Chemical Engineering
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This is the collection for the University of Waterloo's Department of Chemical Engineering.
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Item Advanced Separator Modifications for Lithium-Sulfur Batteries: Multifunctional Organic Frameworks and Nanostructured Composites to Mitigate the Polysulfide Shuttle Effect(University of Waterloo, 2025-02-18)This thesis explores innovative approaches to addressing critical challenges in lithium-sulfur (Li-S) battery technology through the development of modified separator materials. The escalating concerns surrounding climate change, pollution, and fossil fuel depletion are propelling a global transition toward renewable energy sources like wind, solar, and hydropower. Alongside this shift is an increasing demand for efficient, high-capacity, and cost-effective energy storage systems that support these sustainable energy technologies, especially for applications in electric vehicles. Various rechargeable battery technologies, such as lithium-ion, sodium-ion, potassium-ion, magnesium-ion, zinc-ion, and aluminum-ion batteries, have garnered significant research attention due to their high efficiency, reversibility, light weight, and environmental friendliness. Although lithium-ion batteries have achieved widespread success in portable electronics and electric vehicles, they have limitations when it comes to the growing demand for energy density, long cycle life, and affordability. Consequently, next-generation batteries—particularly those based on sulfur chemistry—are being developed to meet these requirements. This thesis specifically investigates how functional materials for separator modification can address the main issues of polysulfide shuttle and conductivity in Li-S batteries, aiming to make these batteries more feasible for next-generation energy storage applications. The first study in this thesis focuses on designing a series of melamine-based porous organic frameworks (POFs) as efficient polysulfide reservoirs to modify glass fiber (GF) separators in Li-S batteries (LSBs). Despite the promising energy density of Li-S systems, the polysulfide shuttle effect—where lithium polysulfides (LiPSs) dissolve and migrate between electrodes—remains a significant barrier to achieving stable cycling and high capacity retention. To tackle this challenge, we synthesized a series of POF materials (POF-C4, POF-C8, and POF-C12) by reacting melamine with dibromoalkanes of varying chain lengths (C4, C8, and C12). The resulting POFs displayed distinct nanoscale pore sizes and solubility properties, which are critical for effective LiPS trapping and utilization. These POFs were then combined with conductive Super P (SP) and polyvinylpyrrolidone (PVP) binder to create a composite layer (POF-Cn/SP/PVP) that was coated onto GF membranes, forming modified separators that enhance the electrochemical performance of Li-S batteries. The batteries incorporating these modified separators were evaluated through various electrochemical tests, and the POF-C8/SP/PVP-modified separator, in particular, demonstrated outstanding performance. It delivered an initial specific capacity of 1392 mAh g⁻¹ at 0.1C and retained 90% capacity over 300 cycles at 0.5C. This enhanced performance can be attributed to the optimal pore structure of POF-C8 and its high nitrogen content, which work in tandem to capture soluble LiPSs and limit their migration toward the lithium anode. Furthermore, the good solubility of POF-C8 ensures uniform dispersion and strong interactions with LiPSs, enabling efficient redox reactions. This study highlights the potential of functional polymer-based separator modifications to mitigate polysulfide migration, improving the stability and longevity of Li-S batteries. The second study investigates the use of Congo Red (CR), a redox-active organic compound, in conjunction with cetyltrimethylammonium bromide (CTAB), a cationic surfactant, to modify GF separators for improved LSB performance. CR has a unique capability of engaging in redox reactions, which aids in suppressing the polysulfide shuttle by capturing LiPSs at the separator interface. The CR-CTAB/SP/PVP-modified GF separators demonstrated enhanced ion transport properties and higher sulfur utilization, addressing core issues that commonly degrade Li-S battery performance. Electrochemical performance tests revealed that LSBs with these CR-CTAB-modified separators achieved an initial specific capacity of 1161.9 mAh g⁻¹ and maintained 994.1 mAh g⁻¹ after 300 cycles at 0.5C, showing significant improvement over the baseline unmodified GF separators. The CR molecules in the separator modification layer serve as efficient adsorbents for polysulfides, while the CTAB molecules aid in stabilizing the structure and enhancing ion transport across the separator. This work emphasizes the importance of incorporating redox-active molecules into separator designs, showing that such molecules can effectively reduce the shuttle effect, enhance performance, and create more durable energy storage systems. The third study delves into the incorporation of a nanocomposite composed of CR and tin dioxide (SnO₂) nanoparticles for further improvement of polysulfide-trapping capability and redox kinetics in GF separators. The CR-SnO₂/SP/PVP-modified separators were synthesized by combining CR, SnO₂ nanoparticles, conductive SP, and PVP binder. This approach resulted in a composite layer with enhanced surface interactions and improved electron transport pathways. Structural characterization using techniques such as scanning electron microscopy (SEM), X-ray diffraction (XRD), and transmission electron microscopy (TEM) confirmed the uniform dispersion of CR and SnO₂, indicating strong cooperative interactions between these components. Electrochemical tests demonstrated that LSBs incorporating the CR-SnO₂-modified separators exhibited exceptional performance, with an initial specific capacity of 1377 mAh g⁻¹ at 0.1C and capacity retention of 91% over 300 cycles at 0.5C. The CR-SnO₂ composite material provides dual benefits: CR molecules effectively capture LiPSs, while SnO₂ nanoparticles act as catalysts, promoting redox reactions and enhancing ion transport. This synergy between CR and SnO₂ in the separator layer contributes to stable cycling performance and mitigates capacity loss due to polysulfide migration, making this composite a promising solution for improving Li-S battery stability. The forth study address the shuttle effect challenge by employing cysteine and layered double hydroxides (LDHs) as 2D materials to create an innovative 2D heterostructure (Cys/FeNi-LDH). This heterostructure serves as a robust support for immobilizing V2O5 nanoparticles (NPs). Incorporating V2O5/Cys/FeNi-LDH (VCFN) into a GF separator ensured stable electron and ion pathways, significantly enhancing long-term cycling capabilities. The use of L-cysteine, a cost-effective and readily available amino acid, played a crucial role in enhancing the Li-S battery performance. The remarkable enhancement in electrochemical performance is attributed to the synergistic effects of VCFN nanoparticles, cysteine, and SP. A Li-S battery featuring the VCFN GF separator demonstrated an impressive initial capacity of 1036.8 mAh g⁻¹ and, after 300 cycles at 0.5C, retained a capacity of 920.1 mAh g⁻¹. This thesis demonstrates that modifying the separator is a highly effective strategy for addressing the primary challenges in Li-S batteries, particularly the polysulfide shuttle effect. By tailoring the physical and chemical properties of the separator layer, significant improvements in capacity retention, cycling stability, and rate performance have been achieved. Each of the materials that used for modification of GF separators demonstrates the potential to enhance battery performance through unique mechanisms. The melamine-based POF-C8-modified separator leverages a nanoscale porous framework to trap polysulfides and improve LiPS utilization. Meanwhile, the CR-CTAB and CR-SnO₂ composites add a redox-active element to the separator, aiding in polysulfide trapping and catalyzing redox reactions at the interface. A novel composite of V₂O₅ nanoparticles on Cys/FeNiLDH sheets (VCFN) was synthesized and used to modify GF separators, enhancing the electrochemical stability of LSBs. This research contributes to the field of LSBs by providing insights into the design of multifunctional separators that simultaneously address multiple performance issues, including polysulfide retention, ion transport, and redox catalysis.Item A High-Order, Flow-Alignment-Based Compartmental Modelling Method(University of Waterloo, 2025-02-11)Industrially-relevant chemical engineering processes, such as stirred tank bioreactors in the pharmaceutical sector, inherently operate across multiple scales and involve complex, multiphysics, and multiphase interactions. Modelling of these systems is essential for their design, optimization, control, and operational troubleshooting; these processes are often too intricate for experimental approaches alone, with trial runs proving prohibitively costly or key metrics being difficult or impossible to measure. Traditionally, modelling such systems has relied on simplified design equations or idealized models, such as the continuously stirred tank reactor (CSTR). However, these approaches lack the explanatory power required to capture real-system outcomes, such as concentration gradient formation. With advancements in computational capabilities, computational fluid dynamics (CFD) simulations have become standard for investigating specific questions within these systems. Nonetheless, certain critical applications, such as extended simulations of microorganism growth or real-time predictive control, remain impractical due to their high computational demands. Reduced Order Models (ROMs) offer a middle ground between the simplistic CSTR models and the computationally intensive CFD simulations. ROMs trade off some of the generality and accuracy of CFD simulations in exchange for a substantial reduction in computational cost, often by several orders of magnitude. This work focuses exclusively on a specific type of ROM: Compartmental Models (CMs). They are underpinned by the assumption of one-way coupling between the hydrodynamics and mass transport of reactive species. CMs are constructed through a two-step process. First, the domain is divided