School of Chemistry (ETDs)
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Item Synthesis and electrochemical properties of high-entropy spinel oxides, cobalt atomic clusters and zinc oxide as electrode materials for rechargeable zinc-air batteries(University of the Witwatersrand, Johannesburg, 2024-07) Gaolatlhe, Lesego; Ozoemena, Kenneth IkechukwuThis thesis investigated cathode and anode electrode materials for application in rechargeable zinc-air battery (RZAB). Two types of cathode materials were strategically studied in RZAB applications: (a) cobalt carbon composites of (i) cobalt atomic clusters (Co AC@CBPDC) and (ii) cobalt nanoparticles (Co NP@CBPDC), and (b) high-entropy spinel oxide (HESOx, containing five transition metals – Cu, Mn, Fe, Ni, and Co). The activities of these materials toward oxygen reduction reaction (ORR and oxygen evolution reaction (OER) were investigated in both half- and full-cell configurations as a proof-of-concept in RZAB cells in alkaline electrolyte. Considering that conventional zinc plate has several short-comings as an anode for RZAB, a new material, polydopamine-derived carbon-coated zinc oxide (ZnO@PDA-DC), was also synthesised and applied in RZAB as a possible alternative anode to the popular zinc plate. First, Co AC@CBPDC and Co NP@CBPDC were prepared using the metal-organic framework (MOF) route through the microwave-assisted solvothermal method and acid treatment. From the XRD results, the spectra showed dominant {111} and {200} phases, characteristic of metallic cobalt with a face-centred cubic (fcc). There were trace amounts of CoO observed indicating the coexistence of Co/CoO. From TEM imaging, Co AC@CBPDC was highly defective with a visible porous carbon structure than its counterpart (Co NP@CBPDC) and showed dispersed atomic clusters. BET data showed that Co AC@CBPDC had a higher surface area (144.8 m2/g) than the Co NP@CBPDC (33.25 m2/g). The improved physicochemical merits of the Co AC@CBPDC allowed for better ORR and OER activities than the Co NP@CBPDC in terms of low halfway potential (E1/2), onset potential (Eonset), overpotential at 10 mA/cm2 (ƞ10), potential gap (∆E) between the overpotential of OER and the halfway potential, and a higher kinetic current density (jk). The enhanced electrochemistry of the Co AC@CBPDC was attributed to the defects created by the acid treatment. As proof of real-life applicability, the Co AC@CBPDC electrocatalyst delivered an excellent air cathode in a parallel plate RZAB cell with notable OCV (1.23 V), peak power density (49.9 mW/cm2), a real energy density (477 mAh/cm2), long-term stability for 210 h, enhanced voltage retention, Coulombic efficiency (ca. 100 %) and DOD (51.3%), comparable to literature. In addition, an all-solid-state RZAB based on the Co AC@CBPDC catalyst gave a higher and constant OCV (1.73 V) at varied bending angles (0 – 180 degrees) and excellent stability. Second, new HESOx materials were prepared via the Pechini method at two different annealing temperatures of 500 and 750 oC (abbreviated herein as HESOx-500 and HESOx-750). P-XRD results showed that these are inverse spinel oxides, with {311} as the dominant phase. HR-TEM images proved that they are single nanocrystalline materials. XRD and BET data showed that the HESOx-500 is smaller in size, more porous, and has a higher surface area than its counterpart (HESOx-750). HESOx-500 showed superior ORR performance with an onset potential of 0.93 V and a E1/2 of 0.88 mV. The OER performance also showed improved ƞ10 compared to IrO2 with an overpotential of 340 mV at a current density of 10 mA/cm2, and a 45 ± 5.0 mV/dec Tafel slope, above the performance of IrO2 (66 ± 6.1 V/dec). The ∆E of HESOx-500 was 0.69 V. The material was further tested as a cathode material in a RZAB cell. The optimised RZAB cell showed remarkable performance with a theoretical potential of 1.67 V and long-term stability of 375 h at 10 mA/cm2. The performance was attributed to the high-entropy compositional design with a high number of surface oxygen vacancies and different metal oxidation states. Finally, having dealt with the issue of bifunctionality in RZAB, a new ZnO@C anode material was also considered. The ZnO@PDA-DC (where PDA-DC means polydopamine-derived carbon) was used due to its ability to form Zn2+ pathways. Electrochemical potentiodynamic polarisation tests were performed to understand and compare the corrosion inhibition effects in an alkaline medium (6 M KOH). The ZnO@PDA-DC showed better corrosion inhibition properties than the zinc plate and other samples: low corrosion current (icorr = 0.107 uA/cm2) and corrosion potential (Ecorr = 1.077 V), and a mixed inhibition effect, indicating reduced hydrogen evolution reaction and zinc dissolution. Due to the excellent corrosion inhibition properties of the ZnO@PDA-DC, it was then evaluated in the RZAB cell. The shallow galvanostatic charge-discharge cycle stability at 2 mA/cm2 was able to maintain 150 h in a RZAB at a voltage gap of 0.76 V to 0.80 V. The results demonstrated that enhanced rechargeability is possible with ZnO@PDA-DC for RZAB.Item Synthesis of platinum-based electrocatalysts using nitrogen doped onion-like carbon and WS2 composites as the support for electrooxidation of ethanol in direct alcohol fuel cells(University of the Witwatersrand, Johannesburg, 2024-10) Bila, Laercia Rose; Gqoba, Siziwe; Maubane-Nkadimeng, Manoko S.The study reports on the synthesis of onion-like carbons (OLCs)/tungsten disulfide (WS2) composites as catalyst support for direct alcohol fuel cells (DAFC). OLCs were synthesized using waste engine oil over a flame pyrolysis (FP) method. The pristine OLCs (p-OLCs) were functionalized and purified using nitric acid (HNO3). The functionalized OLCs (F-OLCs) were further doped with nitrogen using melamine to increase the electronic properties of the OLCs. WS2 was synthesized using the colloidal method and oleylamine was used as the capping agent. Pt/p-OLCs, Pt/F-OLCs, and Pt/N-OLCs were synthesized using a reflux method where ethylene glycol was the reducing agent. Finally, WS2/N-OLCs were synthesized using the colloidal method and then Pt was dispersed on WS2/N-OLCs to form Pt/WS2/N-OLCs. High-resolution transmission electron microscopy showed the presence of onion-like rings in the OLCs and the quasi-spherical morphology, while a flower-like morphology was observed for WS2. Powder X-ray diffraction revealed that the synthesized WS2 had traces of WO3 due to the