Chemical Engineering

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Recovery and Reuse of Nanomaterials from Radically Polymerizable Thermoset Nanocomposites; Towards A Circular Economy
(University of Waterloo, 2026-01-21) Rezaei, Zahra
The widespread adoption of thermoset nanocomposites has created significant end-of-life management challenges due to their permanent crosslinked networks, which resist conventional recycling methods and trap valuable nanomaterials within non-degradable matrices. This work presents a proof-of-concept study to assess a new approach for achieving a circular economy for thermoset nanocomposites; recovering and reusing nanomaterials from thermoset nanocomposites through the incorporation of cleavable comonomers into the polymer matrix, enabling controlled matrix degradation and nanofiller recovery at end-of-life. Carbon nanotubes (CNTs) were selected as the nanofiller for this study due to their widespread use in nanocomposites and growing industrial significance, and a styrene/divinylbenzene (DVB) thermoset matrix was chosen as a model matrix for its chemical compatibility with CNTs. To enable controlled degradation at end-of-life and nanofiller recovery, comonomer additives that can install cleavable bonds into the matrix’s polymer network were systematically evaluated. Several candidates were investigated, including cyclic ketene acetal (CKA) (specifically 2-methylene-1,3-dioxepane, MDO), which underwent hydrolysis too rapidly and an unwanted ring-retaining side reaction for practical application, and thionolactones (specifically dibenzo[c,e]-oxepine-5(7H)-thione, DOT and 2-(isopropylthio)dibenzo[c,e]oxepine-5(7H)-thione, 2SiPrDOT), which was limited by the monomers’ solubility in the styrene/DVB system. Through this careful screening process, 2SiPrDOT was selected as the most suitable option, offering both chemical stability during processing and sufficient solubility in the system. Comprehensive characterization of the primary nanocomposites using thermal gravimetric analysis (TGA), differential scanning calorimetry (DSC), electrical resistivity measurements, and hardness testing confirmed that 2SiPrDOT incorporation did not significantly alter the thermal, electrical, or mechanical properties of the material, preserving the high-performance characteristics essential for practical applications. The thermoset matrix was then deconstructed through nucleophilic degradation, allowing recovery of finely distributed CNTs from the crosslinked network. Analysis of recovered CNTs using energy-dispersive X-ray spectroscopy (EDX), transmission electron microscopy (TEM), and Raman spectroscopy revealed no significant changes in the nanofiller’s structure or surface chemistry, demonstrating the gentle nature of the recovery process. The recovered CNTs (68.7% yield) were subsequently re-embedded into a fresh styrene/divinylbenzene matrix and polymerized. Characterization of these secondary nanocomposites using the same characterization techniques showed properties comparable to the primary nanocomposites, confirming successful retention of nanofiller functionality through the recovery and reuse cycle. This research demonstrates that strategic incorporation of cleavable comonomers into thermoset matrices offers a viable pathway toward circularity for high-performance nanocomposites. By enabling controlled matrix deconstruction while preserving nanomaterial quality, this approach addresses both environmental concerns associated with nanocomposite waste and the economic imperative to reclaim valuable nanomaterials. The demonstrated success with the styrene/DVB system suggests broader applicability of this methodology. As a general radical ring-opening polymerization strategy, this approach has the potential to be extended to other vinyl-based thermosets and diverse nanofillers, offering a promising foundation for developing next-generation recyclable composites across multiple industrial sectors.
Model-Based Optimization of pH and Temperature in Chinese Hamster Ovary Cell Culture
(University of Waterloo, 2026-01-20) Ghodba, Ali
Monoclonal antibodies (mAbs) are widely produced in mammalian cell cultures, with Chinese Hamster Ovary (CHO) cells being the predominant host cell used in the pharmaceutical industry. The growing global demand for mAbs has driven significant advances in biomanufacturing and motivated the pharmaceutical sector to develop strategies that enhance productivity. Among the key factors influencing mAb yield are the operating conditions of CHO cell cultures, such as pH and temperature. Optimizing these parameters is therefore essential for improving process performance and product quality. Model-based optimization offers a powerful and systematic approach for improving complex bioprocesses, including mAb production. Combining mechanistic understanding with mathematical modeling, it enables quantitative prediction of process behavior and identification of optimal operating strategies without excessive experimentation. In essence, model-based optimization relies on two critical components: (1) a dynamic model capable of accurately describing process behavior, and (2) an optimization algorithm that determines the best operating conditions based on model predictions. The effectiveness of a Model-based optimization depends on both components working reliably to ensure convergence toward realistic and true optima. The repetitive nature of batch processes makes them particularly suitable for batch-to-batch optimization, where information from previous runs is used to improve future ones. In this iterative framework, process measurements from a completed batch are used to update the model and compute the optimal input profile for the next experiment. However, optimization of mammalian cell cultures is challenging because of the strong nonlinearities and interactions among growth, metabolism, and product formation under varying environmental conditions. These complexities often lead to model–plant mismatches, so parameters estimated through model identification may not accurately reproduce the true gradients of the cost function or constraints, which are quantities that are essential for optimization. To address this, a modified batch-to-batch optimization, so-called the simultaneous identification and optimization method, is employed. This approach forces the model-predicted gradients to match experimentally measured gradients by adjusting model parameters, while an output correction term ensures that previously achieved fitting accuracy is retained. Consequently, the resulting parameter set satisfies both identification and optimization objectives even when structural model errors are present. Despite its potential, several challenges must be overcome before applying this framework to complex biological systems. Previous studies have computed and corrected gradients only at the end of each batch; however, incorporating transient, within-batch measurements could provide richer information and improve the characterization of model discrepancies. Additionally, integrating optimal experimental design can enhance parameter identifiability and accelerate convergence, and the framework can be further extended to continuous operation modes. Most importantly, the methodology has not yet been thoroughly tested in a real experimental system to demonstrate its performance and robustness. A reliable mechanistic model capable of describing CHO cell metabolism under varying process conditions is also essential but remains insufficiently explored. Two major modeling paradigms exist for bioprocesses: kinetic models and dynamic flux balance analysis (dFBA). Kinetic models employ ordinary differential equations to relate measurable process variables, such as viable cell density, substrate and by-product concentrations, and product titer, to underlying rates of growth, uptake, and synthesis. In contrast, dFBA models optimize a biological objective (e.g., growth rate) with respect to intracellular fluxes subject to stoichiometric and steady-state constraints. Compared to purely kinetic models, dFBA frameworks can offer deeper physiological insight and require fewer parameters, making them particularly attractive for model-based optimization and control. Building upon these concepts, this thesis first presents a novel dFBA model integrated with kinetic constraints to predict the dynamic metabolism of CHO cells under varying pH and temperature conditions in fed-batch cultures. The model captures the main metabolic behaviors across different operating conditions. In the subsequent chapters, the batch-to-batch optimization framework is extended and modified for both batch and continuous bioprocesses, incorporating gradient correction and optimal experiment design to ensure robustness and faster convergence. Finally, the developed methodology is implemented and experimentally validated using an AMBR-15 mini-bioreactor system, where it is applied to determine the optimal pH profile that maximizes monoclonal antibody production in CHO cultures.