into non-overlapping compartments using a set of criteria; next, each compartment is represented by one or more simplified models. This network of models decouples mass transport from hydrodynamics and reduces the number of degrees of freedom on which the conservation of mass of the reactive species needs to be solved. This reduction is particularly important for bioreactors, where hundreds of coupled nonlinear reactions are common. Current compartmental modelling methods exhibit several limitations, such as a disconnect between the criteria used for compartment identification and their subsequent modelling, an assumption that each compartment is well-mixed, a reliance on manual compartmentalization or manual intervention, and a non-prescriptive framework that is challenging to adapt to new geometries. This work introduces a novel compartmental modelling method based on flow alignment. The velocity field is analyzed and split into compartments within which the flow is unidirectional. Each compartment is then modelled as a series of 1D Plug Flow Reactors (PFRs). Benchmarking this method against the state-of-the-art method demonstrates that it yields more accurate results while achieving computational speeds that are orders of magnitude faster than traditional CFD simulations. Further, many current CM approaches simplify three-dimensional geometries by either modelling two-dimensional cross-sections and relying on rotational symmetry or by using a uniform grids of compartments. The developed method is extended to fully three-dimensional two-phase stirred tank systems without using these assumptions. It successfully compartmentalizes the distinct recirculatory regions generated by the impellers, eliminating the manual ad hoc intervention required by past methods. Mixing time and concentration predictions at probe locations are validated against CFD simulations, other CMs, and experimental data. The proposed general method performs as well or better than past CMs which were tailor made for the stirred tank geometry. Further, the model's capability to handle complex spatially varying reactions is demonstrated by simulating oxygen dissolution into the liquid phase, accurately capturing spatial gradients in dissolved oxygen concentration. Lastly, a significant limitation in previous compartmental modelling work is the reliance on a single velocity snapshot or a time-averaged steady-state velocity field. For instance, in the case of vortex shedding from a cylinder in the laminar flow regime, neither time-averaged velocity-based CM nor an ensemble of CMs based on discrete velocity snapshots accurately captures the impact of the inherently non-stationary flow topology. The non-stationary nature of such flow fields is addressed by employing projection mappings to cycle through a series of compartmental models, allowing dynamically updating their shape, number, location, and connections. This approach successfully captures the oscillation period of the flow and demonstrates promise in representing non-stationary flow behaviours accurately. In summary, this work advances the field of compartmental modelling by unlocking their the application to complex, industrially-relevant systems by developing a generalized, alignment-based method. This method extends the capability of CMs to handle both time-varying and fully three-dimensional multiphase flows without requiring manual intervention. The approach is validated through benchmarking against CFD simulations, other CM approaches, and experimental data, demonstrating improvements in computational efficiency and accuracy.Item Transition metal doped ceria catalyst prepared by direct precipitation method for thermocatalytic conversion of carbon dioxide via reverse water gas shift(University of Waterloo, 2025-02-05)Since the beginning of the industrial revolution, mankind has utilized large amounts of fossil fuels to obtain energy, which has led to the emission of large amounts of greenhouse gases such as carbon dioxide. How to reduce CO2 and utilize CO2 to obtain high-value products has become a hot topic in today's research. The thermocatalytic reduction of CO2 by using renewable H2 is expected to be a potential solution to these challenges. In this experiment, the reverse water gas shift (RWGS) reaction of various loaded transition metal doped cerium (MCeO2) catalysts (M = Fe, Co, Ni and Cu) was investigated. The desired catalysts have been synthesized by utilizing the direct precipitation method. The reverse water gas shift reaction has been extensively studied including reaction tests and some characterizations such as X-ray crystallography (XRD), Brunauer Emmett Teller (BET), Temperature Programmed Desorption (TPD), Inductively coupled plasma - optical emission spectrometry (ICP - OES) etc. In reaction tests, the performance of M-CeO2 was evaluated in terms of conversion and selectivity by varying the temperature (400°C - 600°C). The resulting reaction products were monitored using an on-line infrared analyzer to identify the formation of carbon monoxide (CO), methane (CH4), and unconverted CO2. T-test results show that transition metal doping has a significant effect in enhancing the surface CO2 adsorption and reduction. effects, including high loading of Fe with higher than 56% CO2 conversion and 100% selectivity to CO at 600 °C, Cu with 100% selectivity to CO but lower CO2 conversion, and Co and Ni with significant methanation ability, especially at high loading. In addition, the structures of the catalysts before and after the reaction were investigated using XRD. The binding strength of CO2 on the doped CeO2 surface was investigated using the programmed temperature rise desorption (TPD) method. The effect of specific surface on CO2 adsorption was investigated using BET. This experiment explores the effect of different kinds of transition metal-doped cerium catalysts on the reverse water-gas shift (RWGS) reaction, which reduces excess CO2 emissions and also provides an idea for CO2 conversion and utilization.Item Techno-Economic Assessment of Carbon Capture for Integrated Steel Mills in Canada(University of Waterloo, 2025-01-29)Globally and within Canada, steel production accounts for 10% and 23% of total industrial CO2-eq emissions, respectively. This is primarily owed to the prevalence of the traditional blast furnace-based integrated steel mill, responsible for 73% of steel production globally. This thesis investigates the techno-economic feasibility of carbon capture methods within a Canadian integrated steel mill, focusing on reducing the direct emission intensity of hot rolled steel slabs till non-emitting steel production methods can be employed. The study emphasizes two post-combustion capture techniques: First, Monoethanolamine (MEA) absorption identified as the primary technology due to its maturity and cost efficiency. Second, hybrid methods combining vacuum pressure swing adsorption with low-temperature purification (VPSA-LTP) are explored for their commercial potential and lower thermal energy penalty relative to the chemical absorption base case. A systematic framework involving performance modelling using Aspen Plus and Aspen Adsorption, and cost assessment evaluates energy consumption, cost implications, and environmental benefits of both carbon capture methods. The opportunity for waste heat recovery for the steel production process was also evaluated. A surrogate-based optimization framework was developed and proven to be a tool for conducting a less-computationally intensive techno-economic assessment of batch separation processes. Key findings highlight that the lowest capture cost of $75 per tonne of CO2 captured ($86 per tonne of CO2 avoided) is achieved using a single-point of capture: the central power station, due to its volume and high CO2 composition. To achieve this minimum cost alongside its’ lowest achievable steel emission intensity, this carbon capture implementation includes MEA absorption with an oxy-combustion boiler and waste heat recovery from flared gas and flue gases to offset energy demand. In the case of natural gas supply constraints and overall reliance on electricity, using a hybrid VPSA-LTP process offers the lowest electricity consumption at a cost of $120 per tonne of CO2 avoided. Overall, carbon capture can be used to reduce the emission intensity to 0.76 tonnes of CO₂ per tonne of hot rolled steel slabs while increasing the production cost by 17% to $741 per tonne of steel. It is recommended that advanced solvents and sorbent be explored to further reduce the energy penalty and increase the productivity of their respective methods. There must also be evaluation of alternative decarbonization schemes for further emission reduction and the potential of heat integration with the existing power station to generate more steam in lieu of electricity. There must also be a multi-disciplinary assessment of the impact of policies on the viability of carbon capture as a decarbonization solution for the steel industry.Item Engineering cell-penetrating peptide mediated protein-bound nanoparticles for delivering siRNA and chemotherapeutics(University of Waterloo, 2025-01-27)Proteins serve as the “workers” of biochemistry, orchestrating nearly all biological functions. Functional endogenous proteins are often related to the pharmacokinetics and pharmacodynamics of drugs and nanomedicines, particularly in processes such as drug absorption, biodistribution, and metabolism. That means the innate interactions between proteins and drugs/nanoparticles exist, but the discovery and application of these interactions are underappreciated so far. By imitating the protein binding behaviors and interactions, some proteins may hold significant promise in drug and nanoparticle delivery due to their biocompatibility and functionalities. This thesis presents a methodology for engineering biomimetic protein coronas to camouflage cationic peptide/siRNA (P/si) nanocomplexes by utilizing proteins derived from the innate P/si protein corona (P/si-PC), which was also applied to the peptide-based lipid nanoparticles (pLNP). By leveraging these protein corona species, an efficient method for producing protein-bound chemotherapeutic nanoparticles in aqueous phases using microfluidic technology was developed. For cationic nanoparticles, the spontaneous nanoparticle-protein corona formation and aggregation in biofluids can trigger unexpected biological reactions. This thesis presents a