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    Powder Bed Fusion of Difficult-to-Print Ni-Based Superalloys: Microstructural Evolution and Cracking Behavior
    (University of Waterloo, 2026-06-26) Aghajani, Hamidreza
    IN738 is a precipitation-strengthened nickel-based superalloy that is widely valued in industry due to its excellent creep resistance and good corrosion performance. However, it exhibits poor manufacturability, primarily due to its complex alloy chemistry and the challenges associated with solidification during processing. In this study, a mechanistic process–microstructure–cracking relationship was first established for LPBF-processed IN738LC. It was observed that melt pool geometry plays a critical role in crack formation, with an optimal width-to-depth ratio governing crack susceptibility. Reducing hatch spacing or increasing laser power resulted in grain coarsening, with the effect being more pronounced for hatch spacing reduction. Nevertheless, crack density was significantly reduced with decreasing hatch spacing, which is attributed to improved part densification and a more favorable melt pool geometry. The as-built microstructure was found to be highly non-equilibrium due to the rapid cooling rates inherent to LPBF. It consisted of a γ matrix with cellular/dendritic solidification substructures, submicron carbides located at interdendritic regions, and dispersed oxide particles with Al-rich cores. No γ′ precipitates were detected in the as-built condition. Elemental segregation and oxide formation, combined with thermal stresses, contributed to reduced ductility and promoted crack initiation during processing. In the second stage of the study, heat treatment was employed to develop a high-temperature-capable microstructure, particularly aiming for a controlled distribution and size of γ′ precipitates with spherical, cuboidal, and irregular morphologies. A series of heat treatments with varying solutionizing (S) and ageing (A) temperatures were performed to promote crack healing and to develop an optimized microstructure, particularly γ′ precipitates with desirable size, distribution, and morphology for high-temperature applications. The heat treatment conditions mainly included solutionizing at different temperatures (S), solutionizing followed by low-temperature ageing at 845 °C (SLA), solutionizing followed by high-temperature ageing at 1120 °C (SHA), solutionizing followed by double-ageing at high and low temperatures (SDA), and the industry-recommended standard heat treatment for this material (ST: S1120-A845). It was observed that high-temperature solutionizing promotes a more homogeneous microstructure, whereas at lower temperatures (around or below 1120 °C), homogenization is only partial. It was observed that varying the solutionizing and ageing conditions led to the development of diverse γ′ precipitate size distributions, ranging from unimodal to bimodal and multimodal. Unimodal distributions were dominated by fine secondary γ′ precipitates, while multimodal structures consisted of fine secondary γ′ in conjunction with coarse primary γ′. It was further demonstrated that high-temperature ageing (≈1120 °C) facilitates γ′ coarsening. In contrast, low-temperature ageing (≈850 °C) stabilizes the secondary γ′, resulting in a fine, well-defined, and coherent γ′ distribution within the γ matrix. In addition to γ′ precipitation, other secondary phases were identified. Carbide precipitates, including those enriched in alloying elements such as Ti, were predominantly located along grain boundaries. Moreover, Cr-rich phases were observed to preferentially form at grain boundaries. These Cr-rich precipitates were shown to develop during low-temperature ageing (≈850 °C) and may contribute to the degradation of tensile properties. Solutionizing was identified as the primary factor governing recrystallization. At elevated temperatures, the microstructure underwent full recrystallization, resulting in pronounced grain coarsening. In contrast, at lower temperatures (e.g., ~1120 °C), the grain structure remained largely similar to the as-built condition with minor modifications. Additionally, crack healing was observed at higher solutionizing temperatures and was directly associated with the recrystallization of the material. A solid-state crack healing mechanism was proposed, whereby the high-energy state of the as-built microstructure—characterized by cracks, free surfaces, and high grain boundary density—provides a strong thermodynamic driving force for energy reduction. Upon heating above a critical temperature, this driving force promotes recrystallization and crack closure, leading to a more stable microstructure. In the subsequent phase, mechanical performance was systematically evaluated through room-temperature tensile testing of both as-built and heat-treated samples. Tensile tests at room temperature were performed along the vertical direction (i.e., loading direction parallel to the build direction). The as-built condition exhibited the lowest yield strength, while the standard heat-treated sample showed the highest. Overall, the tensile properties at room temperature were found to be governed by a combination of factors, including dislocation density, LAGB structures, grain size, γ′ precipitation (precipitation strengthening), anisotropy, residual cracking, crack healing, recrystallization, grain coarsening, and the presence of detrimental grain boundary phases. In the as-built state, the relatively lower strength and higher ductility were primarily attributed to strengthening mechanisms dominated by high dislocation density and low-angle grain boundary (LAGB) networks. The superior strength of the standard heat-treated sample in the vertical direction resulted from the synergistic effect of γ′ precipitation strengthening and the retained as-built microstructural characteristics (e.g., columnar grain structure and high LAGB density). In the other heat-treated conditions, strengthening