Media Optimization of CHO Cell Culture using a Hybrid Dynamic Flux Balance Analysis Model
(University of Waterloo, 2026-01-20) Negahban, Zahra
The manufacturing of pharmaceuticals relies heavily on upstream cell-culture processes that must achieve high, reproducible productivity and quality under tight timelines. Mathematical modeling is an essential tool for bioprocess prediction and optimization. Classical kinetic models provide mechanistic detail but require high parameterization, thus making them prone to overfitting and prediction inaccuracy outside the domain of conditions studied for model calibration. On the other hand, purely data-driven (black-box) models are easy to train but extrapolate poorly due to their lack of physical constraints. This thesis addresses that gap by developing, validating, and experimentally applying a hybrid modeling framework for Chinese hamster ovary (CHO) cell culture that couples dynamic flux balance analysis (dFBA) with partial least squares (PLS) regression models to describe concentration-dependent kinetic constraints. A key challenge in formulating dynamic metabolic models without overfitting is defining a minimal set of parameter-dependent constraints that is sufficient for accurate data fitting. In practice, the dominant drivers of growth and productivity include both abundant extracellular metabolites (e.g., glucose, glutamine) that can be tracked over time and minor components (vitamins, growth factors) that are often unknown due to confidentiality or only known at inoculation and are not routinely measured during the run. Direct optimization over all media components is therefore impractical. This work addresses that limitation by optimizing proportions of commercially available basal media and feeds rather than individual trace constituents. Kinetic bounds embedded in the hybrid model are then expressed as explicit functions of the media proportions, allowing the indirect, but operationally meaningful, optimization of media without time-resolved measurements of each species. Like many empirical and hybrid models, accuracy is strongest near the calibration domain, which can bias an optimizer if the predicted optimum lies outside the data support. To mitigate this, the thesis implements a run-to-run (batch-to-batch) optimization strategy in which each iteration consists of (i) model identification using newly collected data and (ii) model-based optimization to recommend the next experiment. The recommendation is executed, new trajectories are acquired, and parameters are updated for the subsequent iteration, thereby guiding the model and the process toward the true optimum through successive refinements. In this study, the hybrid dFBA–PLS model is integrated with experiments on an Ambr15® microbioreactor platform and enables efficient exploration of the media-blend simplex under consistent operating conditions. The availability of multiple parallel runs allows a design-of-experiments strategy to be layered onto the run-to-run loop, accelerating convergence to high-performing blends while quantifying variability across batches. In particular, the experimental study demonstrates the key importance of matching gradients between experiments and model predictions, an intermediate step in our methodology, to drive the process close to an optimum. Without such matching of gradients, it is shown that the optimization is not meaningful. The overall optimization goal is to improve culture performance by identifying media blend compositions, encoded here by inoculum and feed fractions of commercial media, that maximize monoclonal antibody (mAb) production while maintaining target viability. Systematically varying these fractions tunes both major nutrients and traces in a controlled, scalable manner. Within the hybrid model, a piecewise PLS layer maps measured states (e.g., extracellular concentrations, viable cell density) and media proportions to metabolite uptake/production rates; these rates are transformed into upper–lower kinetic bounds for selected exchange and lumped reactions, which the dFBA layer enforces alongside intracellular stoichiometry and mass balances. In this way, the model links media composition to feasible flux distributions and, in turn, to dynamic trajectories of biomass and mAb. A key novel contribution of the modeling approach is the use of uncertainty bounds for the regression models describing the constraints. It is shown that relaxing or tightening these bounds for the regression models provides several advantages: i- it addresses the multiplicity of solutions of dFBA by limiting the solution space, ii- it reduces overfitting by widening some bounds, thus making them less sensitive to the corresponding constraint, and iii- the relaxation of bounds for a particular constraint reduces sensitivity with respect to this constraint without the need of completely eliminating the constraint that would require expensive mixed integer optimizations. The specific contributions of the thesis are 1. Development of a novel hybrid CHO model that combines a dFBA core with PLS defined, concentration- and media-proportion-dependent kinetic bounds, using a minimal set of tunable uncertainty parameters to avoid overfitting. 2. Implementation and validation of the hybrid model for CHO cultures conducted on Ambr15® cultures under diverse inoculum and feeding formulations, demonstrating the ability to reproduce key metabolic behaviors (e.g., lactate and ammonia dynamics) and product formation profiles. To our knowledge, this is the first CHO model of the dFBA type that explicitly accounts for mixtures of media. 3. Integration of the hybrid model into a run-to-run optimization procedure that recommends next-batch media blends to maximize mAb titer at target viability, using parallel experiments to update parameters, assess variability, and improve recommendations iteratively. This is the first application of the Ambr15® in the context of a run-to-run model-based optimization approach. The application of this methodology led, after 3 iterations, to an almost 30 percent improvement in the value of an objective function consisting of the specific productivity at 80 percent viability. Together, these elements yield practical modeling and model-based optimization frameworks that respect physicochemical constraints, leverage data efficiently, and directly support media-blend design. By expressing kinetic limits as functions of media proportions, the approach enables optimization over both major and minor components without requiring time-resolved measurements of every trace species. Embedding the model in a run-to-run loop further aligns the model to the plant response as the search advances toward the true optimum. The resulting dFBA–PLS methodology provides accurate, interpretable predictions and actionable guidance for upstream process development in CHO cell culture.
Cellulose Nanocrystal Coated Paraffin Wax Coating for Fog and Dew Water Harvesting
(University of Waterloo, 2026-01-16) Yan, Riyao
Fresh water scarcity is an urgent global issue. A sustainable and renewable method is harvesting atmospheric water, among which fog and dew water can be passively collected onto a surface. The efficiency of such collecting systems depends critically on the wetting and dynamic behavior of water droplets on the surface. Common approaches to modify surface topography and hydrophobicity often relies on lithographic, plasma, or fluoropolymer-based methods that are costly, complex, and environmentally unsustainable. In contrast, this work proposes a novel, simple, and bottom-up approach for producing surface with functional coatings through cellulose nanocrystal (CNC)–stabilized Pickering emulsions. The first part of the study focuses on understanding the stabilization and formulation behavior of CNC-based oil-in-water emulsions under varying CNC concentration, ionic strength, and oil-to-water ratios. The resulting interfacial coverage and droplet packing efficiency govern the size and assembly of the wax microparticles, allowing fine control of surface roughness and wettability. Coatings derived from these particles exhibit a wide range of wetting states—from hydrophilic to superhydrophobic—depending on CNC surface coverage and aggregation state. In the second part, these coatings are evaluated for fog and dew water collection, emphasizing the differences between liquid water deposition and humid air condensation on surface. The results show that overall water collection performance is governed by two coupled processes: the rate at which moisture is captured on the surface and the efficiency with which the accumulated water is removed. Previous studies have shown that while superhydrophobic surfaces exhibit superior droplet removal efficiency, their performance can degrade under continuous usage due to partial loss of superhydrophobicity and water film formation. On the other hand, surfaces with balanced nucleation density and drainage efficiency are more desirable, especially for condensation. This research establishes a biobased, PFAS-free, and scalable fabrication route for tailoring surface wettability using CNC-stabilized emulsions. Beyond atmospheric water harvesting, the insights gained here into interfacial assembly and condensation dynamics under realistic humid-air conditions contribute broadly to the design of sustainable coatings for humidity control and anti-fogging/anti-icing applications.
Influence of Cellulose Nanocrystals and Surfactants on Catastrophic Phase Inversion and Stability of Emulsions
(University of Waterloo, 2025-12-22) Kim, Hyungseak
This thesis presents the first quantitative comparison of catastrophic phase inversion in emulsions stabilized by nanocrystalline cellulose (NCC) versus surfactants. NCC extends stability limits, raising the critical aqueous fraction from 0.253 to 0.545. Conversely, surfactants show non-monotonic behavior, delaying inversion at low concentrations and accelerating inversion at high concentrations. These findings demonstrate the effectiveness of NCC in high-internal-phase systems, validating its potential as a robust, bio-based stabilizer for industrial applications.