biomimetic strategy for camouflaging the P/si with single or dual proteins, which exploits the unique properties of endogenous proteins and stabilizes the cationic P/si for safe and targeted delivery. An in-depth study of P/si-PC formation and protein binding was conducted. The results provided insights into the biochemical and toxicological properties of cationic nanocomplexes and the rationales for engineering biomimetic protein camouflages. Based on this, the human serum albumin (HSA) and apolipoprotein AI (Apo-AI) ranked within the top 20 abundant protein species of P/si-PC were selected to construct biomimetic HSA-dressed P/si (P/si@HSA) and dual protein (HSA and Apo-AI)-dressed P/si (P/si@HSA_AI), given that the dual-protein camouflage plays complementary roles in efficient delivery. A branched cationic cell-penetrating peptide (CPP, b-HKR) was tailored for siRNA delivery, and their nanocomplexes including the cationic P/si and biomimetic protein-dressed P/si were produced by a precise microfluidic technology. The biomimetic anionic protein camouflage greatly enhanced P/si biostability and biocompatibility, which offers a reliable strategy for overcoming the limitation of applying cationic nanoparticles in biofluids and systemic delivery. Currently, commercially applied lipid nanoparticles (LNPs) for RNA delivery, such as in siRNA and mRNA vaccines, utilize similar lipid compositions and ratios, raising the risk of unintentional patent infringement. This research attempted to engineer a novel peptide-based LNP formulation stabilized and functionalized by artificial protein corona that constitutes HSA and lipoprotein (Apo-AI; apolipoprotein E, Apo-E). The cationic peptide (b-HKR) enabled efficient siRNA condensation and reversible protein binding. Combining b-HKR and the artificial protein corona offers an alternative to the commonly used ionizable lipids, PEG-lipids, and excipients (such as sucrose), providing both pH-responsive functionality and storage stability. The in vitro results showed that the dual protein (HSA and Apo-AI) functionalized pLNP (pLNP@HSA_AI) is optimal for enhanced stability and RNAi efficacy. In contrast, single protein-functionalized pLNPs encountered a dilemma: pLNP@HSA improved stability but showed almost no RNAi efficacy, while the pLNP@AI exhibited remarkable RNAi efficacy but aggregated upon the addition of Apo-AI. The dual protein (HSA and Apo-E) functionalized pLNP (pLNP@HSA_E) also showed promise in addressing this dilemma, although the use of Apo-E is less cost-effective than Apo-AI due to its limited availability. The use of endogenous proteins, particularly albumin, for the targeted delivery of chemotherapeutics has proven practical. However, how to effectively produce the protein-bound chemotherapeutics nanoparticles in a complete aqueous phase (without the use of organic solvents) is worth pursuing to eliminate the solvent-related safety risks. In this research, the protein-bound Dox (Dox) nanoparticles were successfully produced through a one-step microfluidic mixing process in aqueous phases, in which the nanoparticle formation was instantaneously mediated by a self-assembled nano-peptide (np). The np-mediated HSA-bound Dox (D-np-HSA) and dual proteins (HSA; Apo-AI)-bound Dox (D-np-HSA-AI) nanoparticles exhibited efficient drug encapsulation and pH-triggered drug releases. In vitro cellular studies showed that the nanoparticles (D-np-HSA and D-np-HSA-AI) exhibited superior efficacy in killing tumor cells (A549 and MCF7) while being less toxic to normal cells (NIH3T3) compared to free Dox. Notably, D-np-HSA-AI was less prone to induce drug resistance, and cell lines that developed resistance to free Dox remained sensitive to D-np-HSA-AI. Besides, the results revealed that drug resistance development of A549 is associated with cellular phenotypic (size, morphology, and dividing speed) changes. Cellular (cytoplasmic and nuclear) proteomics was conducted by comparing the protein species, abundances, and relation networks of normal, Dox-induced, and nanoparticle (D-np4-HSA-AI) induced A549 cells, which aimed to provide potential protein biomarkers associated with drug resistance and druggable protein/gene targets for overcoming the drug resistance.Item Rheology of Suspensions and impact of Cellulose Nanocrystal as an additive(University of Waterloo, 2025-01-23)Suspensions, as complex fluids, embody a fascinating interplay of solid particles within a liquid medium, presenting a diverse range of viscosity behaviors. Unlike simple Newtonian fluids, suspensions exhibit non-linear responses to applied forces, owing to interactions between dispersed particles and the surrounding solvent. Their viscosity can vary significantly with factors such as shape and size of particle, surface chemistry and concentration. Understanding the rheological properties of suspensions is crucial across industries like pharmaceuticals, cosmetics, paints, and food processing, where their flow behavior dictates product quality and performance. The research examines the consistent rheological characteristics of suspensions containing solid particles thickened by cellulose nanocrystals. Two distinct types and sizes of particles are utilized in preparing the suspensions: TG hollow spheres with a Sauter mean diameter of 69 µm and Solospheres S-32 with a Sauter mean diameter of 14 µm. The concentration of nanocrystals ranges from 0 to 3.5 wt%, while the particle concentration varies from 0 to 57.2 vol%. Additionally, the study investigates the impact of salt (NaCl) concentration upto 2 wt% and pH varying from 3 to 11 on suspension rheology. Generally, the suspensions display shear-thinning behavior, with a more pronounced effect observed in suspensions containing smaller particles. Experimental viscosity data conform well to a power-law model, with variations in flow behavior index and consistency index and under different conditions being thoroughly examined and discussed.Item Melt-blowing of polymers for porous and functional air filters(University of Waterloo, 2025-01-23)This thesis develops innovative, high-performance, melt-blown nonwoven materials for air filtration. The first chapter presents a two-step process to create nano-porous, compostable PLA nonwovens with high porosity for particulate capture. First, PLA is melt-blended with polyethylene glycol (PEG) of varying molecular weights to enhance melt flow index (MFI), producing blends with MFI values ranging from 56 g/10 min to 238 g/10 min. These blends are processed into microfibers, with diameters from 1.05 to 2.64 µm, using a twin-screw extruder. The second step involves boiling water etching to remove PEG and form nanopores (50–200 nm), achieving approximately 85% particulate capture efficiency for 0.3 µm NaCl particles. This eco-friendly method shows potential for air and water filtration and battery separators. The second chapter addresses the limitations of conventional face masks, which lack antibacterial or antiviral properties. To improve mask functionality, advanced melt-blown filters are created using polypropylene (PP) and Rose bengal (RB), a photosensitizer. The study investigates the impact of processing temperature on fiber morphology, filtration efficiency, and antibacterial properties. The optimized filters show superior antibacterial performance, particulate filtration efficiency, and breathability, offering significant improvements for personal protective equipment (PPE), with enhanced antimicrobial protection and durability.Item Effect of substrate topography on human vascular smooth muscle cell proliferation and phenotype change(University of Waterloo, 2025-01-22)Cardiovascular diseases (CVDs) remain the leading cause of mortality worldwide, with vascular occlusion being a primary contributor. Bypass grafting is a common surgical intervention to restore blood flow, traditionally using autologous grafts such as saphenous veins and internal thoracic arteries. However, the limited availability and invasive harvesting process of autologous grafts have prompted the development of synthetic small-diameter vascular grafts (sSDVGs) as alternatives. Despite advancements, the clinical efficacy of sSDVGs remains unsatisfactory due to high rates of thrombotic occlusion, intimal hyperplasia (IH), and restenosis, primarily caused by dysregulated vascular smooth muscle cell (VSMC) behavior. VSMCs play a critical role in the progression of IH through their proliferation, migration, and phenotypic plasticity following vascular injury. While extensive studies have explored the influence of substrate topography on endothelial cell (EC) response, the effects on VSMCs remain underexplored. This study investigates the hypothesis that substrate topographies with varying geometries, isotropy, and sizes can differentially regulate VSMC behavior, potentially mitigating IH and improving the functionality of sSDVGs. To test this hypothesis, a 16-pattern multiarchitecture (MARC) chip was employed to screen various surface patterns for their ability to modulate VSMC phenotype. Five promising patterns were selected and individually fabricated on polydimethylsiloxane (PDMS) substrates for further evaluation. The influence of these topographies on VSMC behavior was assessed under normal and platelet-derived growth factor (PDGF)-stimulated conditions by analyzing protein markers associated with VSMC phenotypic states, including α-smooth muscle actin (α-SMA), phosphorylated myosin light chain kinase (pMLCK), F-actin, desmin, vimentin, phosphorylated focal adhesion kinase (pFAK), and yes associated protein (YAP). Among the tested patterns, the 2μm grating emerged as the most effective in inducing a contractile VSMC phenotype. VSMCs cultured on this pattern exhibited reduced proliferation, an elongated spindle-like morphology, and increased expression of muscle-specific proteins, irrespective of PDGF presence. Conversely, VSMCs on the 1.8μm convex microlens and unpatterned substrates showed higher proliferation rates and a diminished contractile phenotype. Remarkably, the beneficial effects of the 2 μm grating pattern were retained when incorporated into a fucoidan-modified polyvinyl alcohol (PVA) hydrogel, a biomaterial known to support EC adhesion and exhibit low thrombogenicity. The 2μm grating suppressed PDGF-induced proliferation while promoting a contractile phenotype and enhancing directional motility. Mechanistic studies revealed elevated pMLCK expression, increased cytoplasmic