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(2022)ThesisAlanates (i.e. NaAlH4 and LiAlH4) have been identified as the promising hydrogen storage candidates due to their high volumetric and gravimetric hydrogen densities. Extensive investigations have shown that the hydrogen kinetics and reversibility of NaAlH4 can be significantly enhanced upon the addition of catalysts. Unfortunately, the positive catalytic effects observed with NaAlH4 have been difficult to translate to LiAlH4 of a much higher hydrogen storage capacity. LiAlH4 also suffers from hydrogen thermodynamic constraints, and to date there is no clear path to effectively control the hydrogen storage properties of alanates. Nanosizing is believed to be an attractive alternative approach that could allow control over the hydrogen properties of complex hydrides. This thesis aimed at further understanding the potential of this approach and identify the significant hydrogen properties alterations occurring when alanates are nanosized. In this respect, particle size restriction was first implemented through the known method of hydrides confinement in mesoporous carbons. Through this learning, nanoconfined NaAlH4, LiAlH4, and KAlH4 all clearly demonstrated an improved hydrogen release and uptake behaviour, and this evidenced a clear correlation between particle size restriction and hydrogen properties across well-known alanates. From this learning, the focus had then been to translate the nanoconfinement approach to the freestanding alanate nanoparticles, where there is no dead weight from the scaffold to compromise the practical hydrogen storage capacity of alanates. Methods using both steric/electrostatic stabilisation had been established to effectively synthesise NaAlH4 and LiAlH4 nanoparticles. To enable hydrogen reversibility by keeping the decomposition products in close vicinity upon hydrogen release, method to enable the deposition of a titanium (Ti) metallic shell at the surface of the freestanding alanate particles had also been advanced. Hence, by forming a core(alanate)-shell(Ti) particles, the full storage hydrogen capacity of the material became accessible. More remarkably, through this nanosizing approach it became possible to shift and modify the thermodynamics of NaAlH4 and LiAlH4, their hydrogen release path, but also the position and shape of the equilibrium plateau pressure.
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(2022)ThesisConverting natural resources or greenhouse gases into value-added species with low carbon footprint, is essential for the development and sustainability of modern society. However, the goal for sustainable and cost-effective conversion by using many current technologies, including photo-, electro- and thermal-based catalytic reaction systems, has been largely underachieved. Hence, it is a necessity to explore and develop new approaches to fulfill this objective. In this thesis, three hybrid catalytic systems, containing liquid gallium (Ga) and solid materials as co-catalysts, are demonstrated, which realize the gaseous and liquid feedstocks conversion through nano-tribo-electrochemical reaction pathways. In the first stage of this PhD thesis, the author reports a green carbon capture and conversion technology for mitigating CO2 emissions. The technology uses suspensions of Ga liquid metal to reduce CO2 into solid carbonaceous products and O2 at near room temperature. The solid co-contributor of silver-Ga rods ensures a cyclic sustainable process. The overall process relies on mechanical energy as the input, which drives nano dimensional triboelectrochemical reactions. In the next stage, for the gaseous feedstock conversion, the author demonstrates an approach based on Ga liquid metal droplets and Ni(OH)2 co-catalysts for CH4 conversion into H2 and carbon. Mainly driven by the triboelectric voltage, originating from the joint contributions of the co-catalysts during agitation, CH4 is converted at the Ga and Ni(OH)2 interfaces. The efficiency of the system is enhanced when the reaction is performed at an increased pressure. The dehydrogenation of other non-gaseous hydrocarbons using this approach is also demonstrated. In the final stage, the author explores and realizes the liquid biofuels conversion, including canola oil and other liquid hydrocarbons, with H2 and C2H4 as the main products by employing Ga and nickel particles as the co-catalysts and mechanical energy as the stimulus. Altogether, the work of this PhD research offers novel pathways for low energy and green conversion of gaseous and liquid feedstocks that can be implemented in large scale conversion systems of the future.