Electrolytes Design for Metal-based Anode Batteries
(University of Waterloo, 2025-12-16) Ma, Qianyi
Aqueous zinc-metal batteries (AZIBs) promise intrinsically safe, low-cost energy storage, yet their practical deployment is constrained by interfacial instabilities—hydrogen evolution, corrosion, and dendritic growth—especially under high current density, high depth-of-discharge (DOD), and sub-zero temperatures. This thesis develops an electrolyte-centric roadmap that couple’s solvation-structure regulation with interphase chemistry to stabilize Zn plating/stripping across harsh operating regimes. The approach integrates three mutually reinforcing pillars: (i) outer-solvation-shell tailoring to direct desolvation and crystal orientation, (ii) interphase engineering with multifunctional additives to build robust, ion-conductive SEIs, and (iii) radical management to arrest chemistry that triggers corrosion and gas evolution. Multiscale evidence from synchrotron probes, in-situ/operando imaging, depth-profiling spectroscopies, and simulation closes the loop between molecular design and device-level durability. First, I introduce an “outer-solvation-shell” strategy using 2-propanol in Zn(OTf)2/H2O that selectively modifies the second solvation environment of Zn²⁺ while preserving the canonical inner shell Zn(H2O)62+. EXAFS/XANES, wide-angle X-ray scattering, NMR, and molecular dynamics consistently indicate water-dominant inner coordination with 2-propanol and OTf- participating in the outer shell. Density-functional theory combined with 2D grazing-incidence XRD reveals preferential adsorption/desolvation pathways on Zn(101)/(002), enabling oriented, compact deposition with lower nucleation barriers. This manifests as markedly extended symmetric-cell lifetimes (≥3000 h at 1 mA cm-2), stable cycling under heavy load (15 mA cm-2 with ~50% DOD), broadened electrochemical stability, suppressed corrosion/HER, and robust low-temperature operation down to −40 °C. Second, I employ N, S-dual-doped graphene quantum dots (GQDs) as a multifunctional electrolyte/interphase regulator. Their heteroatom sites and surface functionalities coordinate within the solvated layer and at the metal interface to reduce interfacial resistance and homogenize nucleation. Electrochemical analyses (EIS, Coulombic efficiency) and multimodal imaging (in-situ optical/TXM, SEM/FIB-SEM) show dense, void-free deposits and smoother morphology evolution. Depth-profiling (XPS, ToF-SIMS) and diffraction (GIXRD) confirm a ZnF2-rich, mechanically resilient SEI that sustains reversibility under high-rate. Third, I identify hydroxyl radicals (•OH) as direct drivers of interfacial degradation and demonstrate that free-radical scavengers (FRS) effectively suppress radical-induced corrosion and gassing. EPR verifies radical quenching; cryo-TEM and computed laminography visualize mitigated porous by-product layers and reduced “dead-Zn”; line-scan micro-GIXRD tracks crystallographic evolution during plating/stripping. When integrated, the three pillars deliver coin cells with high-rate, long-life operation; Zn∥Zn symmetric cells sustaining up to ~1700+ h at ~45–51% DOD; high-areal-capacity cycling (≥5 mAh cm-2 at 2 C for extended cycles); and 17Ah-class Zn∥V2O5 pouch cells. The chemistry is compatible with scalable manufacturing, including dry-electrode processing using Zn powder anodes. Methodologically, the thesis leverages synchrotron metrologies (VESPERS-GIXRD, HXMA-XAFS, BMIT laminography/TXM), interfacial mechanics (electrochemical-AFM force spectroscopy), and depth-profiling (XPS, ToF-SIMS), complemented by MD/DFT, to establish causality from solvated Zn2+ structure through desolvation kinetics and interfacial reactions to macro-scale durability. Collectively, the results constitute a generalizable design playbook—outer-shell tailoring, interphase engineering, and radical management—that advances fast-charging, low-temperature, and high-DOD AZIBs toward practical, safe, and scalable energy storage.
Development of Functional Binders and Li2S@Carbon Nanocomposites for High-Performance Lithium Sulfide Batteries
(University of Waterloo, 2025-11-20) Huang, Zhe
Lithium sulfide (Li2S) is a promising cathode material for lithium-sulfur batteries (LSBs) owing to its high theoretical capacity (1166 mA h g-1) and potential for safer, scalable battery architectures. In contrast to sulfur cathode, Li2S enables direct pairing with commercial anode materials, avoiding the safety risks of lithium metal. Despite these merits, practical application of Li2S is challenged by its hygroscopic nature, which forms insulating LiOH/Li2O surface layers that cause a large first-charge overpotential; its high melting point (~938 °C), which prevents melt infiltration into carbon frameworks; sluggish redox kinetics; severe polysulfide dissolution; poor conductivity. Addressing these challenges requires integrated advances in binder design, electrode engineering, and cathode nanostructuring. The large first-charge overpotential due to the insulating LiOH/Li2O surface layer in Li2S-LSBs hinders activation and induces irreversible side reactions. Chapter 3 proposes mitigating the activation barrier by exploiting the reaction between polyvinylidene fluoride (PVDF) binder and LiOH/Li2O through dehydrofluorination. The overpotential was successfully reduced from 3.74 V with 30 min slurry grinding to 2.75 V by extending slurry stirring to 48 h. However, PVDF was also found to react with Li2S itself, partially consuming active material and lowering discharge capacity. Overall, this study provides mechanistic insights into the origin of Li2S activation overpotential and demonstrates the dual role of conventional PVDF binders, where slurry processing with PVDF can effectively reduce the first-charge barrier, while also highlighting the limitations of PVDF as a binder for Li2S electrodes. Since PVDF proved unsuitable for Li2S electrodes, Chapter 4 investigates alternative binders capable of enhancing the electrochemical performance of Li2S-LSBs. A binder based on a zinc acetate triethanolamine (Zn(OAc)2·TEA) complex was developed, which not only provides strong polysulfide-trapping ability but also exhibits redox catalytic activity, leading to markedly improved capacity, rate capability, and cycling stability compared with PVDF. To further reinforce electrode integrity and improve dispersion stability, polyethylenimine (PEI) was incorporated to form a Zn(OAc)2·TEA/PEI hybrid binder. Electrochemical testing showed that Li2S cathodes employing Zn(OAc)2·TEA/PEI with 10 wt.% PEI achieved superior rate performance, high discharge capacity, and excellent long-term cycling stability. An additional advantage of these binders is their fluorine-free composition, which aligns with sustainability goals and complying with emerging regulations, including EU restrictions on per- and polyfluoroalkyl substances (PFAS). In Chapter 5, an efficient precursor solution infiltration-decomposition strategy was invented to synthesize Li2S@Carbon nanocomposites under mild conditions, overcoming the challenges of Li2S’s high melting point, poor solubility, and the large particle size of commercial Li2S. In this approach, Li2S was first reacted with carbon disulfide (CS2) in ethanol at ambient temperature to form a highly soluble lithium trithiocarbonate (Li2CS3) precursor, which was readily infiltrated into mesoporous Super P carbon (SP). Subsequent thermal decomposition of Li2CS3@SP at 400 °C produced Li2S@SP-400 nanocomposites with a Li2S:SP mass ratio of 60:40, containing finely dispersed Li2S particles (~11 nm) uniformly confined within the Super P matrix. Electrochemical testing demonstrated that these nanocomposites delivered a high discharge capacity of 821 mA h g-1 (Li2S) at 0.1 C, equivalent to 1190 mA h g-1 (S), and exhibited superior rate capability and cycling stability compared to commercial Li2S, non-infiltrated Li2S nanoparticles, and melt-infiltrated sulfur composites (S@SP). The thermal decomposition of Li2CS3 precursor releases a large amount of CS2 gas (~62 wt.% of the precursor), which creates internal voids and limits the in-pore Li2S loading. To address this, Chapter 6 builds upon precursor infiltration-decomposition method with a multi-cycle strategy, enabling higher Li2S content and in-pore loading. Using mesoporous Super P as the conductive host and Li2CS3 as the precursor, repeated infiltration-decomposition cycles progressively increased the pore filling factor (FF) and in-pore Li2S loading (IPL), from FF = 38% and IPL = 30% for Li2S@SP-1 (one cycle) to FF = 91% and IPL = 73% for Li2S@SP-5 (five cycles), while also raising the overall Li2S content to 70 wt.