oxidation of WS2 which introduces WO3 impurities. Energy Dispersive X-ray Spectroscopy revealed that the OLCs derived from waste engine oil present some impurities that were attributed to the motor wear as well as the fuel. When Pt was loaded onto the WS2/N OLCs composite, the WS2 lost its original nanoflower morphology, which was attributed to the presence ethylene glycol used as a reducing agent. X-ray photon spectroscopy confirmed the successful synthesis of the Pt electrocatalysts. Cyclic voltammetry was used to determine the oxidation of ethanol and the current density of the synthesized electrocatalysts. Interestingly, the Pt/p-OLCs electrocatalyst had a higher current density compared to Pt/F-OLCs and Pt/N-OLCs. This was attributed to metal impurities found in p-OLCs, which were reduced during the purification process. The Pt/WS2/N-OLCs electrocatalyst showed higher current density compared to Pt/WS2 but this was low compared to Pt/N-OLCs. The data reveals that the addition WS2 shows a co-catalyst behaviour, rather than a support.Item Preparation of nitrogen-doped multiwalled carbon nanotubes anchored 2D platinum dichalcogenides for application as hydrogen evolution reaction catalysts(University of the Witwatersrand, Johannesburg, 2024-09) Mxakaza, Lineo Florence; Moloto, Nosipho; Tetana, ZikhonaThe alkaline hydrogen evolution reaction (HER) (H2O + 2e − → H2 + 2OH−) is fast gaining traction as a sustainable hydrogen gas generation route but suffers from slow reaction kinetics because of the additional water dissociation step and large reaction overpotential. As such, the current state-of-the-art acidic medium Pt and Ru catalysts suffer from considerable loss of catalytic activity in an alkaline medium. We propose the development and use of platinum metal dichalcogenides for alkaline HER. Platinum dichalcogenides are 2D materials that offer the advantage of more exposed catalytic sites, show dramatic chalcogen-dependent electronic properties, and have a band gap (0.24 eV - 1.8 eV for PtS2 and PtSe2) thus extending the use of these materials to light-stimulated photo-electrochemical (PEC) HER. As such, PtS2 is reported to be a semiconductor, PtSe2 is semi-conductive/semi-metallic depending on the number of layers, and PtTe2 is metallic. The Pt-chalcogen covalent bond intensifies down the chalcogen group. Additionally, the interlayer interactions in Pt dichalcogenides are covalent, and just like the Pt-chalcogen bond, intensify as the chalcogen atom changes from sulphur to selenium to tellurium. This behaviour of Pt dichalcogenides results from the Pt bonding d orbitals and the chalcogen bonding p orbitals that are relatively close in energy than in other TMDs, and the difference in the energy becomes smaller and smaller down the chalcogen group. Herein, we report on the synthesis of PtSe2 and PtTe2 using the colloidal synthesis method for the first time and then applying them as electrocatalysts in alkaline HER. As mentioned, developing 2D materials results in band gap development, particularly in PtS2 and PtSe2. Following this, PtSe2 was explored as a photocathode in light-induced photo-electrochemical HER. Generally, semiconductors are poor electron transporters and one of the major requirements for an efficient PEC cathode is solar absorption, charge generation, and efficient charge separation. The charge separation properties of PtSe2 were improved by supporting this material on highly conductive, mechanically, and thermally stable nitrogen-doped multi-walled carbon nanotubes (N-MWCNTs). In Chapter 3, we report on the effect of varying selenium precursors from elemental selenium, sodium selenite to selenourea on the colloidal synthesis of PtSe2 in a mixture of oleylamine and oleic acid at 320 ℃. All the reactions resulted in the formation of PtSe2 although PtSe2 prepared from selenourea is amorphous, evidenced by relatively broader XRD peaks and a smaller crystallite size. HER activity of the three PtSe2 catalysts was evaluated in 1 M KOH at a scan rate of 5 mV/s and PtSe2 prepared from selenium exhibited the earliest onset potential of 46 mV, overpotential of 162 mV, and a smaller Tafel slope of 112 mVdec-1. This material exhibits the smallest resistance to electron transport and a high electrochemical surface area. We then explored the effect of altering tellurium precursor from elemental tellurium to tellurium tetrachloride, and sodium tellurite. Unlike the PtSe2 synthesis, different platinum tellurite phases, PtTe2, PtTe, and the mixed phase PtTe: PtTe2 were produced from Te, PtCl4, and sodium tellurite, respectively. Of the three, PtTe2 exhibited the highest alkaline HER activity with an onset potential of 29 mV, an overpotential of 107 mV, and a Tafel slope of 79 mVdec-1. In the same chapter, we compared the catalytic activity of PtSe2 (prepared from Se) and PtTe2 (prepared from Te) catalysts. We determined that PtTe2 has a high surface roughness and electrochemical surface, leading to relatively higher activity than PtSe2. However, PtTe2 is metallic and therefore does not have a band gap, which implies that it cannot be employed in light-stimulated catalysis reactions. In Chapter 4, we explored the use of PtSe2 as a light-stimulated PEC alkaline HER catalyst. We used in situ colloidal synthesis to grow PtSe2 on the walls of N-MWCNTs to improve the overall electron transport properties of PtSe2. PtSe2 anchored on N-MWCNTs was also studied in the dark and under illumination using 1 sun (100 mW/cm2) to determine the influence of light on the HER catalytic activity of the hybrid materials. This study demonstrates that the light-stimulated HER activity of PtSe2 improves when minimal amounts of N-MWCNTs are incorporated in the PtSe2 sample matrix. This then leads to employing these materials as photocathodes in PEC HER.Item Microwave-assisted synthesis of palladium-based ferroalloy electrocatalysts for application in alkaline direct alcohol fuel cells(University of the Witwatersrand, Johannesburg, 2024-11) Ramashala, Kanyane Nonhlanhla Eugenia; Billing, Caren; Modibedi, R. Mmalewane; Ozoemena, Kenneth IkechukwuThis research work describes the study of Pd-based ferro-electrocatalysts for application towards direct ethanol fuel cells (DEFCs), direct ethylene glycol fuel cells (DEGFCs), direct glycerol fuel cells (DGFCs) and oxygen reduction reaction (ORR) operated in a basic environment. The initial part of the research was to explore the Pd-based monometallic and bimetallic (Pd/C and