localization of YAP, and enhanced focal adhesion maturation on 2μm gratings, supporting contractility and reducing proliferation. In contrast, unpatterned and 1.8μm convex lens substrates induced nuclear YAP localization and reduced pMLCK expression, favoring a proliferative phenotype. This study introduces a promising strategy for regulating VSMC behavior through substrate topography, leveraging biophysical cues to promote a contractile phenotype while suppressing proliferation. By incorporating these insights into the design of biomimetic graft surfaces, this approach holds significant potential to address the limitations of sSDVGs, reduce complications such as IH, and improve long-term graft patency. Furthermore, the integration of topographical and biochemical modifications into PVA-based hydrogels represents an innovative avenue for the development of next-generation vascular grafts that combine mechanical strength with enhanced biological functionality. This work paves the way for advancing sSDVGs toward better clinical outcomes, reduced graft failure, and improved patient prognosis.Item Engineering of Electrode-Electrolyte Interphase for High Performance Aqueous Rechargeable Batteries(University of Waterloo, 2025-01-22)The development of advanced aqueous rechargeable batteries is critical for the realization of sustainable, safe, and cost-effective energy storage systems to support renewable energy technologies. However, challenges such as narrow electrochemical stability windows and material degradation limit their practical application potential. To address these issues, this thesis systematically introduces electrode-electrolyte interphases for aqueous lithium-ion, aqueous sodium-ion and aqueous zinc-ion batteries to enhance their electrochemical performance. In the first study, a novel hybrid electrolyte system comprising lithium methanesulfonate-trimethyl phosphate (LiMS-TMP-H2O) was developed to address key limitations of aqueous batteries, including the narrow electrochemical stability window (ESW) and low output voltage. The in-situ formation of lithium phosphate interphases (Li3PO4), derived from TMP, significantly enhances the ESW to approximately 4.5 V, enabling compatibility with a wide range of electrode pair materials. These include LiMn2O4(LMO)/LiTi2(PO4)3 (LTP), LMO/TiO2, LMO/Li4Ti5O12(LTO), LMO/Zn2Nb34O87(ZnNbO), LiCoO2(LCO)/LTO, LiN0.33Co0.33Mn0.33O2(NCM111)/LTO, and LiNi0.5Co0.2Mn0.3O2(NCM523)/LTO. These configurations exhibit high output voltages (up to 2.5 V) and excellent cycling stability, with performance maintained over 1,000 cycles. Notably, this electrolyte design offers an exceptionally low bill of materials (BOM) cost, accounting for only 0.4% of the cost of a 21 m water-in-salt (WIS) electrolyte and approaching the cost of dilute aqueous sulfate electrolytes. These attributes highlight the potential of this electrolyte as a universal and cost-effective solution for the development of high-voltage, long-lifespan aqueous batteries. The second study elucidates the phase transformation mechanism of NaMnO2 and introduces TMP as a multifunctional electrolyte co-solvent for aqueous sodium-ion batteries. TMP not only enhances sodium-ion intercalation/de-intercalation on the cathode side but meanwhile in-situ forms a stable, robust and uniform solid electrolyte interphase on the anode side. These functions lead to batteries with enhanced performance with a high specific capacity of 198.21 mAh/g, an operation time of over 1440h and an energy density of 121.935 Wh/kg and in addition, this co-solvent expands the electrochemical stability window of the electrolyte to around 3.0V and imparts excellent low-temperature performance to the batteries (82.91mAh/g at -20℃), advancing ASIBs as a safe and environmentally friendly energy storage solution. In the third study, the challenges of cathode degradation in Zn/MnO2 batteries are addressed through the development of an artificial Kaolinite-based Cathode-Electrolyte Interphase (K-CEI). This interphase effectively mitigates Mn2+ dissolution and suppresses the formation of Zn-vernadite nanoplates, ensuring stable cathode morphology and improved cyclic stability. The batteries with K-CEI achieve a reversible specific capacity of 380.89 mAh/g over 1,000 cycles and maintain superior performance across various MnO2 phases, providing insights into the design of next-generation long-lifespan aqueous Zn/MnO2 batteries.Item Impact of Hydrogen in a Reheat Furnace in the Steel Industry: a Computational Fluid Dynamics Study(University of Waterloo, 2025-01-22)The steel industry accounts for around 2.8 gigatonnes of CO2 emissions per year. Reheat Furnaces are used in integrated steel mills prior to hot rolling and are a significant source of emissions. The focus of this thesis is on the decarbonization of reheat furnaces in the medium term and has an objective of evaluating the use of hydrogen-methane mixtures as fuel in reheat furnaces using computational fluid dynamics simulations. To do this, first, the numerical models and other settings used are tested on simple single burner cases, and a NOx post-processor was developed. Then, due to the periodically transient nature of the furnace, an iterative procedure was implemented to solve for the furnace load. A Test Furnace was used to validate this methodology by comparison to published simulation results obtained using an alternate methodology. Finally, a reheat furnace based on information provided by Stelco is modeled as a baseline and the use of various fuel mixtures is evaluated. The baseline case yielded an exiting slab average temperature of 1520K, compared to the 1530-1540K expected based on the validation data. A basis of constant heat input to the furnace was used to calculate fuel inputs for a range of cases using hydrogen-methane fuel mixtures. Hydrogen addition was found to lead to an increase in the average slab temperature by up to 55 K and in NOx emissions. It was also found to cause a decrease in the temperature difference across the slab and in CO2 emissions. The change in fuel did not heavily impact the temperature profile of the slab. The impact of hydrogen on the slabs is expected to be easily mitigated by slightly reducing slab residence time or reducing fuel input Further analysis and research on the practical considerations of hydrogen substitution, such as the impact of increased volumetric flow rates and burner material requirements would be essential to determine the extent of work required to retrofit existing furnaces to be able to use hydrogen as a fuel. Additional NOx reduction may be desired as well, with several methods available for consideration. As hydrogen pricing is a major obstacle in the implementation of the fuel substitution considered, a cost analysis is recommended for future work. In the present study, scale formation was neglected, but further modeling of this phenomenon may also be beneficial.Item Enzyme-mediated controlled release of DNA polyplexes from gelatin methacrylate hydrogel for nonviral gene delivery(University of Waterloo, 2025-01-20)Corneal diseases such as recurrent corneal erosion and dry eye disease are common diseases which can significantly interfere with quality of life. The lack of effective treatments for these diseases necessitates the development of novel treatment methods. Skin wounds are another disease area which presents opportunities for improvement of clinical solutions. Gene delivery solutions have gathered interest for both corneal disease treatment and skin wound healing applications. Matrix metalloproteinase 9 (MMP9) enzymes are highly upregulated in both corneal diseases and in chronic skin wounds. Gelatin methacrylate (GelMA) is a biocompatible hydrogel which is degraded in the presence of MMP9 enzyme. It was thus hypothesized that GelMA could serve as an enzyme-responsive controlled release scaffold for polyplexes. The objective of this project was to demonstrate the potential of GelMA hydrogel as an enzyme- responsive controlled release scaffold for chitosan-graft-polyethyleneimine (CS-PEI) polyplexes as a non-viral gene delivery platform to treat corneal diseases or skin wounds. Key criteria of a controlled-release system are tunable release kinetics and maintained bioactivity of the therapeutic molecule after loading and release. The aims of this work were to characterize the release kinetics of the polyplexes and assess the bioactivity of polyplexes released from the GelMA hydrogel system. Methods were developed to quantitate the concentration of the released CS-PEI polyplexes in solution, and the release profile of polyplexes from GelMA in different MMP9 concentrations was measured. The release was found to be sustained over a 5-day period in the presence of physiologically relevant MMP9 concentrations. The in vitro transfection efficiency of released CS-PEI polyplexes was also explored to demonstrate the bioactivity of the polyplexes. The released polyplexes successfully transfected COS-7 cells in an enzyme-responsive and dose- dependent manner.Item Investigation and Enhancement of Zn-Ce Redox Flow Battery Performance Through Experimental and Modeling Studies(University of Waterloo, 2025-01-20)The transformation from energy based on fossil fuels to that based on sustainable options such as wind, solar and hydroelectric sources is crucial to reduce air/water pollution and carbon emissions. However, the production of electricity from these sustainable sources is typically intermittent in nature and can perturb the stability of the existing power grid. Redox flow batteries (RFB) have emerged as promising devices for grid-scale energy storage to stabilize power systems and improve their efficiency. Among the different types of RFBs, zinc- and cerium-based RFBs are promising for large-scale applications that require high output power density due to their low cost and high cell voltage. Motivated by its potential for future applications, this work focuses on the performance improvement of Zn-Ce RFBs through both experimental and modeling studies. Many of the findings and general ideas for RFB performance improvement are also applicable to other RFB systems and to commercial scale RFBs in real-life scenarios. In this work, the effect of different positive supporting electrolytes on the performance of a bench-scale Zn-Ce RFB has been studied. The effectiveness of mixed methanesulfonic/sulfuric acid, mixed methanesulfonic/nitric acid and pure methanesulfonic