%. Direct structural evidence from XRD and SEM confirmed reduced crystallite size, suppressed external deposition, and uniform Li2S distribution in the optimized Li2S@SP-5. Electrochemical tests demonstrated that Li2S@SP-5 delivered an initial discharge capacity of 807 mA h g-1 (Li2S) at 0.1 C, 598 mA h g-1 (Li2S) in the first cycle at 1.0 C, and retained 376 mA h g-1 (Li2S) after 500 cycles at 1.0 C. To construct high-performance cathodes, the functional binder from Chapter 4 was combined with the high in-pore loading Li2S@SP from Chapter 6. This attempt failed because Zn(OAc)2·TEA/PEI-based binders exhibited limitations with highly reactive nanoscale Li2S, resulting in diminished binding effectiveness. Chapter 7 therefore introduces a series of polyethylenimine-epoxy resin (PEI-ER) binders, where high-molecular-weight PEI anchors and catalyzes polysulfides while epoxy crosslinking reinforces mechanical stability, making this strategy particularly effective for stabilizing nanoscale Li2S composites. The in-situ crosslinking method further improved processing by removing the short crosslinking time window and enabling uniform networks without altering Li2S@SP morphology. Electrochemical tests showed the optimized in-situ crosslinked PEI-ER1:1 binder achieved 928 mA h g-1 at 0.05 C, 688 mA h g-1 in the first cycle at 0.5 C and retained 325 mA h g-1 after 1000 cycles at 0.5 C with stable Coulombic efficiency. SEM confirmed its compact structure, establishing in-situ PEI-ER crosslinking as a robust binder strategy for nanoscale, high-loading Li2S cathodes. Chapter 8 serves as the culmination of these research projects, combining the optimized Li2S@Carbon cathodes from Chapter 6 and functional binders developed from Chapter 7 with commercial Si/C anodes to successfully assemble and evaluate lithium-anode-free full cells, with PVP used as a baseline comparison, thereby demonstrating their practical feasibility. The in-situ crosslinked PEI-ER1:1-based full cell batteries delivered 670 mA h g-1 at 0.1 C and retained 304 mA h g-1 after 100 cycles (~45% retention), outperforming PVP-based full cell batteries (582 to 250 mA h g-1, ~43%). At 0.5 C, the in-situ crosslinked PEI-ER1:1-based full cell batteries achieved 564 mA h g-1 after activation and maintained 377 mA h g-1 after 500 cycles (66.8% retention), while the PVP counterparts fell from 573 to 176 mA h g-1 (30.7%). These results underscore the binder’s role in stabilizing cathodes and mark the successful assembly of lithium-free-anode Li2S full cells with commercial Si/C anodes. In summary, this thesis addresses the critical challenges of Li2S cathodes, including the large first-charge overpotential, the drawback of PVDF consuming Li2S, the large particle size of commercial Li2S, the high melting point and poor solubility that hinder conventional Li2S@Carbon composite fabrication, and the limitations of binders when applied to nanoscale Li2S, each identified in the process of resolving the preceding issue. By systematically investigating these problems, this thesis advances functional binder design, exploits precursor chemistry, and engineers nanostructured composites, concluding with the successful demonstration of lithium-anode-free full cell batteries. Further improvements could be achieved by employing more efficient carbon hosts with tailored structures, developing high-loading electrodes, integrating solid-state electrolytes to mitigate polysulfide dissolution, and incorporating catalytic components to accelerate Li2S redox kinetics, thereby pushing Li2S-LSBs closer to practical, high-energy-density applications.
Analysis of Heterogeneities in a 20 L Bioreactor
(University of Waterloo, 2025-10-02) Kang, Danny
Biological systems are utilized in various industries to produce valuable products, including biopharmaceuticals. This is done in bioreactors, which are specialized vessels that are able to precisely control key parameters, including agitation, air flow, temperature, pH, dissolved oxygen, and nutrient supply. With the high demands for biopharmaceuticals caused by advancements in medicine, the need for efficient production and optimization of bioreactors has been evident. This has been especially seen during the COVID-19 pandemic, and the high costs of some products, which are inaccessible to many individuals. To optimize production, simulation models have been developed to predict effective control schemes for high growth and product yield. However, this is challenging to translate between lab-scale and industrial-scale due to the formation of gradients in industrial-scale systems, which have poor mixing. Gradients lower the efficiency of bioreactors as cells must constantly adapt to changing extracellular conditions, which cause stress and lower yields. Thus, it is necessary to validate simulation models using the gradients formed in large-scale bioreactors; however, this data is not readily available, and it is difficult to obtain such gradients in smaller-scale bioreactors. In this work, fed-batch experiments are studied to investigate the formation of gradients in dissolved oxygen, kLa, pH, cell density, glucose, and acetate concentrations. This was done through the movement of sensors, turning the air on and off, and the usage of different sampling locations. The objectives of this work were first to characterize the culture with flask and batch experiments and then to use this information to carry out the fed-batch experiments to explore the potential of measuring these gradients. Dynamic metabolic responses were observed and measured depending on the control of the glucose feeding, and consistent gradients were observed for the dissolved oxygen, pH, and kLa, while gradients for cell density, glucose, and acetate were not observed, which may be due to limitations in sampling times. Finally, the metabolic responses have been modeled using modified Monod kinetics, where the modifications include self-growth inhibition, an acetate metabolic switch, and a cell density-dependent lag function. This work was done using a genetic algorithm on Python to optimize parameters, and the model was able to adapt to the different extracellular conditions presented in the fed-batch experiments.
Defining and Validating Convergence Criteria for the Determination of Representative Elementary Volume in Porous Media
(University of Waterloo, 2025-09-23) Fan, Ricky
The representative elementary volume (REV) is a fundamental concept in the study of porous media, describing the minimum volume at which a material property can be considered statistically representative of the whole. Determining an REV is essential for linking pore-scale measurements, often obtained from high-resolution imaging, to continuum-scale models used in engineering and geoscience. In particular, accurate REV identification of porosity and tortuosity is critical, as these parameters govern transport processes such as flow, diffusion, and conductivity in porous structures. This work presents a systematic methodology for identifying REVs based on a threshold criteria designed to reduce computational demands. An REV is defined as the volume in which at least 80% of 100 randomly sampled subdomains yield porosity or tortuosity values within 20% of the overall average. The method was applied to both synthetic datasets and real samples provided by Dong and Blunt, with subdomain volumes ranging from 10^3 to 100^3 voxels [1]. Of the 12 real samples analyzed, 7 satisfied the proposed criteria, and REVs were identified for both porosity and tortuosity. Samples that met the criteria exhibited smaller average pore sizes and higher porosity ratios, while outliers were explained using pore size distribution data. To further assess robustness, predicted tortuosity values obtained using the correlation proposed by Tomadakis and Sotirchos were compared with ground truth measurements [2]. Several samples failed to reproduce the true values, indicating that even when an image contains an REV, it may not be internally self-consistent. While this may appear contradictory, it reflects the distinction between the stability of averaged values across subdomains and predictive accuracy of empirical correlations. The results of this work demonstrate that REVs can be identified from relatively small fractions of the total image volume given that certain conditions are met, offering a balance between accuracy and computational efficiency. This framework provides a flexible approach for porous media characterization, with direct implications for hydrogeology, petroleum recovery, fuel cell design, and filtration technologies.