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(2022)ThesisShifting away from the traditional mass production approach, the process industry is moving towards more agile, cost-effective and dynamic process operation (next-generation smart plants). This warrants the development of control systems for nonlinear chemical processes to be capable of tracking time-varying setpoints to produce products with different specifications as per market demand and deal with variations in the raw materials and utility (e.g., energy). This thesis aims to develop controllers to achieve time-varying setpoints tracking using contraction theory. Through the differential dynamic system framework, the contraction conditions for discrete-time systems, which ensure the exponential convergence between system responses and feasible time-varying references, are derived. The discrete-time differential dissipativity condition is further developed, which can be used for disturbance rejection control designs. Computationally tractable equivalent conditions are then derived and additionally transformed into an Sum of Squares programming problem, such that a discrete-time control contraction metric and stabilising feedback controller can be jointly obtained. Synthesis and implementation details of the resulting contraction-based controller are provided, which can achieve offset-free tracking of feasible time-varying references. To do contraction analysis and control design for systems with uncertainties, which are often complex and difficult, neural networks are used. It involves training and constructing a neural network embedded contraction-based controller. Learning algorithms of uncertain system model parameters are developed. The resulting control scheme is capable of achieving efficient offset-free tracking of time-varying references, with a full range of model uncertainties, without the need for controller structure redesign as the reference or uncertain parameter changes. This neural network based approach also ensures process stability during online simultaneous control and learning of uncertain parameters. To further improve the economics of contraction-based controller, a nonlinear model predictive control approach is developed. Contraction condition is imposed as a constraint on the optimisation problem for model predictive control with an economic cost function, utilising Riemannian weighted graphs and shortest path techniques. The result is a reference flexible and fast optimal controller that can trade off between the rate of target trajectory convergence and economic benefit (away from the desired process objective).
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(2022)ThesisExperimental and probabilistic methods were used to assess the risk of exposure to Legionella sp from aerators used in groundwater treatment plants. Factors considered include an assessment of conditions conducive to Legionella growth, detachment and inhalation by operators; the use of coupon studies to understand temporal changes and biofilm formation; and modelling the risk of Legionella using iterative Bayesian networks (BNs). A survey of 13 groundwater treatment plants (GWTPs) aerators, including tray, open and semi-enclosed systems were identified to feature design and operational risk factors favouring elevated levels of nutrients, water stagnation, challenging water quality, aerosolisation, and inconsistent operation and maintenance. Based on these observations, design considerations for the next generation of safer aerators that can overcome identified Legionella risks factors were outlined. Analysis of 300 sampling events from the aerators over five years indicated an average of 7% increase in colony counts between the inlet and outlet, indicating growth of Legionella within the aerators. In total, 28% of all samples collected from aerator surfaces testing positive for Legionella. However, there was no correlation between the type of aerator and Legionella positivity. Coupons were placed in aerators to assess temporal changes in fouling developed after 6 weeks of operation. The biological activity per unit area (ATP/cm2) was higher for samples collected on the sprayed (vertically placed) coupons (277 ng ATP/cm2) compared with the submerged (horizontally laid) (73 ng ATP/cm2) coupons. Concentrations of dissolved organic carbon (DOC) in the biofilm formed on the coupons were statistically similar for the two tested conditions. Comparing fouling characteristics from the lab and full-scale coupons confirmed the impact of surface orientation and influent characteristics on biofilm formation. In terms of cleaning of the fouled surface, NaOCl at (concentration greater than 6%) was found to achieve 99.9% efficiency in biofilm inactivation. Oxalic acid (concentration greater than 1%) significantly removed inorganic materials like iron and manganese. Combining biocides and antiscalants was therefore recommended to efficiently address fouling challenges in aerators. A BN which considered risk of exposure due to growth and transmission was developed using a fishbone diagram and bowtie analysis. The initial iterative output BN model was elicited deterministically through expert weighted scoring process and discretisation approach and defined relative contributions of risk variables. The BN model also efficiently categorised and differentiated Legionella risk thresholds. A revised BN model conceptually mapped and estimated the causes and consequences of Legionella aerosolisation separately. The Legionella growth sub-model showed weak prediction accuracy with a negative kappa coefficient, signifying inconsistency in predicted and observed Legionella occurrence. The effect of water quality was further explored with a data-driven learning approach using diverse historical water quality records. The optimised BN model utilised the greedy thick thinning approach, complemented with domain knowledge, and achieved superior performance accuracy exceeding 90%. The results indicated that water temperature, free chlorine, season, and heterotrophic plate count can be utilised to track Legionella occurrence in water systems.