acid has been assessed and compared. The Ce(III)/Ce(IV) reaction exhibits faster kinetics and the battery exhibits higher coulombic efficiency in the mixed 2 mol/L MSA-0.5 mol/L H2SO4 electrolyte compared to that achieved in the commonly used 4 mol/L MSA electrolyte due to lower H+ crossover and higher Ce(IV) solubility. The rate of the fade in coulombic efficiency in the mixed MSA-H2SO4 electrolyte is 0.55% per cycle over 40 charge-discharge cycles, while the fade rate is 1.26% in the case of 4 mol/L MSA. Furthermore, the positive electrode reaction is no longer the limiting half-cell reaction even at the end of long-term battery charge-discharge operation. The effect of ion crossover on the overall Zn-Ce RFB performance has also been investigated through the measurement of the Zn(II), Ce(III), Ce(IV) and H+ concentrations on both sides of a Nafion 117 membrane during charge-discharge cycles. As much as 36% of the initial Zn(II) ions transfer from the negative to the positive electrolyte and 42.5% of the H+ in the positive electrolyte has crossed over to the negative side after 30 charge-discharge cycles. Both of these phenomena contribute to the steady fade in battery performance over the course of operation. Based on these findings, experiments aimed at reducing the concentration gradient driving crossover by intentionally adding different amounts of Zn(II) to the positive electrolyte at the outset of operation have been conducted. This approach has been shown to reduce the crossover of Zn(II) from the negative side to the positive side, improve both the battery coulombic and voltage efficiencies and reduce the decay of battery performance. Since the ion crossover phenomena is very commonly observed, this strategy to improve battery overall performance and reduce ions crossover by minimizing concentration gradient is not only applicable to similar lab-scale RFB research, but also beneficial for real-life RFB applications. Since the positive electrode reaction becomes the limiting half-cell reaction during the course of battery operation, two strategies have been investigated to regenerate the positive electrolyte by converting the accumulated Ce(IV) ions back to Ce(III) ions. The first strategy which utilizes RuO2 as a catalyst for Ce(IV) reduction improves the voltage efficiency from 71.1% to 77.8% over 16 cycles but reduces the coulombic efficiency from 74.1% to 57.8% due to the leakage of RuO2 catalyst through the porous filter into the positive electrolyte. The method utilizing H2O2 to regenerate the positive electrolyte improves the average coulombic efficiency from 63.7% to 68.3% and the average voltage efficiency from 56.8% to 76.1% over 30 cycles. Similar battery performance and life-cycle improvement can also be expected if these electrolyte regeneration methods are applied on a commercial scale. Furthermore, the implementation of these regeneration methods should also reduce the overall operating costs since it will reduce the frequency with which electrolytes have to be replaced. Finally, a transient 2-D model for the Zn-Ce RFB that accounts for the crossover of different electroactive species through the membrane has been developed. All three modes of transport (migration, diffusion and convection) coupled with electrode kinetics of Zn/Zn(II) and Ce(III)/Ce(IV) redox couples as well as HER and OER side reactions are included in the model. This model has been successfully validated against measurements of the evolution of the cell voltage, negative and positive electrode potentials and ion crossover during the course of 5 charge-discharge carried out in our laboratory. The validated model is then used to simulate the battery behaviour when operated under various operating conditions and using positive electrodes with different geometries. The results obtained provide useful information for the future design of Zn- or Ce-based RFBs with the aim of further improving their performance.Item Advancing sustainable packaging: The role of nanofibers in bioplastics(University of Waterloo, 2025-01-20)In the last few decades, the packaging industry has become one of the fastest-growing industries worldwide, owing to some changes in standards of living, consumption habits, and global trade expansion. Bio-based materials have emerged as one of the most interesting subjects of research in the packaging industry due to the environmental concerns associated with materials derived from petrochemical sources, such as resource depletion, recycling challenges, and biodegradation which have resulted in the development of eco-friendly materials. Polymers are widely used in the packaging industries, and synthetic polymers are extensively employed mainly because of their outstanding mechanical properties, effective barriers against oxygen and water, and ease of processability. However, they present significant downsides, such as poor degradability and challenges in recyclability, and as a result, packaging waste constitutes a large portion of post-consumer solid waste, leading to ecological problems. Therefore, extensive research is being conducted to develop biopolymers in the packaging industry. The challenges associated with the global usage of biopolymers include poor mechanical and barrier properties and high production costs. In order to modify the properties of biopolymers, various methods could be employed, such as reinforcing the polymer matrix with nanomaterials, especially nanofibers. The first goal of this project was to optimize the process of preparing nanofibers derived from hemp. Pre-treatments were applied before the fibers underwent the refining process to reduce the number of steps required for refinement and to investigate their effect on the stability and diameter of the nanofibers produced. This approach not only saves time, energy, and costs but also enhances the overall efficiency of the process, representing a significant step forward for the industry. In this study, mechanical treatment was applied for the fibrillation of hemp fibers. This method has significant advantages over chemical treatment, particularly in terms of reducing the amount of chemicals used. This aligns with one of the most important goals of this project, promoting a more sustainable and cost-effective approach. In order to improve the efficiency of the fibrillation process, several pre-treatments were applied. Among them, the pre-treatment involving fiber hydration by immersing the fiber in water for one hour, subjecting it to a strong vacuum for 30 minutes, and processing it in a pressure cooker at high temperature (≈120°C) and pressure (12 psi) for 10 minutes resulted in the smallest fiber size reduction after eight passes. Furthermore, based on the stability test, this sample exhibited the highest stability, remaining stable after seven days. Another goal of this project was to improve the mechanical and barrier properties of biodegradable nanocomposite films for packaging applications. Polybutylene succinate (PBS) has high flexibility, high elongation at break, good biodegradability, and water resistance. However, due to its low molecular weight, low stiffness, poor oxygen resistance, and high cost, its potential applications are limited. Therefore, one solution could be the addition of hemp nanofibers (HNF) to PBS in order to enhance biodegradation and reduce costs. In this study, nanocomposites of PBS and HNF, with a ratio of 95/5, were first prepared using an extruder and hydraulic press. Their barrier and mechanical properties were then investigated. Then, these properties were compared with the properties of nanocomposites containing PBS/HNF with the addition of beeswax and sodium dodecyl sulfate (SDS) at different ratios. The moisture content, water absorption capacity, and water solubility tests showed that adding beeswax reduced moisture content, water absorption, and water solubility. These effects became more pronounced with increasing amounts of beeswax. Similarly, introducing SDS as a surfactant resulted in a greater decrease in these properties compared to adding beeswax alone, with further reductions observed as the concentration of SDS increased. Furthermore, the results of the water vapor permeability (WVP) test revealed that the incorporation of nanofibers resulted in a decrease in the film permeability due to its hydrophilic nature. However, beeswax created a barrier that hindered the movement of water vapor molecules through the film due to its hydrophobic nature. The extent of this decrease depends on the amount and distribution of the beeswax. When SDS was introduced to the film’s formulation, its bridging effect could further reduce the WVP amounts of films, though only at low SDS concentrations. Overall, the interactions between all components (PBS, hemp nanofiber, beeswax, SDS) can influence the final film structure. Additionally, mechanical tests demonstrated that adding HNF to PBS films increased tensile strength and modulus. However, this led to a decrease in elongation at break. For samples with beeswax in the formulation, the flexibility of the films increased, resulting in an increase in the film's elongation. In terms of tensile strength and tensile modulus, beeswax improved the compatibility between PBS and HNF. This enhancement led to better dispersion of hemp nanofiber within the PBS matrix, resulting in a more uniform composite and improved tensile strength. Meanwhile, the addition of beeswax to the formulation, due to its plasticizing effect, is expected to reduce the tensile modulus. In the final compositions, SDS was added to the film formulation. At low concentrations, SDS behaves as a surfactant, reducing the surface tension between PBS and HNF. This leads to a better dispersion of the nanofibers throughout the PBS matrix, which could reduce stress concentration. Well-dispersed nanofibers create a more uniform stress distribution within the film. This can help prevent premature failure at specific points and allow for more stretching before breaking, potentially increasing elongation. While SDS aids in dispersion at lower concentrations, excess SDS can interact with the surfaces of both PBS and HNF, disrupting the natural interactions (such as hydrogen bonding) between them, which contribute to the overall strength and integrity of the film and their disruption can make the film more susceptible to breaking under stress, potentially leading to decreased elongation. Meanwhile, the initial addition of SDS