3D printable fungi-based Chitin nanofiber/CNC hydrogels: implication for fabrication of functional cryogels
(University of Waterloo, 2025-09-15) Ghasemi, Shayan
Fungal-derived chitin nanofibers represent a naturally abundant and renewable material with considerable mechanical strength, making them a promising candidate for advanced material applications. However, their application in 3D printing remains in the early stages of research, as pure fungal chitin hydrogels exhibit poor printability that limits their use in additive manufacturing. In our study, we address this challenge by incorporating cellulose nanocrystals (CNCs) into the chitin-based hydrogels. The addition of CNCs effectively fine-tunes the rheological properties of the chitin-based hydrogels, enabling stable extrusion-based 3D printing while preserving the structural integrity of the material. This approach allowed us to formulate a range of high-fidelity printing inks by hybridizing these bio-based nanomaterials, ultimately creating sustainable aerogels that are ideal for divers applications. Moreover, while CNC aerogels often suffer from insufficient mechanical strength and poor handling characteristics, hybridizing them with chitin nanofibers results in robust, well-structured aerogels. Compression tests confirmed that the mechanical strength of these aerogels is predominantly dictated by chitin network, with CNCs contributing significantly to improved printability and enhanced structural uniformity. To further expand the functional properties of these hybrid aerogels, we incorporated multi-wall carbon nanotubes (MWCNTs) to impart electrical conductivity, thereby enabling their use in electromagnetic interference (EMI) shielding applications. Electrical conductivity measurements demonstrated excellent charge transport capabilities, resulting in a total EMI shielding effectiveness of 34 dB over the X-band frequency range (8–12 GHz). Overall, this study highlights the tremendous potential of fungal-derived, 3D printable chitin aerogels as sustainable, lightweight substrates, offering an eco-friendly alternative to conventional synthetic composites for applications ranging from wound dressings to EMI shielding devices.
Kraft Lignin as a Sustainable Flame Retardant Additive for Polymer Composites
(University of Waterloo, 2025-09-11) Alikiotis, Periklis Dimitrios
Plastic waste is a widespread and continuing issue, including the leaching of toxic additives from microplastics. Lignin is the second most abundant biopolymer, and although previously considered as waste and used as fuel, lignin’s availability and unique properties have garnered popularity as a sustainable and functional additive in many material applications. In this thesis, the versatility of lignin is explored at varying levels of valorization. The first part of this work explored three differing purities of lignin and their effect on the properties of polyvinyl chloride (PVC) composites. These were tested alongside composites with differing concentrations of lignin and were all subject to various thermomechanical and flammability testing. Additionally, the decomposition kinetics of PVC and a lignin-PVC composite were explored. The industrially purified lignin outperformed the other purities mainly in mechanical properties, but the laboratory purified lignin retained the most heat capacity compared to the control. Additionally, at a concentration of 18 wt.% lignin, combustion indices were improved by 50 to 80%, but the elongation at break of these composites were reduced by 38.7%. The second part of this work focused on incorporating a hydrophilic FR (ammonium polyphosphate) into natural rubber (NR), a hydrophobic polymer, by utilizing nano-containers constructed via the crosslinking of lignin. The properties of the lignin nanocontainers (LNCs) were studied to best enhance the dispersion of this filler within the NR at varying concentrations. These composites were tested alongside bulk incorporated lignin & FR as well as foamed samples to best determine the value brought by the LNCs. At a concentration of just 10 wt.% LNC, various flammability parameters improved and outperformed the bulk incorporated sample. This work demonstrated the versatility of lignin to by adding value to polymeric materials without additional modification or being modified to improve its incorporation as a nanomaterial.
Designing Porous Polymer Systems for Water Treatment Applications
(University of Waterloo, 2025-09-11) Crawford, Ethan
Increasing pollution and contamination of the World’s water bodies come with great concern over potable water safety and accessibility. Current solutions for water treatment often have large carbon footprints or are too expensive to scale up effectively. These shortcomings warrant the exploration of new and effective methods of water treatment. Polymer-based solutions offer lightweight, scalable, and inexpensive methods for water filtration while being minimally intrusive to the surrounding environment. In particular, porous polymeric materials have garnered considerable attention due to their high specific surface area, which enables them to have enhanced interactions with their target analyte. This thesis presents two such types of porous materials: nonwoven fabrics and three-dimensional (3D) printed filters. The first section of this thesis focuses on nonwovens, a type of fabric comprised of bonded, interlocking, randomly oriented fibers. Nonwovens can be used as topically placed sorptive mats for the removal of pollutants, or as a pass-through filter for the separation of water from the pollutants. Here, the unique oil gelation properties styrene-ethylene-butylene-styrene (SEBS) block copolymer are leveraged for the creation of melt-blown nonwovens for oil-water separation applications. The poor processability of SEBS, due to its elastomeric nature, was overcome through highly optimized processing parameters to create fine diameter, highly porous nonwoven mats. These mats possessed exceptional lipophilicity and oil-water separation properties due to the oil-soluble midblocks of SEBS that created a semi-solid gel capable of retaining all oil it came into contact with. The latter section of this thesis focuses on 3D printing, specifically fused deposition modelling (FDM), for the creation of flow-through filters for microplastic capture. 3D-printed parts are often very smooth, greatly limiting their surface area and ability for microplastics to become lodged on their surface. To overcome this, a sacrificial additive was added to the base polymer matrix that could be etched out, creating a highly porous surface that greatly improved the filtration efficiency of the printed filters. Pressure-sensitive adhesives (PSAs) were also explored and were found to further bolster the filtration capabilities of the filters. This is due to the added tack and non-covalent interactions that more strongly hold microplastics to the surface of the filters. The findings from these studies demonstrate a promising direction for utilizing porous polymer systems in water treatment applications.
Dry Extraction of Nickel from Mixed-Hydroxide Precipitates via Reduction and Carbonylation
(University of Waterloo, 2025-09-09) Dave, Param
The global transition towards electric vehicles (EVs) has prompted significant research into the sustainable and efficient production of battery-grade materials. Among the critical components of rechargeable batteries, nickel (Ni) is of particular importance due to its central role in cathode materials, specifically for Nickel Manganese Cobalt (NMC) and Nickel Cobalt Aluminum (NCA) batteries. Ni is conventionally extracted from primary sources such as laterite ores (containing 2-3% Ni by mass) through hydrometallurgy (with acid-intensive processing) or pyrometallurgy (with high-temperature, energy-intensive processing). Hydrometallurgical extraction produces an intermediate product called mixed-hydroxide precipitate (MHP), which can contain up to 50% Ni by mass on a dry basis, but still requires further processing to obtain high-purity nickel. This study explores an alternative, sustainable and selective extraction pathway for nickel from MHPs derived from laterite ores and spent battery materials (black mass). The explored vapour metallurgical approach is a two-step, dry process: 1) hydrogen reduction of nickel hydroxides with the MHP to metallic nickel at temperatures between 400°C to 500°C, and 2) selective nickel extraction via carbonylation and conditions of 100°C to 120°C and 150 psig to 450 psig. The carbonylation of metallic Ni using carbon monoxide (CO) produces a volatile molecule called nickel tetracarbonyl (Ni(CO)4), which selectively extracts Ni into the vapour phase. Rigorous safety protocols were employed in this research study to handle the toxic nature of the produced Ni(CO)4 molecules, including CO detectors to identify leaks, and an in-situ decomposition furnace downstream of the reactor to thermally decompose the carbonyls. Reduction and subsequent carbonylation experiments were conducted in a pressurized thermogravimetric analyzer (PTGA), allowing for real-time monitoring of mass changes associated with the reactions. Characterization techniques, including Fourier Transform Infrared (FTIR) spectroscopy, inductively coupled plasma–optical emission spectroscopy (ICP-OES), and Brunauer-Emmett-Teller (BET) analysis, were used to quantify Ni extraction, evaluate morphological changes from fresh samples to reaction residue, and confirm the formation of Ni(CO)4. Significant results demonstrated that the Ni extraction via carbonylation is strongly dependent on the precursor’s structural properties, specifically requiring high surface areas, adequate pore sizes, and minimal cobalt content to enhance transport of CO and Ni(CO)4. Optimal reduction conditions were identified at 450°C, producing residues with a balanced surface area and average pore size, favourable for the carbonylation reaction. Increased carbonylation pressure, at 450 psig, improved Ni extraction efficiency to 95% for a black mass-based MHP.