PdFe/C) by utilising varied methods such as the conventional sodium borohydride (NaBH4) and microwave-assisted technique (MW) towards the oxidation of glycerol (gly), intending to choose the best method viable for these catalysts. This study revealed that MW techniques tuned the physicochemical properties of Pd/C and PdFe/C by augmenting their crystallinity and defect. These led to improved electrocatalytic activities towards glycerol oxidation reaction (GOR) over NaBH4 technique. MW process as a powerful tool was further used in the entire study to synthesise bimetallic and trimetallic electrocatalysts in ethanol (EtOH), ethylene glycol (EG) and glycerol (Gly) oxidation reaction in an alkaline environment. The synthesised bimetallic catalysts studied in this research work were (PdFe/C, PdCo/C, and PdMn/C) at varied ratios of Pd: M (Pd2M/C (2:1) and PdM/C (1:1)). Amongst them all, Pd2Fe/C and PdFe/C were observed to be the most favourable catalysts towards all the alcohols, with the excellent specific activity of about, for EtOH (11.59 and 4.15 mA cm-2), EG (9.82 and 5.51 mA cm-2) and Gly (8.94 and 4.73 mA cm-2), respectively. The satisfactory performance exhibited by the PdFe/C electrocatalyst prompted the exploration of the second 3d transition metal (PdFeMn/C and PdFeCo/C), intending to investigate the synergistic behaviour between the non-noble metals and Pd. The XRD confirmed that these electrocatalysts are in a crystalline nature with a decrease in d spacing (from 0.2247 nm, PdFe/C to 0.2236 nm (PdFeMn/C)) after the insertion of Mn into PdFe/C. This was supported by the TEM images obtained for the PdFeMn/C catalyst with a particle size of sub 10 nm. The comparison studies towards EtOH, EG and Gly were investigated for all the electrocatalysts and there was a remarkable observation, which is dissimilar from the theoretical studies (DFT). Density Functional Theory (DFT) revealed that PdFeCo performed better in terms of Gibbs free energy, binding energy, and energy band gap than PdFeMn; however, the experimental studies favoring the performance of PdFeMn. The PdFeMn/C delivered the best electrochemical activities, including a superior electrochemical active surface area (ECSA), larger current densities and mass activity response, and less susceptibility to poisoning and high conductivity as compared to PdFe/C and PdFeCo/C electrocatalysts. Furthermore, the PdFeMn/C electrocatalyst exhibited remarkable electrochemical properties during the ORR (basic medium). Ultimately, the best two anode electrocatalysts (PdFe/C & PdFeMn/C) were explored and tested for the proof-of-concept in the two-electrode configuration with the micro-3D printed cell. The PdFeMn/C delivered improved µ-ethylene glycol fuel cell, µ-glycerol fuel cell, and µ-ethanol fuel cell activities with respective to high voltage and power density of 33.27 mW cm-2, 11.00 mW cm-2 and 45,80 mW cm-2 respectively, operated at 100 mV / s. These electrocatalysts have demonstrated promising results in advancing ADAFCs.Item Towards the development and determination of trace impurities in battery grade nickel sulphate(University of the Witwatersrand, Johannesburg, 2024-10) Mabowa, Mothepane Happy; Tshilongo, James; Chimuka, LukeThis study introduces innovative research focused on developing and optimizing advanced extraction techniques for refining nickel hydroxide from secondary material solutions. This precursor to nickel sulfate is effectively purified through impurity removal and precise determination, enhancing the final product to battery grade standards. The research addresses the extraction of metal hydroxide from secondary sources such as spent batteries and industrial waste, promoting recycling and reducing environmental impact. By refining analytical methodologies and improving impurity control, this study advances the sustainable production of high quality nickel sulfate essential for advanced rechargeable batteries. The key challenge addressed in this study is the presence of impurities in secondary material solutions, which complicates the process of refining nickel hydroxide and hinders the production of high-purity nickel sulfate suitable for battery applications. Existing methods for recovering nickel from secondary materials are often inefficient, leading to high impurity levels, low recovery rates, and significant environmental impacts. Current methods such as solvent extraction and precipitation often fail to achieve the desired purity levels for nickel sulfate, necessary for use in high-performance battery manufacturing. Furthermore, these methods can be costly, resource-intensive, and environmentally damaging. Analytical methods used to measure impurities also have limitations. The complex and saturated matrix of battery-grade solutions challenges accurate impurity determination, often necessitating indirect methods such as difference analysis from nickel sulfate, which may not fully capture all impurity types or their concentrations. To resolve these issues the study focuses on optimizing advanced extraction techniques from these secondary sources. The research includes: (1) investigating the effectiveness of S-Curve precipitation by varying parameters such as pH levels, nickel concentration, precipitate dosage, temperature, impurity concentration, and solubility products; (2) evaluating solvent extraction for copper removal prior to nickel precipitation; (3) validating various analytical techniques (FAAS, EDXRF, ICP-OES) for trace element analysis; (4) examining lime precipitation for the removal of iron, manganese, and copper; and (5) characterizing β-nickel hydroxide (Ni(OH)₂) using scanning electron microscopy (SEM), X-ray diffraction (XRD) patterns, Fourier-transform infrared spectroscopy (FTIR), and X-ray photoelectron spectroscopy (XPS). The research employed a combination of precipitation methods, solvent extraction, and advanced analytical techniques. The S-curve precipitation of nickel hydroxide was optimised by varying pH levels, nickel concentration, and temperature. The study also examined lime precipitation as a method for impurity removal and used solvent extraction for copper removal before nickel recovery. Various solvents with different ratios were utilized at room temperature for copper extraction, and the 1:5 ratio of 5,8-diethyl-7-hydroxydodecan-6-oxime (LIX 63-70) proved to be effective. Analytical tools like FAAS, EDXRF, and ICP-OES were employed to validate the concentration of trace impurities, and