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(2022)ThesisThe polydisperse solid-liquid system has been practised in many chemical engineering applications. A fundamental understanding of complex multi-phase flow with a wide particle size distribution (PSD) in the system is beneficial for process control and reactor optimisation, yet the currently existing numerical models, including conventional computational fluid dynamics - discrete element method (CFD-DEM), fail to capture the cross-scale inter-phase/particle interactions. Accordingly, multi-resolution models are developed in this thesis for the high-fidelity simulation of polydisperse solid-liquid systems. 1) A smoothed volume distribution model (SVDM) is first developed based on the unresolved CFD-DEM framework, with the capability of simulating the polydisperse solid-liquid system with a coarse-to-fine particle size ratio of up to 20. Via studying the migration of fine particles in suspension flow through a packed bed of coarse particles, the migration mechanism of fine particles is proposed and the inherent fundamental of clusters are elucidated. Via investigating the bed hydrodynamics in a bi-disperse solid-liquid fluidised bed (SLFB), the segregation and mixing mechanisms of particles in solid-liquid systems are illuminated. Via quantifying the solid transportation behaviours during the rapid filtration of dual-media filters, a probabilistic model is derived and verified for predicting clogging performance. This work establishes an effective framework to handle complex polydisperse solid-liquid systems. 2) Two acceleration methods (i.e., coarse-grained method and machine learning method) are studied, with the capability of simulating solid-liquid systems with improved computational efficiency at spatial and temporal scales, respectively. The coarse-grained method is employed to simulate large-scale particulate systems for unveiling the sedimentation mechanism of particles in water. The machine learning method is used to predict mixing and segregation behaviours in a solid-liquid system. This work provides an efficient method to predict granular flow behaviours in solid-liquid systems. 3) Further, a hybrid CFD-DEM model combining the resolved and unresolved CFD-DEM frameworks is originally developed, with the capability of simulating the polydisperse solid-liquid system with unlimited coarse-to-fine particle size ratios, for the first time. A resolved part obtains the fluid details around each coarse particle without extra models using fine grids (i.e., grid size to particle diameter ratio, lm/dp < 1/10), an unresolved part describes the fluid-fine particle interactions with empirical correlations using coarse grids (lm/dp > 3), and a semi-resolved part denotes the medium particle behaviours with a kernel-based approximation using medium grids (1/10 < lm/dp < 3). This work delivers a novel idea for modelling cross-scale solid-liquid flow and has the potential application to any polydisperse solid-liquid systems. This thesis represents collection of a suite of innovative numerical works of polydisperse particulate flows in solid-liquid systems and provides a range of numerical tools for understanding and optimising polydisperse solid-liquid flow systems.
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(2022)ThesisVat photopolymerisation (VP) is a promising additive manufacturing technology which enables the construction of complex 3D objects via versatile photochemistries. VP techniques have demonstrated superior advantages in imparting spatiotemporal control and providing high build rates and high printing resolution. However, current photocuring methods are based on non-living free radical or cationic polymerisation which offer limited control over chain growth, network formation and thus the final properties of 3D printed materials. Moreover, inert polymer chains produced during the polymerisation are incapable of being reactivated for post-functionalisation of pre-formed polymers. To fabricate materials with controlled properties and post-modifiable networks, photomediated reversible addition-fragmentation chain transfer (RAFT) polymerisation techniques were employed in VP. The addition of RAFT agents in photoresins provided control over polymer chain growth and network formation. Also, the retention of thiocarbonylthio polymer chain-ends in the network imparted living characteristics to 3D printed materials, which were easily post-modified with diverse functions and properties. This work firstly explored photoinduced electron/energy transfer-reversible additionfragmentation chain transfer (PET-RAFT) polymerisation in 3D printing under visible light irradiation in the open air. The use of an organic dye in conjunction with a tertiary amine as co-catalyst allowed fast printing speeds. The inclusion of RAFT agents in photoresins provided control over the mechanical properties of 3D printed materials. The presence of latent RAFT agents in the resin allowed post-functionalisation of these materials. Based on this study, photoresins containing RAFT agents with different activating Z groups and leaving R groups were investigated for their application in 3D printing. Also, the impact of the concentration of trithiocarbonates on mechanical properties of 3D printed materials was demonstrated. In addition, the 3D printed materials containing RAFT agents were easily post-modified via one-pot in situ aminolysis and thiol-Michael additions. Finally, the inclusion of RAFT agents in 3D printed thermosets materials conferred self-healing functionality. Materials containing trithiocarbonate units that were 3D printed under visible light can perform rapid self-repair via a secondary polymerisation mechanism under UV light irradiation under open-air conditions and at room temperature. This study promisingly paves the way for the fabrication of novel 3D printed thermosets with self-healing properties.
