N-H bonds from 1581 cm-1 on the chitosan spectrum to a lower wavenumber of 1532 cm-1 in the FTIR spectra of the membranes and by the new peak at the wavenumber of ~1260 cm-1 attributed to the asymmetric O=S=O stretching vibrations of the sulphate groups and sulfonic acid groups from the cross-linking sulphuric acid solution and 2-aminoethanesulfonic acid incorporated on the chitosan polymer chain during the modification. Notably, the FTIR spectra of the developed sulfonated chitosan membranes lacked the peak at the wavenumber of ~1153 cm-1 attributed to the stretching of C-O-C bonds of the polysaccharide ring of chitosan. A reaction mechanism was proposed in this study illustrating the possible conversion of the polysaccharide rings of chitosan into a poly (cyclohexene-oxide) thermoplastic rings in the developed membranes. The TGA/DTGA results of the developed sulfonated chitosan membranes showed three degradation stages. The initial weight loss occurred at temperatures ˂100 °C due to the evaporation of volatile components and water molecules inside the membranes. The second degradation phase of the membranes occurred at 208 ℃ with a loss in weight of >30% resulting from the decomposition of cross-linking networks. The third degradation stage was associated with the decomposition of the main polymer backbone of the membranes and occurred at 263°C for the chitosan membranes modified with 2-aminoethanesulfonic acid and at 266 °C for the chitosan membrane modified with silica nanofiller. The TGA/DTGA curves of Nafion 117 showed a small loss in weight of ~ 5% before a sharp decomposition that occurred between 346–505 °C. The XRD diffractograms of the developed sulfonated chitosan membranes showed amorphous phases, the crystal peaks of chitosan at 2theta of 10° and 20° were flattened on the membranes. The SEM images showed a homogenous surface morphology for the sulfonated chitosan membrane with a higher weight percentage of 2-aminoethanesulfonic acid (13,6 wt.%). The SEM images performed on the surface of the sulfonated chitosan membrane modified silica nanoparticles showed a slight agglomeration associated with the migration of the unbonded silica to the surface. The methanol permeability coefficient of the developed sulfonated chitosan membrane modified with 2-aminoethanesulfonic acid was calculated to be 2.29x10-6 cm2/s. This value was close to the methanol permeability coefficient of 2.33x10-6 cm2/s associated with unfavourable depolarisation at the cathode in direct methanol fuel cells when using Nafion 117. The proton diffusion coefficient of Nafion 117 was calculated to be 1.64x10-5 cm2/s and that of the developed sulfonated chitosan membrane modified with 2-aminoethanesulfonic acid was found to be 6.56x10-6 cm2/s, respectively. The fuel cell performance of the developed sulfonated chitosan membrane modified with 2AESA was investigated in a hydrogen fuel cell (PEMFC) supplied with H2 and O2 directly from the electrolyser. The sulfonated chitosan membrane modified with 2-aminoethanesulfonic acid (13.6 wt.%) achieved an open-circuit voltage of ~0.9 V and a maximum power output of 64.7 mW/cm2 at a maximum current of 70 mA. The current produced by the developed chitosan membrane was applied into the load and was able to turn (power) the electric fan. The sulfonated chitosan membrane modified with silica nanoparticles (2 wt.%) yielded an open-circuit voltage of ~0.9 V and attained a maximum power output of 58 mW/cm2 at a maximum current output of 60 mA/cm2. The current generated by the membrane was also able to turn the electric fan. The Nafion 117 membrane was also investigated under similar conditions and obtained an open-circuit voltage of 0.6 V and a maximum power output of 130 mW/cm2 at the maximum current output of 308 mA. The current produced by Nafion 117 was supplied into the load and was able to turn the electric fan.
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    Modelling of in-situ real-time monitoring of catalysed biodiesel production from sunflower oil using fourier transform infrared
    (Vaal University of Technology, 2020-10) Mwenge, Pascal Kilunji; Rutto, H. L., Prof.; Seodigeng, T. G., Dr.