Nanocellulose from Hemp: Characterization for Molded Pulp Applications
(University of Waterloo, 2025-09-09) Abdul Hadi Bin Jawad, .
The global shift to sustainable packaging solutions has generated growing attention towards biodegradable substitutes for traditional plastic materials. Molded pulp products, originating from lignocellulosic fibers, are both biodegradable and recyclable; however, they frequently demonstrate inadequate mechanical strength and moisture resistance, which restricts their use in high-performance packaging applications. This study explores the capabilities of cellulose nanofibers (CNF) as a reinforcing additive to enhance the characteristics of molded pulp. CNF was generated from multiple hemp-derived sources through Masuko grinding at varying pass levels and characterized using centrifugation-based techniques, such as water retention value (WRV) and settling volume, to assess their degree of fibrillation and dispersion. TEM analysis validated the findings from the centrifugation-based techniques, confirming that the trends noted in settling volume and WRV correspond to fibrillation quality at the nanoscale. Among the samples evaluated, Dry Anka Bast processed at 12 passes exhibited exceptional dispersion characteristics and was chosen for further application. CNF was integrated into molded pulp of four types: softwood, hardwood, thermo-mechanical eucalyptus pulp (TMP), and kraft eucalyptus pulp. Mechanical testing was performed to evaluate the impact of CNF incorporation on tensile strength and structural integrity. The findings indicated that CNF markedly improved the mechanical properties of molded pulp, especially in both softwood and hardwood samples, where there was a notable increase in tensile strength. Tensile strength increased from 4 MPa to 13 MPa in hardwood pulp, from 4 MPa to 18 Mpa in softwood pulp, from 3 MPa to 14 MPa in Kraft Eucalyptus pulp, and from 1 MPa to 3 MPa in TMP Eucalypts. The findings validate the enhancing capabilities of CNF and emphasize the significance of the CNF source and processing conditions in maximizing the performance of molded pulp. The results of this study contribute to the development of efficient, bio-based packaging solutions and support wider initiatives aimed at minimizing plastic waste via sustainable material innovation.
Interfacial Behaviors of Polymer and Metal-Polymer Thin Films under Contact and Solvent Stimuli
(University of Waterloo, 2025-09-04) Fan, Zhao
Polymeric thin films and metal-polymer bilayers are foundational components in flexible electronics, adaptive surfaces, and emerging interface technologies, valued for their mechanical compliance, ease of processing, and tunable functionality. Unlike homogeneous rigid or bulk elastic materials, polymer thin films exhibit inherently display scale-dependent mechanical and optical properties, particularly at interfaces, where deformation behavior is governed by factors such as film thickness, cross-link density, and free liquid content, often resulting in nonlinear and time-dependent viscoelastic phenomena. The integration of nanoscale metallic coatings introduces an additional layer of complexity: the rigid-soft coupling further alters both mechanical and optical properties, giving rise to hybrid contact behaviors that go beyond the assumptions of classical contact theories developed for either purely stiff or bulk soft materials. Moreover, the interfacial deformations are typically confined to micro- or even nanometer scales, where stress localization, modulus gradients, and geometric confinement jointly govern the contact behaviors and its evolution. This multiscale, multiphysics coupling presents significant challenges for experimental characterization. Most conventional techniques isolate mechanical and optical measurements, rely on model-specific assumptions, and involve multi-step or complicated procedures. Thus, these techniques present certain challenges in precisely characterizing the real micro-scale structural properties and deformation behavior under actual loading or environmental conditions. Despite growing interest in these bilayer systems, a clear, experimentally accessible framework for quantitatively probing their contact behaviors and underlying properties remains lacking. Addressing this gap is essential not only for advancing the fundamental understanding of thin film mechanics, but also for enabling the rational design of high performance, multifunctional soft interfaces for next generation technologies. To address this gap, this dissertation applies spectroscopy and microscopy techniques: confocal Raman spectroscopy and dual-wavelength reflection interference contrast microscopy (DW-RICM), to systematically investigate the interfacial behaviors of polymeric and metal-polymer bilayer thin films under contact and solvent stimuli. The resulting insights aim to inform the rational design of multifunctional soft interfaces with enhanced performance and broader applicability in next generation surface and device technologies. The dissertation first highlights a parameter independent framework for characterizing soft contact deformation using in-situ confocal Raman spectroscopy. To achieve this, a calibration platform was constructed using a five-glass sphere probe assembly, with a glass slide placed on top to establish a reliable measurement protocol. This setup was then adapted for soft contact analysis by replacing the upper glass slide with a PDMS coated glass slide (P10), enabling localized deformation under controlled spherical contact. Raman mapping was performed in three spatial dimensions by tracking the intensity distribution of the 2905 cm⁻¹ Raman peak, which serves as the -CH3 stretching of PDMS. The resulting contour maps enabled imaging of the deformation region across multiple planes, allowing the extraction of physical parameters such as contact radius and indentation depth. The obtained results were broadly consistent with Hertz predictions, while revealing local deviations indicative of non-conformal contact behavior. The proposed technique and framework offers a unique method to observe the formation and change of contact deformation, leading to a deeper insight into the soft contact system. Building upon this molecular insight, a methodology was developed to simultaneously extract the optical and mechanical properties of polymer and metal-polymer bilayer thin films using dual-wavelength reflection interference contrast microscopy (DW-RICM). Nanoscale gold (Au) and silver (Ag) layers were deposited on PDMS substrates with varying elasticity and coating thickness. By analyzing interference patterns obtained at two wavelengths (488 nm and 561 nm) during contact with a glass probe of known geometry, the effective refractive indices and elastic modulus of the bilayer system were quantitatively determined. The refractive index was found to decrease with increasing metal deposition time, decreasing PDMS elasticity and increasing coating thickness, consistent with UV/Vis spectroscopy measurement. Elastic moduli were derived using Hertz theory based on the measured contact radii. This integrated optical-mechanical approach simplifies current multi-step characterization procedures, offering insights into fundamental properties of the metal-polymer bilayers. To further investigate the metal thin layer coating on the contact behavior of metal-polymer bilayers, a black-ink-coated probe was incorporated with DW-RICM to suppress unwanted reflections at the probe-air interface. This modified configuration enabled visualization of deformation features including contact deformation region and contact ridge formation with nanoscale resolution. Experimental results show that increasing the metal deposition time (i.e., metal coating thickness) leads to a reduction in both contact radius and contact ridge height. Moreover, long-term contact analysis of the gold coated bilayers showed a steady increase in ridge height over time, unlike the gradual decrease observed in the bare counterparts until reaching a steady state, suggesting altered interfacial viscoelastic behavior driven by the presence of the metal coating layer. Building on insights into the role of free liquids in thin film contact behavior, the final phase of this dissertation investigates out-of-equilibrium interfacial mechanic of solvent-induced surface instabilities on solid supported soft substrates using DW-RICM. The morphological evolution of PDMS and silicone gel substrates were monitored over prolonged hexane extraction and drying. A consistent transition was observed from shallow circular depressions to highly ordered triradial (Y-shaped) surface patterns driven by internal stress accumulation and elastic modulus gradients between the surface and bulk. Comparative analysis across formulations with varying crosslinking densities revealed that while the pattern formation mechanism is broadly conserved, it remains sensitive to material properties such as free liquid content and elasticity. These findings shed light on the mechanisms of solvent-mediated patterning and underscore solvent processing as a promising strategy for engineering programmable surface architectures in soft materials. Overall, this dissertation constructs a framework for soft interface characterization, integrating mechanical deformation under contact and surface morphological transformation under solvent extraction. The findings highlight how vibrational spectroscopy and optical interferometry can be used in tandem to probe complex contact phenomena, offering new tools and insights for the design of adaptive, compliant surfaces in applications such as soft robotics, flexible electronics, and interfacial patterning.