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(2022)ThesisPolymer Electrolyte Membrane Fuel Cells (PEMFCs) have been extensively investigated as promising candidates for a wide range of applications. However, the use of platinum (Pt), complex manufacturing processes and heavy reliance on auxiliary devices such as air blowers to operate existing PEMFCs have limited their applications to only small scales where more compact fuel cells are needed. PEMFCs operating with an open cathode enable to reduce the size and weight and eliminate parasitic power losses inherent to conventional PEMFCs. The self-breathing feature of PEMFCs would improve not only the system's overall efficiency, but also enable their silent operation. To date, self-breathing PEMFCs are in their infancy. One of the key requirements for the wide deployment of PEMFCs is to minimise or eliminate the need for Pt at the cathode to overcome the sluggish nature of the oxygen reduction reaction. Platinum alloyed with transition metals such as nickel and cobalt is an appealing approach to reducing the amount of Pt. Pt-free candidates based on nitrogen and iron-doped carbon would be better alternatives. To date, many Pt-alloys and Pt-free catalysts have shown encouraging performances; however, extensive testing under a fuel cell environment is needed to validate the viability of these catalysts. This work aims to develop efficient self-breathing PEMFCs by (i) re-thinking the design and making of self-breathing PEMFCs through 3D printing and alternative cylindrical geometries to enable better cell stacking and optimum self-breathing operation, (ii) developing alternative Pt-alloy catalysts based on copper, tin and iron suitable for both the hydrogen oxidation and oxygen reduction in PEMFCs, (iii) developing phosphorous and nitrogen-based catalysts that are Pt-free for the oxygen reduction at the cathode of fuel cells, and (iv) validating the performance of these new catalysts under prolonged self-breathing fuel cell operation. Overall, this work demonstrates the development of alternative self-breathing PEMFCs leading to superior performances and a path towards powering small and portable applications.
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(2022)ThesisLiquid metals (LMs) are a class of metals and their alloys which have low melting points near or below room temperature, and they are mainly composed of post-transition elements. The low melting points of LMs make them easily stay in a liquid state and readily be broken into tens or hundreds of nanometers, which are called LM nanoparticles (LMNPs). In this thesis, the author investigates LMNPs for three exciting applications of creating conductive polymer-LMNPs compositions and explores the potential utilization of LMNPs in biological applications. In the first phase of this research, the author develops nanocomposites of Ga-based LMNPs (EGaIn NPs) with conductive polymer polyaniline (PANI). This work reports a method of growing PANI nanofibers on the EGaIn NPs by firstly providing initial functionalization sites at the interfaces for the formation of PANI nanofibrous network. The nanocomposites provide synergistic effects of PANI nanofibers and EGaIn NPs for the applications of environmental sensing and molecular separation. In the second phase of the research, the author focused on the exploration of LMNPs for their anti-inflammatory applications. Considering that Ga ions (Ga3+), have been historically utilized as anti-inflammatory agents by interfering with the Fe homeostasis of immune cells. The study presents the anti-inflammatory effects of Ga by delivering Ga nanoparticles (Ga NPs) into lipopolysaccharide-induced macrophages. The Ga NPs show a selective anti-inflammatory effect by modulating nitric oxide production without disturbing other pro-inflammatory mediators. This work reveals the different anti-inflammatory effects between Ga NPs and Ga3+ come from their different endocytic pathways: transferrin receptor independent and dependent endocytosis for Ga NPs and Ga3+, respectively. In the final phase, the author studies the interactions between LMNPs and macrophages at a light microscopic level. The mechanistic responses of macrophages to LMNPs with different densities were observed, in comparison to some other commonly studied nanoparticles. This work discovers the mobility of macrophages is very much density-dependent. This thesis comprehensively studies the interactions between LMNPs and polymeric and biological systems, at both molecular and microscopic levels, which provides a basis and road map for utilizing LMNPs in various fields such as electronics and biomedical engineering.