techniques such as SEM, FTIR, XRD, and XPS were used to characterize the crystalline structure and purity of β-Ni(OH)₂. The first part of the work entailed devising a technique to extract base metals, specifically nickel, from the waste stream resulting from the nickel sulphide-fire assay waste. This study explores the recovery of nickel (Ni) through a combination of solvent extraction and precipitation techniques. The main objective is to develop an efficient process for separating Ni from copper (Cu) and iron (Fe) impurities, thereby optimising metal recovery at varying pH, concentration with addition of calcium hydroxide at 60˚C and contributing to the circular economy. The approach involves using LIX 63-70 for solvent extraction, which effectively loads Cu into the organic phase and allows for Ni liberation into the aqueous phase. Characterization of the S-curve precipitation process was carried out using various analytical techniques. The precipitation of Ni(OH)₂ was optimised at pH 6.5, as evidenced by X-ray diffraction (XRD) patterns, Fourier-transform infrared spectroscopy (FTIR), and X-ray photoelectron spectroscopy (XPS). The results show that Ni(OH)₂ precipitates in a crystalline β-phase, with XPS confirming the successful precipitation and minimal presence of Cu and Fe impurities at pH of 6.5 at 60˚C. Notably, the study also identifies the presence of Fe and Ca impurities at pH 2.5, as indicated by scanning electron microscopy (SEM), energy-dispersive X ray spectroscopy (EDX), and XRD analyses. The study addresses a critical research gap by providing a detailed assessment of the separation process for Ni from complex waste streams. It demonstrates the efficacy of 5,8-diethyl-7-hydroxydodecan-6-oxime (LIX 63-70) in selectively extracting Cu and reveals the influence of pH on the purity of Ni(OH)₂ precipitates. The process also involves significant lime consumption for neutralising the feed solution, with about 71% used to adjust the solution to pH 2.0, highlighting the importance of optimising reagent usage. The research presents a successful method for recovering Ni from fire assay waste in separating value-added metals from impurities. The findings contribute to advancements in metal recycling and repurposing, supporting the development of sustainable waste management practices and the promotion of a circular economy. Paper II evaluates the accuracy and reliability of elemental analysis in synthetic cathode liquor using Energy Dispersive X-ray Fluorescence (EDXRF) and Flame Atomic Absorption Spectroscopy (FAAS) with both factory default settings and after internal calibration and compares these results with those obtained from Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES). The research aims to test the performance of EDXRF and FAAS for identifying and quantifying elements such as calcium (Ca), sodium (Na), cobalt (Co), iron (Fe), nickel (Ni), copper (Cu), arsenic (As), selenium (Se), antimony (Sb), and bismuth (Bi). The investigations into the impact of these parameters on the variations in absorbance for the targeted impurities guarantee satisfactory linearity and recovery. The recovery was quantified by comparing the concentration of elements in spiking samples and certified reference materials (CRMs) to known quantities, while the sensitivity of each method was assessed by the limits of detection (LOD). Linearity was assessed by constructing calibration curves at a variety of concentrations and calculating the coefficient of determination (R²) to guarantee precise results at varying concentration levels. Initial EDXRF results using default settings showed substantial inconsistencies, particularly with Ca, where measured values invariably showed 0 mg/L despite actual concentrations ranging from 0 to 0.15 mg/L, and Ni, where measured concentrations varied between 493,327 and 529,280 mg/L compared to the true value of 120,000 mg/L. After calibration, EDXRF displayed better accuracy for Co, Fe, and Cu but experienced limits with light elements like Se and Sb due to high LOD. FAAS demonstrated effective results for Co, Cu, Fe, and Mg but encountered limits, particularly in detecting low amounts of metals like Na. FAAS readings for Na demonstrated high variability with a standard deviation (SD) of 505.24 mg/L and a relative standard deviation (RSD) of 23.39%. Furthermore, differences in FAAS measurements for Ca, Fe, and Ni were seen, with fluctuations in standard deviation (SD) and relative standard deviation (RSD) suggesting a certain level of inconsistency. The ICP-OES results confirms the accuracy of FAAS by closely aligning with its measurements for elements such as Co and Ni. The precision of FAAS is further demonstrated by the low standard deviations (8.08 mg/L for Co and 4 mg/L for Ni) of ICP-OES results (e.g., Co: 990 mg/L, Ni: 126 mg/L). This validation underscores the dependability of FAAS to these components due to selection of FAAS for its cost-effectiveness and broad applicability in industrial analysis. Evaluation of numerous methods is crucial for a thorough evaluation of elemental analysis accuracy, as evidenced by the comparison with ICP-OES. In addition, it is crucial to distinguish between the discourse on analytical methods and recovery metrics, as recovery rates are more closely associated with preconcentration techniques than with the analytical methods themselves. This work aims to fill a significant research need by emphasising the need for internal calibration for EDXRF and the necessity of using several analytical methods in conjunction to obtain dependable results. It stresses the strengths and limits of each method, providing a complete approach to enhancing analytical accuracy in industrial applications. The study in Paper III investigates the characterisation and retrieval of β-Ni(OH)₂ from fire assay waste using chemical precipitation. Various analytical methods are used to confirm the successful synthesis and purity of the molecule. Nickel hydroxide (Ni(OH)₂) is a functionally diverse chemical with a broad spectrum of uses. A hexagonal crystalline structure of β-Ni(OH)₂ is confirmed by X-ray diffraction (XRD) analysis, therefore validating the successful precipitation procedure. Fourier-transform infrared spectroscopy (FTIR) spectra provide additional evidence for the presence of nickel hydroxide by displaying distinct peaks associated with υ(OH) and υ(NiO) bonds. The X-ray photoelectron spectroscopy (XPS) analysis reveals the