    The industrialisation of the twenty-first century and the worldwide population growth led to the high demand for energy. Fossil fuels are the leading contributor to the global energy, and subsequently, there is a high demand of fuels. The decrease of global fossil fuels and the environmental air pollution caused by these fuels are concerning. Therefore, eco-friendly and renewable fuel such as biodiesel is one the leading alternative. Chromatography and Spectroscopy are the most used analytical methods and proven reliable but are time-consuming, requires qualified personal, extensive samples preparation, costly and do not provide in-situ real-time monitoring. Fourier Transform Infrared (FTIR) has mainly been used for qualitative analysis of biodiesel, but not much work has been reported in real-time monitoring. This study focused on the modelling of in-situ real-time monitoring of the biodiesel production from sunflower oil using FTIR (Fourier Transform Infrared). The first part of the study investigated the effect of catalyst ratio and methanol to oil ratio on biodiesel production by using central composite design (CCD). Biodiesel was produced by transesterification using Sodium Hydroxide as a homogeneous catalyst. A laboratory-scale reactor consisting of; flat bottom flask mounted with a reflux condenser, a hot plate as heating element equipped with temperature, timer and stirring rate regulator was used. Key parameters including, time, temperature and mixing rate, were kept constant at 60 minutes, 60 oC and 600 RPM, respectively. From the results obtained, it was observed that the biodiesel yield depends on catalyst ratio and methanol to oil ratio. The highest yield of 50.65 % was obtained at a catalyst ratio of 0.5 wt% and methanol to oil mole ratio 10.5. The analysis of variances of biodiesel yield showed the R2 value of 0.8387. A quadratic mathematical model was developed to predict the biodiesel yield in the specified parameters range. The same set-up was used to produce waste margarine biodiesel using a homogeneous catalyst, potassium hydroxide (KOH). The effects of four reaction parameters were studied, these were: methanol to oil ratio (3:1 to 15:1), catalyst ratio (0.3 to 1.5 wt. %), temperature (30 to 70 oC), time (20 to 80 minutes). The highest yield of 91.13 % was obtained at 60°C reaction temperature, 9:1 methanol to oil molar ratio, 0.9 wt. % catalyst ratio and 60 minutes. The important biodiesel fuel properties were found to be within specifications of the American Standard Test Method specifications (ASTM). It was concluded that waste margarine can be used to produce biodiesel as a low-cost feedstock. The core of the study was performed using EasyMax Mettler Toledo reactor equipped with a DiComp (Diamond) probe. The quantitative monitoring of the biodiesel production was performed by building a quantitative model with multivariate calibration using iC Quant module from iC IR 7.0 software. Fourteen samples of known concentrations were used for the modelling which were taken in duplicate for model calibration and cross-validation, data were pre-processed using mean centring and variance scale, spectrum math square root and solvent subtraction. These pre-processing methods improved the performance indexes from 7.98 to 0.0096, 11.2 to 3.41, 6.32 to 2.72, 0.9416 to 0.9999, RMSEC, RMSECV, RMSEP and R2Cum, respectively. The R2 values of 1 (training), 0.9918 (test), 0.9946 (cross-validation) indicated the fitness of the model built. The model was tested against the univariate model; small discrepancies were observed at low concentration due to unmodelled intermediates but were quite close at concentrations above 18%. The software eliminated the complexity of the Partial Least Square (PLS) chemometrics. It was concluded that the model obtained could be used to monitor transesterification of sunflower oil at industrial and lab scale. The model thus obtained, a batch reactor setup, EasyMax Mettler Toledodo reactor was used, the experiments were designed and monitored using iControl software. The results were recorded and quantified using iC IR software based on the biodiesel calibrated monitoring model built. The optimisation of the biodiesel was performed using three key parameters (methanol to oil ratio, catalyst ratio and temperature) while keeping time at 60 minutes and mixing rate at 150RPM. The highest yield of 97.85 % was obtained at 60 oC, 0.85 wt % catalyst ratio and 10.5 methanol to oil mole ratio. The analysis of variances of biodiesel production showed the values of 0.9847, 0.9674 and 0.8749, for R-squared, adjusted R-squared and predicted R-squared, respectively. A quadratic mathematical model was developed to predict the biodiesel conversion in the specified parameters ranges. Using the Arrhenius equation, activation energy (Ea) and frequency factor were found to be 41.279 kJ.mole-1 and 1.08 x10-4 M-1. s-1, respectively. The proposed kinetics model was a pseudo-first-order reaction. It was concluded that the model obtained can be used for industrial and laboratory-scale biodiesel production monitoring.