enhanced the composite's tensile strength mainly because of improved PBS-HNF adhesion and better stress transfer from the polymer matrix to the fibers. The addition of SDS over the optimal concentration resulted in phase separation, which could be regarded as a weak point in the composite, thereby having an adverse effect on the tensile strength. It was observed that by introducing SDS to the formulation tensile modulus also decreased. Overall, the nanocomposites prepared exhibited promising properties for sustainable packaging applications. Nevertheless, additional research and development are essential to improve and optimize the material properties further for optimal performance.Item Design of Self-Aggregating and Recyclable Quasi-Solid-State Electrolyte towards Dendrite-Free Zn Anode(University of Waterloo, 2025-01-07)Zn-based electrochemistries have received ever-increasing attention given their non-toxicity, easy recycling, biocompatibility, and abundant natural resources, which can solve the fundamental challenges of Li-based batteries and make promises in the application of grid-scale energy storage in the future. In particular, Zn-ion batteries coupled with quasi-solid-state electrolytes such as hydrogel electrolytes rather than conventional liquid electrolytes can bring less dendrite formation, thermal runaways, and electrolyte volatilization along with higher energy density. Herein, my current research work reports a gelatin-based hydrogel electrolyte using commercially available Jell-O powder, which is able to regulate the cycling behavior of Zn anodes by inhibiting the growth of Zn dendrite formation. Numerous characterizations and electrochemical techniques prove that gelatin chains can twin into helical structure and self-assemble to form a 3D triple matrix during sol-gel transition, which promotes better electrochemical performance than single molecules. In the meantime, the Jell-O QSSE can promote the binding of anions in the Zn2+ solvation sheath while reducing the content of free anions, thereby decreasing their contribution to the current density and inhibiting the formation of Zn dendrites. The as-assembled Zn//Zn symmetric cells using Jell-O QSSE can sustain long-term cycling of 2000 h, 1500 h, 250 h, and 120 h at 1, 10, 20, and 50 mA cm-2 with an areal capacity of 1 mAh cm-2, respectively. Moreover, Zn//Cu coin cells show excellent reversibility with a high average CE of 98.61% for more than 100 stable cycles. To validate the practicality of Jell-O QSSE, Zn//MnO2 full cells are assembled, showing an ultrahigh capacity retention of 88.7% after 1000 cycles with a high average CE of 99.64%. Different cathode materials such as sodium vanadate (β-Na0.33V2O5, NVO) was applied as well, which similarly show excellent cycling stability and capacity retention, indicating good compatibility of Jell-O QSSE to various cathode materials. Finally, the recycling of used Jell-O QSSE was demonstrated via a suction filtration method. The filtered Jell-O QSSE was applied again in the assembly of Zn//Zn symmetric cells, showing an excellent cycling stability of more than 1200 h, making Jell-O QSSE much more promising than conventional ZnSO4 electrolyte in the application of aqueous Zn-ion batteries.Item Tools for Manipulation of Microbial Communities through Bacterial Conjugation(University of Waterloo, 2025-01-06)Microbial communities are ubiquitous across the planet and play essential roles in numerous aspects of society including human health, agriculture, food production, and biodegradation. Controlled manipulation of natural microbial communities by introduction of biological agents is a promising option for precise, in situ microbiome editing. Bacterial conjugation is a well-studied mechanism for gene exchange (horizontal gene transfer) between bacteria in physical proximity to one another. Conjugation can be repurposed as a gene delivery technique into microbial communities and holds potential for addressing problems of environmental and clinical relevance, including the biodegradation of pollutants such as microplastics and delivery of precision antimicrobials. This thesis begins with a proof-of-concept study in which recombinant DNA is delivered to bacteria in wastewater via conjugation to enable the degradation of polyethylene terephthalate (PET), a major component of global plastic pollution. Using a broad-host-range conjugative plasmid, we enabled expression of FAST-PETase in various bacterial species from municipal wastewater, achieving substantial degradation of both commercial PET film and post-consumer PET products under laboratory conditions. Next, the thesis builds computational tools and methodologies to support model-based design of in situ gene delivery into microbial communities through conjugation. Prior to starting model development, a review of practices for calibrating spatio-temporal models to microscopy data was conducted, which demonstrated the need for a more formal process for generating predictive models. Drawing on practices from ecology, new strategies for systematic model validation were proposed. Some of these strategies were then implemented into a model calibration pipeline based on Pattern-Oriented-Modelling and Bayesian parameter inference, and the pipeline was demonstrated by fitting biophysical parameters in an agent-based model to time-lapse microscopy data. The calibrated model was able to reproduce several patterns in microcolony formation that were observed experimentally, but did not fully replicate patterns associated with colony shape. Finally, a single-cell-based approach to characterizing conjugation in microfluidic environments was developed to investigate spread of the previously developed conjugative plasmid that enabled expression of FAST-PETase. Although the plasmid could spread through conjugation, cells bearing the conjugative plasmid tended to get outcompeted for space by the faster-growinghealthier recipient population. The tendency of cells to self-orient in the direction towards the exit of the microfluidic traps through biomechanical processes also reduced conjugation efficiency. The previously developed model calibration pipeline was then applied to calibrate an agent-based model for conjugation to the microscopy data collected. Afterwards, the calibrated model was used to characterize how initial conditions and spatial factors influenced spread of conjugative plasmids in enclosed microenvironments. Collectively, these studies enhance understanding of engineering microbial communities through conjugation, offering novel solutions for plastic waste degradation and advancing model-based design of gene delivery into microbial communities.Item Modifications of Zein Biopolymer for Material Applications: Biopolymer Blends, Films, Bioactive Delivery Nanoparticles, and Nanofibers(University of Waterloo, 2024-12-19)The need for sustainable and high-performance materials is becoming increasingly urgent as society confronts escalating environmental challenges and pressing healthcare demands. Zein, a protein derived from corn, offers promising potential as a renewable, biodegradable, and biocompatible material for various applications. However, its utility is hindered by intrinsic limitations, such as poor processability, inadequate mechanical properties, and limited thermal stability. This research aims to address these challenges through chemical modifications of zein, blending with complementary polymers, and employing advanced fabrication techniques to develop nanoparticles and nanofibers for targeted applications. The first part of this study focused on chemically modifying zein via esterification using fatty acid chlorides of varying chain lengths (C6, C10, and C16). The findings revealed that fatty acid-modified zein exhibited significantly enhanced hydrophobicity, improved melt processability, and superior tensile properties compared to unmodified zein. The introduction of fatty acid chains also acted as internal plasticizers, facilitating the creation of a melt-processable biopolymer suitable for scalable production. In the second phase, the modified zein (mZein) was blended with poly(butylene adipate-co-terephthalate) (PBAT) via melt extrusion to fabricate biodegradable films. The study explored the effects of varying blending ratios on the compatibility, morphology, and physicomechanical properties of the films. It was observed that the esterification with decanoic acid (C10) significantly enhanced mZein's compatibility with PBAT, enabling the formation of films with balanced mechanical and barrier properties. A composition of mZein/PBAT at 30/70 wt% exhibited optimal performance, achieving a tensile strength of 10.88 MPa, elongation at break of 561.41%, and a modulus of 105.63 MPa. Furthermore, the blend demonstrated superior oxygen barrier properties, reduced water vapor permeability, and improved disintegration rates, making it suitable for food packaging and agricultural applications. The third component of this research examined zein as a biopolymer matrix for nanoencapsulation of bioactive compounds, specifically quercetin and α-tocopherol. Zein nanoparticles (ZNPs) were fabricated using a green antisolvent co-precipitation method, achieving encapsulation efficiency of 96% with particle sizes ranging from 50 to 320 nm. Co-encapsulation of quercetin and α-tocopherol in various formulations revealed distinct release dynamics, with the Zein/Que/Toc (20:1:1) formulation demonstrating controlled release rates over 8 hours. ATR-FTIR and fluorescence spectroscopy highlighted the hydrogen bonding and hydrophobic interactions critical to the encapsulation mechanism. In the final phase, α-tocopherol-encapsulated zein was integrated with polyvinyl alcohol (PVA) to produce nonwoven fiber mats via solution blow spinning. These mats exhibited uniform fiber morphology (diameter: 350–796 nm), excellent mechanical properties, and sustained release of α-tocopherol over 24 hours. Cytotoxicity assessments confirmed high cell viability (>90%) and enhanced cell spreading, suggesting the potential for biomedical applications such as wound dressings. Overall, this research contributes significantly to the fields of biodegradable polymers and bioactive delivery systems. By overcoming the intrinsic limitations of zein through chemical modification and advanced processing techniques, this work offers a scalable framework for the development of high-performance sustainable materials. These