significant Ni²⁺ oxidation peak, which confirms the successful precipitation at a pH of 6.5. Additionally, XPS analysis detects the presence of contaminants such as chlorine and calcium in the waste matrix. Scanning electron microscopy (SEM) shows layered granules with a predominantly transparent brucite analogue crystalline phase, typical of β-Ni(OH)₂. It also exposes rough textures and uneven aggregation, indicating increased oxide concentrations on the Ni surface. The presence of nickel (Ni) and oxygen (O), as well as calcium (Ca) impurities arising from the chemical precipitation process, is confirmed by energy-dispersive X-ray spectroscopy (EDX). An investigation of particle size distribution indicates an average particle size of 2.0 µm. The results of Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES) indicate a reduction in Ni concentrations, with recorded values of 62.7 g/L in the pregnant leach solution, 0.8 g/L in the precursor solution, and 0.501 g/L in the solid precipitate (cake). The copper loading efficiency is measured to be 79%, accompanied by a nickel loss of 9.73% and a nickel recovery rate of around 90.27%. This effective separation process demonstrates a cost-efficient and environmentally responsible method for recycling nickel from acidic chloride media, underlining the broader potential for nickel reuse in industrial processes. This study conducts a comparative analysis of nickel oxide (NiO) that is derived from fire assay nickel sulphide (FA-NiS) and produced through chemical precipitation and sol-gel methods. The focus is on the structural, morphological, and sensing properties of the NiO. This research is significant in that it is the first to report on the application of NiO synthesised from waste materials for volatile organic compound (VOC) sensing. The primary goal is to clarify the distinctions in properties between NiO obtained through these methods and evaluate their suitability for environmental sensing applications. Nickel was initially extracted from the raffinate using 5,8-diethyl-7-hydroxydodecan-6-oxime. Subsequently, nickel hydroxide (Ni(OH)₂) was precipitated with lime (Ca(OH)₂) at pH levels of 2.5 and 6.5. The hydroxide was subsequently transformed into NiO through a thermal treatment process. The presence of nickel and oxygen at pH 6.5, as well as iron, nickel, and oxygen at pH 2.5, was verified through the use of scanning electron microscopy (SEM)-energy dispersive spectroscopy (EDS) and X-ray photoelectron spectroscopy (XPS). In both the sol-gel and chemical precipitation procedures, the X-ray diffraction (XRD) analysis demonstrated a cubic crystal structure with high average crystal sizes of 39-41 nm. The sol-gel process resulted in homogenous spherical particles, as evidenced by SEM imaging, whereas chemical precipitation resulted in aggregated layered grains. It is important to note that NiO precipitated at pH 2.5 exhibited coalesced hexagonal particles with a substantial amount of nickel and iron. The transition from nickel hydroxide to nickel oxide is essential because NiO is highly effective for VOC sensing due to its semiconductor properties. The study highlights the importance of utilising NiO in the detection of volatile organic compounds (VOCs) and the impact of each synthesis method on the material's sensory capabilities. Using certified reference materials, analytical methodologies, such as inductively coupled plasma optical emission spectrometry (ICP-OES) and X-ray fluorescence (XRF), demonstrated high-purity NiO (approximately 75%) with a low relative standard deviation (RSD <0.05%) and 90% recovery. The CRM AMIS 56 and SARM 33 were analysed alongside the samples to ensure reliable results were reproducible. Even at the lowest concentration of 1.5 ppm, NiO derived from fire assay waste demonstrated unambiguous sensing responses at 25˚C and 150˚C, with recovery times of 80 and 120 seconds, respectively. The potential of NiO from fire assay waste as an intriguing candidate for VOC sensing applications under ambient conditions was indicated by the highest response (Rg/Ra = 1.198 for 45 ppm ethanol) observed at 150˚C. The findings in paper IV highlight the suitability of nickel oxide synthesized from different methods for environmental sensing applications, particularly in volatile organic compounds detection. In Paper V, the focus is on the removal and characterization of impurities from pregnant nickel solutions at various pH levels, with an emphasis on enhancing nickel recovery and sustainable resource management. Lime is used as a precipitation agent to target impurities such as iron, lead, tin, manganese, and copper. The study employs inductively coupled plasma optical emission spectrometry (ICP-OES) to quantify and characterize these impurities. The objectives include improving analytical approaches for detecting trace contaminants, evaluating ICP-OES reliability for quality control, and assessing precipitation efficiency across different pH levels. Results reveal successful Fe3+ precipitation within the pH range of 2.0-3, alongside efficient manganese and copper precipitation at pH 5.5-6 and 4-6, respectively, aligning with established behaviours. The findings emphasise the significance of pH control for optimizing impurity removal from pregnant nickel solution, offering insights for enhancing nickel recovery processes in industrial settings. ICP-OES, supported by standard solutions and certified reference materials (CRMs), demonstrated exceptional linearity with correlation coefficients above 0.9995. The method showed high sensitivity, with detection limits and recoveries of CRM samples consistently within 10%. The study found that precipitation efficiency varies significantly with pH. Nickel (Ni) exhibited reduced precipitation at pH 2.02, with substantial precipitation occurring only at pH 6.5. Manganese (Mn) began precipitating at pH 2, achieving a peak removal efficiency of 98% at pH 6. Copper (Cu) precipitation started at pH 4, with a maximum efficiency of 99.3% between pH 4 and 6. Iron (Fe³⁺) was efficiently removed at pH 2.0-3.0. Significant variations in contaminant concentrations were observed, influenced by pH and precipitation agents. Fe³⁺ was removed with 100% efficiency at pH 2.5, while Cu precipitation was highly effective (99.3%) between pH 4 and 6. The decrease in Ni concentration at pH 2.02 was attributed to interactions with other metals rather than direct Ni precipitation. SEM revealed the morphology of the