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(2022)ThesisZinc-azole-based metal organic frameworks (MOFs) have been demonstrated to exist in a wide variety of structural states, with applications in different fields such as gas separation. In this dissertation, we explore the phase control and dynamics of zinc-azolebased MOFs in crystalline, liquid, and glassy states. We first study ZIF-7 phase control using mechanochemical synthesis. Ammonium nitrate was found to be a good catalyst in mechanochemical ZIF formation, with the usage of DMF and H2O favouring ZIF-7-I and ZIF-7-III formation, respectively. New phases of ZIF-7 variations not accessible using the solvothermal method were also obtained mechanochemically indicating the possibility of a new mechanochemical synthesis route. The mechanochemical ZIF-7 mixed matrix membrane (MMM) demonstrates good CO2- based selectivity improvements. Next, we demonstrate the formation of a new meltable zinc-azole framework (ZnCP) with liquid crystal behaviour by the addition of orthophosphate. ZnCP was able to melt at a low temperature while retaining and orienting its crystallinity into transparent liquid, thus showing promising use in optical-based applications. This material can also be obtained using a top-down approach by adding phosphoric acid to ZIF-7. Controlling phosphoric acid incorporation results in different melted ZnCP particle ratios, which was explored as a gas separation membrane. We then explore the effect of silver (Ag) composite presence on the thermal dynamics of another zinc-azole framework (ZIF-62). The benzimidazole amount within the Ag-doped ZIF-62 structure affects its thermal conversion, forming either Ag-doped ZIF-zni or Agdoped ZIF glass. The thermal dynamics of Ag-doped structures were explored using both in-situ (thermal) and ex-situ techniques. Both Ag-doped phases were demonstrated to have good MMM separation improvements for CO2 and light hydrocarbon, indicating the accessibility of the silver composite. Lastly, a quick demonstration of new methods (dip and spin coating) to process ZIF-62 and ZIF-62 composite successfully forms continuous particle dispersion, allowing the formation of a continuous glass layer. Different compositions such as sandwiched structure and layer by layer were explored, with advantages outlined. The novelty of this dissertation lies within the exploration of new synthetic methods and thermal dynamics to form structurally diverse zinc-azole MOFs which will be beneficial in the understanding of phase transformations in MOFs
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(2022)ThesisHot water washing systems, applied separately or in combination with steam pasteurization and the use of chemical disinfectants, such as chlorine and organic acids, are conventionally used in the meat industry to achieve microbial safety and reduce the risk of cross-contamination throughout carcass processing. The application of heat in hot water washes, applied at temperatures greater than 74°C, and steam in steam pasteurization, causes adverse sensory changes particularly in the appearance and texture of treated surfaces. Similarly, organic acid spray washes can lead to discolouration of cut meats. Furthermore, there are growing concerns over the emergence of acid-tolerant and chlorine resistant food borne pathogens as well as concerns over the formation of carcinogenic by-products through reactions between chlorine and organic matter. Novel cold plasma technologies including plasma activated water (PAW), have shown real promise as an alternative and environmentally conscious meat decontamination method. In this study, the effects of plasma activated water on planktonic and adhered cells on beef surfaces and the potential for induced resistance was examined. Additionally, the impact of PAW on quality attributes was also investigated. Results show that PAW generated by a pin-to-plate spark air plasma reduced planktonic cell population of P. fluorescens, L. lactis and B. thermosphacta, E. coli, L. monocytogenes and S. Typhimurium by 0.58, 0.70, 0.57, 0.53, 1.69 and 1.16 log, respectively. PAW’s efficacy was lessened when used to treat adhered cells on beef and lamb. A log reduction of 0.37, 0.40, 0.69 log on beef and a 0.29, 0.19, 1.07 log on lamb was reported for S. Typhimurium, E. coli and L. monocytogenes, respectively. PAWs efficacy is improved through changes in the generation parameters including an increase in initial water conductivity and water activation time. Contact time between PAW and the treated surface was also determined to be a determining factor in PAWs antibacterial activity. Furthermore, the application of warm PAW (35°C and 55°C) significantly reduced bacterial population when compared to PAW applied at room temperature. When applied onto meat surfaces, PAW showed no significant reductions in the nutritional composition of meat including vitamin B6, zinc, iron, selenium and protein. PAW treatment also did not significantly change colour coordinate values of L*, lightness, and b*, redness of beef samples. Furthermore, the extent of lipid oxidation was reduced with PAW treatment compared to water and lactic acid. Therefore, our findings demonstrates that PAW may be a viable meat decontaminant with minimal effect on the desirable quality attributes of meat.
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