findings have broad implications for applications in food packaging, agriculture, pharmaceuticals, nutraceuticals, and biomedical sciences, paving the way for more environmentally friendly and functional material solutions.Item A Reinforcement Learning Framework for Simultaneous Chemical Process Flowsheet Generation, Design and Control(University of Waterloo, 2024-12-12)Integration of process design and control of chemical process flowsheets (CPFs) is a key focus in chemical engineering, receiving extensive research attention. The main objective in this area is to identify optimal process design and control variables for a CPF, ensuring both economic viability and dynamic feasibility of plant operations. This integration presents a complex optimization problem, which is challenging to solve using traditional optimization methods. Additionally, the problem becomes even more intricate when discrete decisions or logical constraints, which give rise to Boolean variables, are considered—common in integrated design and control of CPFs problems. Therefore, the development of new methodologies is needed to effectively address these challenges. The emerging trend in Machine Learning (ML), particularly in Reinforcement Learning (RL), for solving such problems serves as the foundation for this thesis. The limited studies regarding the solution of the integrated problem using RL techniques motivates the exploration and development of novel methodologies. Before addressing the integrated problem, it is important to understand the potential of RL as a tool for solving design and optimization problems of CPFs under steady-state conditions. A RL methodology that introduces two novel RL agents: a discrete masked Proximal Policy Optimization (mPPO) and a hybrid masked Proximal Policy Optimization (mHPPO) has been proposed. In this framework, the agents are capable of autonomously generate, design and optimize CPFs utilizing an inlet flowrate and a set of unit operations (UOs) as initial information. A key feature of this approach is the use of masking – an underexplored yet promising area for solving the present problem – which involves the incorporation of expert knowledge or design rules to exclude certain actions from the agent's decision-making process, enhancing the agent’s performance. Adding to that, this method stands out by seamlessly integrating masked agents with rigorous models of UOs, including advanced thermodynamic and conservation equations, within its simulation environment. The effectiveness of these agents was evaluated through several case studies, including two that utilized commercial simulation suites as part of the RL environment. The resulting CPFs generated by the RL agents present viable flowsheet designs that meet the pre-specified design requirements. Recognizing the potential of RL for designing CPF, this thesis also introduces a novel RL approach for generating, designing, and controlling CPFs. Similar to the previous methodology, the proposed framework generates CPFs directly from an inlet stream, eliminating the need for predefined arrangements of UOs. Furthermore, the framework leverages surrogate models, specifically Neural Networks (NNs), to accelerate the learning process of the RL agent and avoid dependence on mechanistic dynamic models. These surrogate models approximate key process variables and closed-loop performance metrics for complex dynamic UO models. The results obtained using this methodology were compared with model-based optimization results to assess the accuracy and validity of the proposed approach in approximating well-established methodologies. Consistency with the model-based approach was assessed. Additional case studies involved formulations with multiple UOs to further demonstrate the approach’s flexibility to deal with various scenarios. Results from those case studies demonstrate that the RL agent can effectively learn to maintain the dynamic operability of the UOs under disturbances, adhere to equipment design and operational constraints, and generate viable and economically attractive CPFs. The high adaptability offered by the surrogate models enables this methodology to approximate the dynamic behavior of the most common UO. As a result, the proposed framework is sufficiently explicit and flexible to be used in more intricate design and control problems involving multiple UOs.Item Development and Evaluation of Nickel and Cobalt-Based Mixed Metal Oxide Catalysts for Anion Exchange Membrane Water Electrolysis(University of Waterloo, 2024-12-12)Hydrogen production using an Anion exchange membrane (AEM) electrolyzer allows the use of non-platinum group metal (PGM) catalysts for oxygen evolution reaction (OER). Nickel and Cobalt-based oxides are active in an alkaline environment for OER and are relatively inexpensive compared to IrO2 catalysts used in Polymer electrolyte membrane (PEM) electrolysis. This study explores the catalytic performance and stability of nickel and cobalt-based oxides, particularly NiFeOx, NiFe2O4, and NiFeCoOx, in OER and AEM water electrolysis. In the first study, mixed metal oxide catalysts NiFeOx and NiFeCoOx catalysts were synthesized by coprecipitation method using NaOH. The catalysts were characterized through X-ray diffraction (XRD) and scanning electron microscopy (SEM). The NiFeCoOx catalysts demonstrated superior performance in AEM water electrolysis compared to NiFeOx and NiO, achieving the highest current density of 802 mA cm−2 at 2 V and 70°C using 1M KOH as the electrolyte. Electrochemical Impedance Spectroscopy (EIS) and equivalent circuit fitting were used to assess ohmic and activation resistances. Results indicated a reduction in both ohmic and activation resistances with increasing electrolyte concentration. Additionally, the performance of commercially available AEMs, Fumasep FAA-3-50, and Sustainion X-37-50 grade T, was evaluated under similar conditions. EIS results showed that the X-37-50 membrane had lower ohmic resistance compared to the FAA-3-50 membrane. The investigation of catalytic activity and performance of nickel cobalt oxide (NiCoOx) catalysts in AEM water electrolysis for hydrogen production was performed in the second study. The catalysts were synthesized with different ratios of Ni to Co and applied to a nickel foam gas diffusion layer (GDL) at the anode. Scanning electron microscopy (SEM) revealed a distinct flaky structure of the NiCoOx catalyst, while X-ray diffraction (XRD) confirmed the presence of a NiCo2O4 spinel crystal structure. Linear sweep voltammetry (LSV) measurements for the Oxygen Evolution Reaction (OER) in a three-electrode system indicated that NiCoOx (1:3) had the highest catalytic activity, with a current density of 238 mA cm-2 at 1.8 V. Tafel analysis showed that NiCoOx (1:3) had the lowest Tafel slope, indicating faster reaction kinetics and a lower overpotential for higher current densities. Chronoamperometry tests demonstrated the stability of the catalysts at different current densities, with long-term stability testing of NiCoOx (1:3) over 500 hours showing minimal voltage increase during OER, confirming its stability in prolonged operation. NiCoOx (1:3) displayed the highest activity among the tested catalysts at different temperatures, achieving current densities of 1700 mA cm-2 at 2.2 V and 70°C in AEM electrolysis. Nyquist plots and equivalent circuit analysis revealed that NiCoOx (1:3) had lower activation resistance compared to other catalyst compositions for AEM electrolysis. Temperature-dependent measurements showed decreased resistances (ohmic, activation, and membrane) with increasing temperature, indicating improved reaction kinetics and ion conductivity. Long-term durability tests confirmed the stable operation of the catalyst, while short-term tests verified its effectiveness at higher current densities in single-cell AEM electrolyzer operation. In the third study, NiCoOx catalysts were modified using Fe in different proportions ranging from 2.5 to 12.5wt.%. and keeping the Ni to Co ratio to 2:1. Evaluation of the catalytic activity of NiFeCoOx catalysts was conducted by linear sweep voltammetry (LSV) and chronoamperometry (CA) experiments for the oxygen evolution reaction (OER). The catalyst containing 5% Fe exhibited the highest catalytic activity, achieving an overpotential of 228 mV at a current density of 10 mA cm-2, with activity declining with further increases in Fe content. Long-term testing for OER at 50 mA cm-2 demonstrated stable electrolysis operation for 100 hours. Further analysis in an AEM water electrolyzer test revealed that the NiFeCoOx catalyst with 5% Fe at the anode demonstrated the highest current densities of 1516 mA cm−2 and 1620 mA cm−2 at 55°C and 70°C at 2.1 V, with a maximum current density of 1880 mA cm−2 achieved at 2.2 V and 70°C. Nyquist plot analysis of electrolysis at 55°C indicated that the NiFeCoOx catalyst with 5% Fe exhibited lower activation resistance compared to other Fe loadings, suggesting enhanced performance. This study compared the performance of NiFeCo(OH)x and NiFeCoOx catalysts for AEM water electrolysis, revealing that NiFeCoOx demonstrated significantly higher current densities at various temperatures compared to NiFeCo(OH)x. The durability test conducted for 8 hours demonstrated stable AEM water electrolysis with minimal degradation, achieving an overall cell efficiency of 70.5% during operation at a higher current density of 0.8A cm-2. The final study investigated the catalytic activity and performance of NiFeOx catalysts in OER and AEM water electrolyzers. These catalysts were synthesized with varying iron content weight percentages and at the stoichiometric ratio for nickel ferrite (NiFe2O4). The stability of NiFe2O4 catalyst over a 600-hour period at 50 mA cm-2 was demonstrated for OER, with a degradation rate of 15 μV/h. In AEM electrolysis using the X-37 T membrane, NiFe2O4 catalyst exhibited high activity, achieving a current density of 1100 mA cm-2 at 45°C, increasing to 1503 mA cm-2 at 55°C. The performance of various membranes was assessed, with Fumatech FAA-3-50 and FAS-50 membranes showing the highest performance, indicating a strong correlation between membrane performance and conductivity. Analysis of Nyquist plots and equivalent circuit analysis revealed that ohmic resistance decreased with increasing temperature, indicating a positive effect on AEM electrolysis. FAA-3-50 and FAS-50 membranes offered lower activation and ohmic