precipitates, showing a cauliflower-like structure for Ni(OH)₂ at pH 6.5 and the EDX confirmed the elemental composition of the precipitates, including Fe, Cu, Ni, Sn, Si, Al, Cl, Ca, and hydroxyl groups (OH), highlighting the presence of impurities precipitated at pH 2.5. This research highlights the effectiveness of ICP OES and EDX in trace impurity analysis and provides insights into optimizing precipitation processes, contributing to better recycling strategies and quality control in nickel processing and battery-grade materials. The study found that β Ni(OH)₂ precipitated optimally at pH 6.5, with a recovery rate of approximately 90.27% and minimal copper (79% loading efficiency) and iron impurities. Lime precipitation effectively removed Fe³⁺ at pH 2.5 and Cu between pH 4 and 6, with high removal efficiencies. Analytical methods such as EDXRF and FAAS, when calibrated, provided accurate results for trace elements, though discrepancies were noted for certain elements. The advancements in extraction and purification techniques, coupled with improved analytical methods and the novel application of NiO in VOC sensing, contribute significantly to the field of nickel recovery and processing. This research supports sustainable recycling practices and enhances the practical utility of recovered nickel, advancing both industrial applications and waste management strategies. Overall, this thesis contributes to advancing the understanding of impurity removal processes in nickel recovery and underscores the importance of precise control and characterization techniques in industrial applications.Item Dissolution of non-functionalized and functionalized nanomaterials in simulated biological and environmental fluids(University of the Witwatersrand, Johannesburg, 2023-06) Mbanga, Odwa; Gulumian, Mary; Cukrowska, EwaThe incorporation of nanoparticles in consumer products is exponentially high, however, research into their behaviour in biological and environmental surroundings is still very limited. In the present study, the static system and the continuous flow-through dissolution protocols were utilized to evaluate and elucidate the dissolution behaviour of gold, silver, and titanium dioxide nanoparticles. The behaviour of these particles was studied in a range of artificial physiological fluids and environmental media, to obtain a more precise comprehension of how they would react in the human body and the environment. The biodurability and persistence were estimated by calculating the dissolution kinetics of the nanoparticles in artificial physiological fluids and environmental media. The details of the current research are described as follows: An investigation into the dissolution of non-functionalized and functionalized gold nanoparticles was conducted as the first component of the research, examining the effect of surface functionalization on dissolution. The study determined the dissolution rates of functionalized and non-functionalized gold nanoparticles. Dissolution was observed to be significantly higher in acidic media than in alkaline media. The nanoparticle surface modification, particle aggregation, and chemical composition of the simulated fluid significantly affected the dissolution rate. It was concluded that gold nanoparticles are biodurable and have the potential to cause long-term health effect as well as high environmental persistency. This work has been published in the Journal of Nanoparticle Research and is presented in this thesis as Paper 1. Silver nanoparticles were also included in this study because they have many applications and industrial purposes. Therefore, their risk assessment was also of utmost importance. The results indicated that silver nanoparticle solubility was influenced by the alkalinity and acidity of artificial media. Low pH values and high ionic strength encouraged silver nanoparticle dissolution and accelerated the dissolution rate. The agglomeration state and reactivity of the particles changed upon exposure to simulated fluids, though their shape remained the same. The fast dissolution rates in most fluids indicated that the release of silver ions would cause short-term effects. This work has been published in Toxicology Reports and has been presented in this thesis as Paper 2. Although titanium dioxide nanoparticles are insoluble and undergo negligible dissolution, it was of utmost importance to investigate their behaviour in biological and environmental surroundings. This is as a result of the incorporation of these particles in everyday consumer products, in the nanosized range which raises concerns about their safety. Therefore, in Paper 3 presented in this thesis the dissolution kinetics of titanium dioxide nanoparticles in simulated body fluids representative of the lungs, stomach, blood plasma and media representing the aquatic ecosystem were investigated to anticipate how they behave in vivo. This work has been published in Toxicology In Vitro and presented in this thesis as Paper 3. The results indicated that titanium dioxide nanoparticles were very insoluble, and their dissolution was limited in all simulated fluids. Acidic media such as the synthetic stomach fluids were most successful in dissolving the particles, while alkaline media had lower dissolution. High ionic strength seawater also had a higher dissolution rate than freshwater. The dissolution rates of the particles were low, and their half-times were long. The results indicated that these particles could potentially cause health issues in the long term, as well as remain unchanged in the environment. This work has been published in Toxicology In Vitro and presented in this thesis as Paper 3. The last component of the research compared the dissolution kinetics of gold, silver and titanium dioxide nanoparticles through the use of the continuous flow-through system. The findings indicated that titanium dioxide nanoparticles were the most biodurable and persistent, followed by gold and silver nanoparticles. Therefore, it was suggested that product developers should use the OECD's guidelines for testing before releasing their product to the market to ensure its safety. This work has been published in Nanomaterials MDPI and presented in this thesis as Paper 4.Item Diastereoselective conjugate addition reactions using diverse nucleophiles on a variety of Morita-Baylis-Hillman (MBH) adducts(University of the Witwatersrand, Johannesburg, 2023-09) Bhom, Nafisa; Bode, Moira L.The Morita-Baylis-Hillman (MBH) reaction involves the formation of a new carbon-carbon bond, generating an MBH adduct. These MBH adducts are multi-functional molecules, which can be used as synthons for the generation of complex and diverse compounds. The first part of the work described here involved the synthesis of a series of diverse ester and nitrile MBH adducts obtained as racemic mixtures. The MBH adducts were protected using different protecting groups, which could potentially control the diastereoselectivity and the formation of alternative products in the subsequent conjugate addition reaction. Conjugate addition reactions were performed on the protected MBH adducts using different nucleophiles to obtain the product as diastereomers. These reactions were monitored to detect whether diastereomers were obtained or not. The diastereomeric ratios obtained using different substrates, protecting groups and nucleophiles were determined. The best diastereomeric ratio was 3:1, obtained for the piperidine and benzylamine addition on the TBDMS protected nitrile adducts 192a/b and 196a/b. The addition of sulfur nucleophiles gave the conjugate addition product only and the addition of nitrogen nucleophiles gave both conjugate addition and allylic substitution products. It was found that the protecting groups did not have an effect on the diastereomeric ratio obtained, nor on the formation of alternative products. The last step performed in the sequence was the deprotection of the conjugate addition products. The configuration of the major and the minor diastereomers were determined, the major product was assigned as the syn diastereomer. The major:minor diastereomeric ratio for compound 208a/b was 3:1 and for compound 209a/b, a ratio of 2:1 was obtained. The next part of the work involved the synthesis of MBH adducts with amide as the electron withdrawing group. The originally proposed route involved the synthesis of MBH esters and their conversion into amides. The conjugate addition reactions were attempted on these amide adducts, but were unsuccessful. A number of alternative routes were attempted for the synthesis of amide adducts and conjugate addition products resulting from these adducts. From all the alternative routes, the best route was the originally proposed route.Item Manganese-Rich Nickel-Manganese-Cobalt Oxides as Hybrid Supercapacitor Electrode Materials(University of the Witwatersrand, Johannesburg, 2023-09) Tshivhase, Funanani; Ozoemena, Kenneth IkechukwuFossil fuels used as the conventional energy source play a substantial negative role in climatic changes and global warming. Their reservoirs on earth keep getting constrained, thus limiting their reliability. These issues make renewable energy sources an excellent alternative due to their abundance, environmental safety, affordability, and renewability. However, renewable energy is subjected to geographic limitations, and some sources are intermittent, which can be solved by applying energy storage devices. Asymmetric hybrid supercapacitors are an excellent choice due to the safety of aqueous electrolytes, exploitation of abundant metals in the metal oxides used, improvement of power and energy density and simple assembly and application. In this work, manganese-rich nickel-manganese-cobalt (MR-NMC) was studied and applied in asymmetric hybrid supercapacitors as a cathode material, and reduced graphene oxide (rGO) was used as an anode. Synthesis was done using co-precipitation-(Conv), laminar Taylor vortex flow reactor-(Lam), and microwave irradiation-(MW) approaches. Physical characterization was performed using XRD and TEM. Electrochemical studies were done using CV, GCD and EIS. Three full cells/two electrode systems were assembled and studied. Those cells were rGO//Conv MR-NMC, rGO//Lam MR-NMC and rGO//MW MR-NMC. The data obtained from electrochemistry tests was used for the calculations of specific capacitance, energy and power densities. rGO//MW MR-NMC cell had the highest specific capacitance response compared to rGO//Conv MR-NMC and rGO//Lam MR-NMC over the entire current density range used, where at the current density of 0.2 A g-1, rGO//MW MR-NMC had 44.77 F g-1, followed by rGO//Lam MR-NMC with 15,89 F g-1, then rGO//Conv MR-NMC with 13.68 F g-1. There was no significant difference in the specific capacitance responses of rGO//Conv MR-NMC and rGO//Lam MR-NMC. rGO//MW MR-NMC also exhibited higher energy density for the entire range of power density over rGO//Conv MR-NMC and rGO//Lam MR NMC. At the power density of 678,08 W kg-1, rGO//MW MR NMC had a specific energy density of 65 Wh kg-1, followed by rGO//Lam MR NMC with 23.45 Wh kg-1, then rGO//Conv MR-NMC with 19.82 Wh kg-1. Overall, the electrochemistry and the calculated perimeters thereafter showed that microwave irradiation is a reliable approach that can be used in the preparation of metal oxides used in energy storage devices for the improvement of electrochemical performance, which potentially enables the commercialization of these systems and management of energy crisis in South Africa, Africa and the world as a whole, hence the rGO//MW MR-NMC material performed better than the other two.Item Imputation of missing values and the application of transfer machine learning to predict water quality in acid mine drainage treatment plants(University of the Witwatersrand, Johannesburg, 2024) Hasrod, TaskeenAccess to clean water is one of the most difficult challenges of the 21st century. Natural unpolluted water bodies are becoming one of the most dramatically declining resources due to environmental pollution. In countries like South Africa which has a mining-centred economy, toxic pollution from mine tailing dumps and unused mines leach into the underground water table and contaminate it. This is known as Acid Mine Drainage (AMD) and poses a grave threat to humans, animals and the environment due to its toxic element and acidic content. It is, therefore, imperative that sustainable wastewater treatment procedures be put in place in order to decrease the toxicity of the AMD such that clean water may be recovered. An efficient circular economy is created in the process since original wastewater can be recycled to not only provide clean water, but also valuable byproducts such as sulphur (from the elevate sulphate content) and other important minerals. Traditional analytical chemistry methods used to measure sulphate are usually time-consuming, expensive and inefficient, thereby, leading