Facile SEI Improvement in the Artificial Graphite/LFP Li-ion System: via NaPF6 and KPF6 Electrolyte Additives
(University of Waterloo, 2025-09-03) Rahbariasl, Sepehr
Lithium-ion batteries (LIBs) are the most widely used energy storage technologies for grid-scale applications, electric cars, and portable devices because of their consistent voltage profiles, high energy density, and extended cycle life. However, interfacial degradation events, especially at the anode, frequently restrict their long-term performance. The creation of the solid electrolyte interphase (SEI) layer, a passivation film that occurs on the graphite anode surface during the initial cycles, is one of the most important issues in this context. Increased impedance, irreversible capacity loss, and decreased coulombic efficiency are caused by unstable or excessive SEI production, which is necessary for stabilizing the electrode–electrolyte interface. These issues are made worse by fast charging or prolonged cycling. This thesis uses artificial graphite anodes and lithium iron phosphate (LFP) cathodes to examine the effects of sodium hexafluorophosphate (NaPF₆) and potassium hexafluorophosphate (KPF₆) additives on SEI properties and electrochemical performance in LIBs. These alkali salt additives, which are rarely investigated in lithium-ion systems, are being investigated as scalable and affordable substitutes for traditional SEI-modifying additives. The effects of the additives were evaluated by electrochemical testing, which included galvanostatic cycling, cyclic voltammetry (CV), and electrochemical impedance spectroscopy (EIS), as well as surface and structural characterization (SEM and XPS). According to our results, using KPF₆ and NaPF₆ considerably lowers irreversible capacity loss (by 38.98% and 37.85%, respectively) as compared to a baseline LiPF₆ electrolyte. Additionally, full cell tests show enhanced capacity retention without adversely altering ionic conductivity, with 67.39% for NaPF₆ and 30.43% for KPF₆ across 20 cycles. High-conductivity electrodes used for SEI generation at 1C further validated the additives' capacity to continue functioning during faster formation. These results provide new perspectives on mixed-ion SEI engineering and show how promising NaPF₆ and KPF₆ are for improving LIB performance in demanding applications like electric vehicles.
Chitosan/SIFSIX-3-Cu Cryogels on Printed Laser-Induced Graphene for CO2 Electric Swing Capture
(University of Waterloo, 2025-08-26) Ho, Monica
To achieve global net zero greenhouse gas emissions, carbon dioxide (CO2) removal technologies (CDR) must be deployed at gigatonne scale by the end of the decade. Direct air capture (DAC) is one category of CDR technology which shows promise due to its more straightforward measurability and verifiability. Low temperature, solid sorbent-based DAC systems in particular offer a lower energy demand and when paired with renewable electrical systems, avoid the use of fossil fuels and the generation of additional CO2 emissions in the process. Several sorbents have been investigated for electric swing adsorption (ESA) DAC, where heat generated using the Joule heating principle is used for the desorption of CO2 from the sorbent. Most of the sorbents are carbonaceous due to their semi-conductive nature which allows for electrical current travel. However, these sorbents suffer from reduced capacity at low CO2 partial pressures, making them less suitable for DAC. As an alternative, we explore an indirect ESA process using laser-induced graphene (LIG) which acts as a flexible heater layer. For the adsorbent layer, chitosan (CS) cryogel with in situ synthesized SIFSIX-3-Cu metal organic framework (MOF) is fabricated for its high capacity, appreciable CO2 selectivity, and sustainability. The pure MOF powder reached its maximum adsorption capacity of approximately 2.5 mmol g⁻¹ within just five minutes, demonstrating its exceptionally fast adsorption kinetics. In contrast, the pure chitosan (CS) cryogel required more than 30 minutes to reach the same capacity. The CS/MOF hybrid cryogel exhibited intermediate kinetics, achieving a maximum adsorption capacity of 2.92 mmol g⁻¹. It was shown that the adsorbents could be regenerated in temperature range of 70-80°C, had low N2 uptake, and 88% of the CS/MOF cryogel capacity was maintained after 4 cycles. Patterned LIG grids were subsequently fabricated and could raise the temperature of the CS/MOF cryogel adsorbent via Joule heating to the target regeneration temperature in 66 s with only 15 V. The LIG grid could also consistently generate the desired temperature range over 4 cycles. Lastly, the chitosan cryogel was fabricated directly on a LIG grid without compromising its heating capability. This successfully demonstrates how an environmentally conscious and efficient ESA system can be engineered by combining LIG optimized for heating and eco-friendly adsorbents with high CO2 capacity.
A CRISPR-Cas9 and next-generation sequencing approach for late/very late AcMNPV gene disruption and comprehensive mutation analysis
(University of Waterloo, 2025-08-26) Chakraborty, Madhuja
The recent global pandemic COVID-19 has taught us the importance of an efficient biologics manufacturing platform that is cost-effective, reliable, and has high product yield and quality. The baculovirus expression vector system (BEVS) has proven to be a promising platform for the production of recombinant proteins, vaccines, virus-like particles (VLPs), viral vectors, and/or other biologics. In the last two decades, many vaccines and therapeutics manufactured using BEVS have received licenses for animal and human use. The majority of the commercially available BEVS transfer plasmids have foreign genes under the viral polyhedrin (polh) or p10 promoters. Although high gene expression can be achieved with the endogenous baculovirus promoters p10 and polh, they are only active very late in the infection cycle when most of the host cellular machinery is turned off. Significant work has been done to identify native promoters and other regulatory elements with expression profiles higher than polh, as well as promoters weaker than polh to express secretory proteins that require extensive post-translational modifications (PTMs). Certain regions, such as polh, chiA, and v-cath, in the baculovirus genome are not essential for their in vitro replication or foreign protein production in cell culture. Thus, it is possible that if there is an expression of genes not required for progeny virus and/or exogenous protein production in insect cell culture, the resources that are being used for their expression could be ‘an additional burden’, resulting in unnecessary depletion of cellular resources. Identifying and removing these genes would probably divert resources towards the production of foreign proteins and progeny viruses, which could improve the BEVS production platform. Moreover, it was previously demonstrated that there is a ‘competition effect’ among protein-coding genes for cellular resources when Sf9 cells are either coinfected with two monocistronic recombinant baculovirus expression vectors (rBEVs) or infected with a dual-protein producing polycistronic rBEV. This work could point to a direction where competition can arise among baculovirus genes for the use of cellular resources, and the knockout of unnecessary genes could presumably lead to appropriate usage of the resources by the essential genes. Separately, the co-production of rBEVs and recombinant protein products in the supernatant complicates the downstream purification process. Disruption of genes essential for virion formation or production could prevent baculovirus contamination in the culture supernatant, thus reducing the burden on purification processes. In the past, gene disruption or downregulation has been a fruitful strategy to improve the expression of foreign genes in the BEVS. However, the traditional methods used for mutant baculovirus genome generation are time-consuming, labor-intensive, and sometimes also produce wild-type viruses, hence requiring additional purification steps. Not until recently has CRISPR-Cas9 gene editing technology been adapted to the Sf9 insect cells and the baculovirus Autographa californica multiple nucleopolyhedrovirus (AcMNPV). It is believed to be an effective tool to scrutinize baculovirus genes by targeted gene disruption and transcription repression. A systematic study of the late and very late AcMNPV genes using a CRISPR-Cas9-based transfection-infection assay (T-I assay), disrupting the unnecessary sequences, and expressing exogenous gene(s) under a late promoter instead of very late promoters could extend the production time and improve biologics production. Moreover, in the final production stage, targeting AcMNPV genes that are required for progeny virus assembly or release but do not affect foreign protein production could minimize rBEV co-production. In this study, the T-I assay was used to probe late and very late AcMNPV genes