resistances, suggesting higher conductivity and faster membrane charge transfer. NiFe2O4 in an AEM water electrolyzer demonstrated strong stability, with a voltage degradation rate of 0.833 mV/h over a 12-hour durability test.Item Applications of Mathematical Models for Lithium-Ion Battery Management Systems(University of Waterloo, 2024-12-12)Lithium-ion batteries (LIBs) are the most widely used electrochemical storage technology in contemporary electrified vehicles (such as electric vehicles (EVs)), portable consumer products, and renewable energy generation applications. While industries pertaining to LIB manufacturing are now mature, LIB also benefits from enhanced performance in terms of high energy (~300-500 WhrL-1 depending on the battery cell geometry) and power densities, long cycling life (> 1000 cycles), low memory effects, and low discharge rates. The battery cells of LIBs are commercially available in various form factors, including cylindrical, pouch, and prismatic form factors. In the above-mentioned applications, these battery cells are electrically connected in series and parallel combinations to output the desired energy and power requirements. This battery pack in term is connected to the battery management system (BMS) which serves various purposes, including (1) sensing for voltage, current, and temperature, (2) protection against extreme conditions such as excessive currents, under and high voltage limits, etc., (3) interface with the user on useful information such as charge control and range estimation and (4) Battery state estimation for performance management and diagnostics. In this thesis, research works for range estimations, early fault detection, and battery state estimations have been included. Accurate range estimates for EVs are deemed an attractive alternative to conventional internal combustion engines due to their low carbon footprint, low running cost, and higher energy efficiency. However, currently, they suffer from a lower range than conventional vehicles, which induces range anxiety for consumers. First, the EV parameters that strongly impact its range are determined using data-driven techniques. A detailed dataset of commercial EV models manufactured from 2008 to 2021 was collected through web mining. A strong correlation between battery capacity, top speed, curb weight, and acceleration with range was observed. Furthermore, machine learning algorithms were trained and tested on this dataset, with the lowest root-mean-squared error of 19.5 miles. Additionally, a simple linear relationship between the EV range and EV model, battery, and performance parameters was determined to be convenient for EV consumers. Second, the EV system-level vehicle dynamics model and a physics-based battery cell model were utilized to estimate the range for specific vehicles on custom user-specific drive cycles. For this purpose, two types of commercially available battery cells that are utilized in various EV models were selected. While most of the battery cell’s electrochemical parameters from prior literature were used, some of these parameters were estimated using a genetic algorithm (GA). Meanwhile, the vehicle dynamics model was used to determine the battery pack energy and current requirements for various EV models. The drive cycles used in the mentioned model were the highway fuel economy test cycle (HWFET) and urban dynamometer driving schedule (UDDS). These requirements were then inputted into the battery cell models for range estimation. The estimated range was compared to the ranges disclosed by the United States Environmental Protection Agency (EPA). The BMS utilizes the sensor readings from the current, voltage, and temperature readings to estimate the battery diagnostics and ensure user safety. Under extreme conditions, LIBs can undergo thermal runaway leading to battery pack fires and explosions, severely jeopardizing user safety. Hence, early fault detection of an EV battery pack can be a critical asset for EV user safety and battery pack longevity. In this work, an autoencoder was trained and applied to a real-world dataset consisting of 100 EVs. Furthermore, the voltage and temperature time series were compared as input for the fault detection. Temperature-based autoencoder was successfully able to detect a faulty battery pack from normal functioning ones in EVs. Lastly, a process flow of battery pack fault detection, with autoencoder, for large-scale EV applications is discussed. Finally, the last set of research works concerns the state estimations, specifically the state-of-charge (SOC), of LIB. The complex and non-linear electrochemical behavior of the LIBs poses a significant academic and commercial challenge for its state estimations. While cell-level simpler equivalent circuit models (ECM) are commonly used by battery management systems (BMS) hardware, continuum-scale electrochemical models (EM) are attractive due to their higher accuracy, higher fidelity, and ease of integration with thermal and degradation models. However, compared to ECMs, EMs can have higher solution times and their numerical schemes require more extensive mathematical and computational expertise. Various reduced-order EM battery models, specifically the single particle model (SPM), enhanced single particle model (ESPM), reduced order pseudo-two-dimensional (P2D), and their computationally efficient numerical schemes have been proposed in the literature. The computational performance of some of these battery models and solvers has been compared under different programming languages (Python and C++) and computational hardware specifications (hardware specifications representative of embedded, personal computing, and cloud systems). C++ programming language displayed at least a 10-fold reduction in solver and battery model solution times with the exact figure dependent on the cycling steps. Meanwhile, the embedded systems were able to perform the simulations using reduced-order battery solvers and battery models even with the slower-performing Python programming language, making them a reasonable candidate for embedded systems.Item DESIGN OF ONLINE ESTIMATOR FOR CULTURE MONITORING AND MEDIA DEVELOPMENT FOR BORDETELLA PERTUSSIS(University of Waterloo, 2024-09-25)Whooping cough, or pertussis, is a contagious respiratory infection. Sanofi Pasteur’s pertussis vaccine production involves fermentation using reactors of increasing sizes, where cells from each stage inoculate the next. The upstream product undergoes purification to extract the five antigens needed for the acellular vaccine. A major challenge is the variability in antigen yields, particularly for pertactin, which limits overall productivity. Despite controls for parameters like pH, temperature, agitation, aeration, and nutrient feed rates, there’s no real-time monitoring to confirm growth and productivity during the batch run. This often leads to undetected deviations and potential yield losses, making fault detection methods essential for identifying variations and ensuring productivity. The current work deals with the development of a method of bioprocess monitoring using soft sensors for Bordetella pertussis cultures and studying changes in media composition that impact the yield of antigens. Accordingly, the following objectives were pursued: 1) Development of a real time fluorescence-based monitoring system. 2)Investigation of possible sources of oxidative stress and its impact or correlation with antigen production. 3) Development of a protocol for simultaneous monitoring of oxidative stress and antigen produced. 4) Development of a mechanistic model for use in model-based filtering of an online fluorescence based sensor. This thesis presents the design and implementation of an in-line fluorescence spectroscopy system capable of real-time monitoring of critical bioprocess parameters. By utilizing dual excitation wavelength fluorometry, this method was able to track the dynamics of biomass, amino acids, and antigen production throughout the fermentation process. The fluorescence data, combined with statistical technique such as Partial Least Squares (PLS) regression was used for predicting key state variables. A significant enhancement in the predictive accuracy of the PLS models was observed when the models were calibrated for the bacterial strain and the media composition used in each cultivation process. Previous research by our group (Vitelli et al. [2023c], Zavatti et al. [2016]) indicated a potential link between oxidative stress and antigen yield variability, particularly for pertactin. We hypothesized that glutamate, the most abundant carbon source, could be causing this oxidative stress. To test this, we developed a multi-parametric flow cytometry method to simultaneously monitor intracellular ROS and pertactin surface expression. Given that pertactin is an auto-transporter protein, understanding the relation between expression and secretion was crucial. Our findings showed a negative correlation between oxidative stress and pertactin surface expression. Using a tailored protein quantification method via affinity chromatography, combined with multi-color flow cytometry, we confirmed that higher glutamate concentrations induced higher oxidative stress and result in reduced pertactin secretion. The studies inlcuded both batch and fed batch bioreactor experiments where the latter closely emulated the production environment at Sanofi. Hence, the findings demonstrated that variability in initial glutamate concentrations can have a major impact of productivity and may partially explain the variability observed in the manufacturing process. The model from (Vitelli et al. [2023c]) was adapted to formulate a hybrid model that was used for model-based filtering of an online sensor. This mechanistic model incorporated the interactions between glutamate, ROS, and NADPH in neutralizing ROS. After calibration, it accurately predicted key variables under different oxidative stress conditions. In parallel, PLS regression models were developed using in-line fluorescence spectra which could predict OD, glutamate, and NADPH. By using a hybrid model that combines the mechanistic and PLS regression models via an Extended Kalman Filter, more accurate real-time estimates of key variables were obtained. The Akaike Information Criteria (AIC) confirmed that this hybrid model achieved a superior balance between complexity and accuracy as compared to purely mechanistic or PLS models.