to incomplete analytical results being reported. To address this, this study aimed at imputing missing values for sulphate concentrations in one AMD treatment plant dataset and then using that to conduct transfer learning to predict concentrations in two other AMD treatment plants datasets. The approach involved using historical water data and applying geochemical modelling as a thermodynamical tool to assess the water chemistry and conduct preliminary data cleaning. Based on this, Machine Learning (ML) was then used to predict the sulphate concentrations, thus, addressing limited data on this parameter in the datasets. With complete and accurate sulphate concentrations, it is possible to conduct further modelling and experimental work aimed at recovering important minerals such as octathiocane, S8 (a commercial form of sulphur), gypsum and metals. Historical data obtained from the three AMD treatment plants in Johannesburg, South Africa (viz., Central Rand, East Rand and West Rand) were obtained and the larger Central Rand dataset was split into smaller untreated AMD (Pump A and Pump B) subsets. Thermodynamic and solution equilibria aspects of the water were assessed using the PHREEQC geochemical modelling code. This served as a preliminary data cleanup step. Eight baseline as well as three ensemble machine learning regression models were trained on the Central Rand subsets and compared to each other to find the best performing model that was then used to conduct Transfer Learning (TL) onto the East Rand and West Rand datasets to predict their sulphate levels. The findings pointed to a high correlation of sulphate to temperature (°C), Total Dissolved Solids (mg/L) and most importantly, iron (mg/L). The linear correlation between iron and sulphate substantiated pyrite (FeS2) as their source following weathering. Water quality parameters were found to be dependent on factors such as weather and geography this was evident in the treated water that had quite different chemistry to that of the untreated AMD. Neutralisation agents used were based on those parameters, thus, further delineating the chemistry of the treated and untreated water. The best performing ML model was the Stacking Ensemble (SE) regressor trained on Pump B’s data and combined the best performing models namely, Linear Regressor (LR), Ridge Regressor (RD), K-Nearest Neighbours Regressor (KNNR), Decision Tree Regressor (DT), Extreme Gradient Boosting Regressor (XG), Random Forest Regressor (RF) and Multi-Layer Perceptron Artificial Neural Network Regressor (MLP) as the level 0 models and LR as the level 1 model. Level 0 consisted of training heterogenous base models to obtain the crucial features from the dataset. These individual predictions and features were then fed to a single meta-learner model in in the next layer (level 1) to generate a final prediction. The stacking ensemble model performed well and achieved Mean Squared Error (MSE) of 0.000011, Mean Absolute Error (MAE) of 0.002617 and R2 of 0.999737 in under 2 minutes. This model was selected to be used for TL to the East Rand and West Rand datasets. Ensemble methods (bagging, boosting and stacking) outperformed individual baseline models. However, when comparing stacking ensemble ML that combined all the baseline models with stacking ensemble ML that only combined the best performing models, it was found that there was no significant improvement in excluding bad models from the stack as long as the good models were included. In one case, it was actually beneficial to include the bad performing models. All models were trained in under 2 minutes which proved the benefit of using ML approaches compared to traditional approaches. The treated water data was highly uncorrelated such that model training was unsuccessful with the highest achievable R2 value being 0.14, thus, no treated water model was available for TL. TL was successfully conducted on the cleaned and modelled East Rand AMD dataset using the Central Rand (Pump B) stacking regressor and a high level of accuracy with respect to Mean Square Error (MSE), Mean Absolute Error (MAE) and R2 (MSE:0.00124, MAE:0.0290 and R2:0.963) between the predicted and true sulphate values was achieved. This was achieved despite a marked difference in the distributions between the Central Rand and East Rand datasets which further proved the power of utilizing ML for water data. TL was successful in imputing missing values in the West Rand dataset following prediction of sulphate levels in the cleaned and modelled West Rand AMD and treated water datasets. No true values for sulphate levels in the West Rand dataset were given, as such, accuracy comparisons could not be made. However, a general baseline idea of the amount of sulphate present in the West Rand treatment plant could now be understood. The sulphate levels in all three treatment plants (Central Rand, East Rand and West Rand) were found to greatly differ from each other with the Central Rand having the most normal distribution, the East Rand having the most precise distribution and the West Rand having the most variable distribution. Whilst the sulphate levels in the treated effluent waters could not be reliably predicted due to inherent issues (e.g., analytical inaccuracies and inconsistences) and poor correlations within the treated water datasets, sulphate levels in all three of the untreated AMD datasets were successfully predicted with a high degree of accuracy. This underpinned the observation made previously about the discrepancies between treated and untreated water. The study has shown that it is possible to impute missing values in one water dataset and use transfer learning to complete and consolidate another similar, but scarce, dataset(s). This approach has been lacking in the water industry, resulting in the reliance and use of traditional methods that are expensive and inadequate. This has caused water practitioners to abandon scarce datasets, thus, losing potentially valuable information that could be useful for water remediation and recovery of valuable resources from the water. As a spin off from the study, it has been indicated that automation of such data analysis is possible. This was achieved by developing a Graphical User Interface (GUI) for ease of use of the SE-ML model by those with little to no programming background nor ML knowledge e.g., the laboratory staff at the AMD treatment plants. This can also be used for teaching purposesin academia.