for their essentiality. Based on the effect of individual gene disruptions on foreign protein (green fluorescent protein (GFP)) and budded virus (BV) production, 38 targeted AcMNPV genes were categorized as essential (reduced both GFP and BV production) and of special interest (reduced GFP production but did not lower BV production). While we identified 19 AcMNPV genes that are essential for BV production and GFP expression from the late p6.9 promoter, 19 other genes were identified as of special interest whose disruption only reduced GFP expression from the late p6.9 promoter. While phenotypic changes were assessed using the CRISPR-Cas9-based T-I assay, investigating the genomes using whole-genome next-generation sequencing (NGS) revealed further information. First of all, shotgun sequencing was used to generate a consensus sequence of the p6.9GFP rBEV stock used in T-I assays, and this is the first report on whole-genome rBEV sequences to the best of our knowledge. This shotgun-sequenced rBEV served as the reference genome to identify mutations upon CRISPR-Cas9-mediated gene disruptions. We also provided a set of tiled-amplicon primers based on the reference genome and adapted a high-throughput tiled-amplicon sequencing assay to control and targeted rBEV genomes. This sequencing assay, combined with a bioinformatics pipeline for major species, was able to successfully detect mutations within the gp64 gene when gp64 targeting sgRNA was delivered to Sf9-Cas9 cells via a plasmid or rBEV. We further demonstrated that gp64 disruption lowered BV levels without decreasing GFP production, thus reducing BV contamination in cell culture supernatant. To probe the gp64 gene further, we targeted it at six different locations using the T-I assay. Plasmids carrying one or two sgRNA targets were used to evaluate the impact of single and multiple targeting sites on virion and foreign protein production. gp64 disruption with each of these sgRNA targets resulted in decreased infectious and total viral titers, whereas GFP production from the late p6.9 promoter was enhanced or remained similar to the control. Low-frequency genomic changes upon CRISPR-Cas9-mediated gp64 disruptions were successfully assessed by the tiled-amplicon sequencing assay and a variant calling pipeline based on the computational tool iVar. While the iVar tool was originally developed to investigate variants in wild-type virus populations, we adapted it to detect variants in a process system. We also demonstrated that variants can be preserved over viral propagation in cell culture, that is, variants present in the virus stock were also observed in the rBEV genomes recovered from the T-I assay, thus indicating that they are not detrimental to viral fitness.
Analysis of integrated heating approaches for cold-start conditions in 21700 lithium-ion battery modules using thermal system simulation
(University of Waterloo, 2025-08-25) Parra Panchi, Grace Stephanie
Cold ambient conditions significantly reduce discharge capacity and slow the thermal response of lithium-ion cells, particularly at low state of charge (SOC). To address these challenges, this research studies the feasibility of heating strategies to improve cold-start performance in 21700 lithium-ion battery modules using thermal system simulation. Both experimental and simulation-based approaches were employed. At the cell level, experimental tests were conducted to evaluate thermal and capacity behavior under sub-zero temperatures. These results were compared against thermal system simulation simulations under convective or adiabatic conditions, revealing that experimental test setups introduce additional resistances not captured in idealized models. And adiabatic conditions could allow faster cell heating compared to convective conditions due to internal heat accumulation, which shows the effect of insulation. In fact, the temperature rise simulated under adiabatic conditions is approximately 2.3 to 2.9 times greater than under simulated convective conditions. Building on these findings, a module design was developed to enable system-level simulation of thermal strategies. The design considered safety, structural integrity, and thermal performance, balancing insulation with heat flow pathways. Then the study focuses on evaluating the feasibility of external and battery-powered heating strategies. Four heating configurations were simulated, external heating, battery discharge, or combined configurations. Simulations were carried out across below zero ambient temperatures of -20 °C, -10 °C, and 0 °C and different initial SOC values of 80%, 50% and 20%. Results show that in the absence of heating, the battery was unable to complete discharge at low SOC, particularly at -20 °C and 20% initial SOC. Yet when external surface heating was applied, the module achieved a faster temperature rise enabling full discharge even under these extreme conditions. Furthermore, when external heating is applied without discharge, the heating rate slows down, highlighting the added benefit of internal heat generation during battery operation. Lastly, the study evaluated whether the battery could power its own heating system. At 20% SOC and -20 °C, the energy required for heating exceeded the battery’s usable output, rendering self-heating unfeasible. In contrast, at 0 °C and moderate SOC levels, it remained viable, with heating demands as low as 2 to 3% of the available capacity. Overall, the findings support the integration of targeted heating strategies into electric vehicle (EV) thermal management systems, showing that a combination of external heating and internal heat generation enables reliable cold-start performance while minimizing energy consumption for battery heating in sub-zero conditions.
Design and Assessment of Membrane-supported Ammonia Cracking for Hydrogen Refuelling Stations
(University of Waterloo, 2025-08-25) Smyth, Emily
As Canada aims to reduce greenhouse gas emissions, there is a growing shift toward cleaner energy and fuel sources. Hydrogen has emerged as a promising alternative fuel source due to its high gravimetric energy density and ability to power fuel cell electric vehicles without producing direct carbon dioxide emissions. However, there are currently challenges in storing and transporting large amounts of hydrogen. Ammonia is gaining attention as a hydrogen carrier because it can be stored under moderate pressure or refrigeration and leverages existing infrastructure. Once delivered, hydrogen can be extracted from ammonia through on-site decomposition and purification. Although this pathway shows promise, its competitiveness depends on the system's energy requirements, operating costs and emissions. Furthermore, most existing ammonia decomposition and hydrogen refuelling models are proprietary, limiting accessibility for researchers and small-scale developers. This thesis addresses this gap by developing an open-source process model for a palladium membrane supported ammonia decomposition process at hydrogen refuelling stations. The process delivers 500 kg of hydrogen gas at 350 bar per day, and its cost and emissions performance were compared to other hydrogen production pathways. A Python-based model was created using Cantera, a chemical kinetic and thermodynamic library, to simulate the isothermal Pd membrane reactor. In the reactor, ammonia decomposes to nitrogen and hydrogen, while hydrogen is separated using the membrane. This eliminates the need for additional hydrogen purification steps. The base case achieved 99.92% conversion and 95.9% hydrogen recovery. To preheat the ammonia feedstock to the membrane reactor, the unconverted ammonia and unrecovered hydrogen were mixed with some ammonia feedstock and combusted with air. The combustion generates NOx emissions, which were reduced by 85% using a selective catalytic reduction unit, bringing NOx emissions well below provincial limits. While the system has no direct carbon dioxide emissions, indirect emissions from electricity consumption, ammonia feed and transportation for the process were estimated at 4.86 kg CO₂e/kg H₂, with an electricity requirement of 9.77 kWh/kg H₂. An economic analysis shows a capital expenditure of approximately $204,000 and an annual operating cost of $1.6 million for the base case. The levelized cost of hydrogen (LCOH) at 350 bar was estimated at $10.38 kg/H2. A sensitivity analysis was also conducted to evaluate the impact of temperature, pressure and membrane permeance on conversion, hydrogen recovery, NOx emissions, and LCOH. The impact of capital and operating expenditure on LCOH was also analyzed, with the price of ammonia being the main contributor to changes in LCOH. These results from a detailed study of the ammonia to hydrogen pathways contribute to a better understanding of clean hydrogen technologies for transportation applications and also provide key insights for future deployment in clean fuel strategies across Ontario and beyond.

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