was mainly controlled by γ′ precipitation together with crack healing during high-temperature solution treatment. The higher yield strength of the SLA sample relative to the other highly solutionized conditions was primarily attributed to the finer γ′ precipitates and reduced interparticle spacing. Furthermore, Cr-rich grain boundary phases formed during ageing at 845 °C contributed to intergranular embrittlement and fracture, which was confirmed by EDS analysis. This was consistent with the lower ductility and reduced UTS values observed in the SLA and SDA conditions relative to the SHA condition. The modified heat treatment strategies developed in this study produced a crack-free and nearly isotropic microstructure while providing improved room-temperature mechanical properties compared with the as-built condition. The combination of recrystallization and complete crack healing highlights their potential for high-temperature service, making these heat treatment routes promising alternatives to the conventional industrial heat treatment. In another case study, CM247LC, a non-weldable Ni-base superalloy, was fabricated by electron beam powder bed fusion (EB-PBF) at a wide range of energy levels. For this purpose, variable process parameters were adjusted to investigate their effect on microstructure and crack formation. Samples fabricated at both low and high area energies exhibited pronounced crack susceptibility. At very low energy densities, lack of fusion (LoF) and porosities were observed, while higher energy densities produced denser samples. Adjustments to energy density and process parameters resulted in a grain structure transition from fine-columnar to coarse-columnar and near-single crystal morphologies. Despite these changes, the cracking issue persisted, with micro-cracks observed in low-energy samples and macro-scale cracks, several millimeters long, forming at higher energy densities, highlighting the material’s high sensitivity to crack formation. Both solidification and liquation cracking were identified— the former showing dendritic crack surfaces, and the latter associated with eutectic phases and grain boundary precipitates. Severe recrystallization around cracks was observed at high energy densities, characterized by elevated dislocation densities. EDS analysis revealed hafnium- and silicon-rich precipitates in interdendritic regions and near cracks, contributing to severe hot cracking in the material.
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    Deployment Concerns in Machine Learning Systems: Unintended Interactions and Accountability
    (University of Waterloo, 2026-06-26) Duddu, Vasisht
    Machine learning (ML) models are increasingly being deployed for client-facing services (e.g., chatbots, search engines, and browsers), high-stakes decision-making applications (e.g., healthcare and criminal justice), and as part of larger systems (e.g., autonomous vehicles and operating systems). However, to deploy ML models for a particular application, practitioners need to address various deployment concerns including (i) infrastructure issues (e.g., latency, throughput, interoperability, scalability), (ii) model design (e.g., high utility and generalization, minimal overfitting, hyperparameter tuning, data processing), (iii) environmental impact (e.g., reducing carbon emissions, water and power consumption by data centers), (iv) adversarial and societal risks (e.g., security, privacy, safety, unfairness, poor transparency, misalignment, misinformation, and cyberattacks), and (v) enabling governance (e.g., verifying claims by practitioners, and regulatory compliance). I focus on two deployment concerns: adversarial and societal risks, and enabling governance, and address unintended interactions and accountability within these respective concerns. I present them as two parts of the thesis. (Part-1) Unintended Interactions in ML: Substantial prior work explores the design of defenses against individual risks to security, privacy, fairness, transparency, and safety. I argue that this is not sufficient for real-world ML models that must protect against multiple risks simultaneously. Practitioners need to address additional challenges that emerge when doing so, including unintended interactions. A systematic understanding of such interactions is lacking, and I study three unintended interactions: (a) a defense against one risk may increase or decrease other unrelated risks; (b) conflicts among defenses can decrease their effectiveness when combined; and (c) potential for collusion among adversaries can enable executing an attack to amplify others. I propose frameworks to identify factors underlying such interactions, and present guidelines to conjecture about unexplored ones. (Part-2) Accountability in ML Pipelines: Practitioners' claims about executing various ML operations needs verification by a verifier (e.g., regulator). This includes demonstrating ML properties covering the model, its training process, its training data, as well as deploying defenses and accounting for unintended interactions from Part-1. Such claims are currently communicated via ML property cards (e.g., model, data, and inference cards). I propose ML property attestation mechanisms that allow provers (e.g., model trainers) to demonstrate ML properties to verifiers, while ensuring model and data confidentiality. I show that existing software-based mechanisms are either inefficient (e.g., cryptographic mechanism), or ineffective and easily evaded (e.g., ML-based mechanism). I then identify hardware-based mechanisms using trusted execution environments as an efficient and effective alternative for providing ML property attestations. These attestations can then be used for verifiable ML property cards, to ensure accountability for practitioners' claims.
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    Cognitive and Epigenetic Predictors of Healthcare Utilization in the Canadian Longitudinal Study on Aging: Factor- and Indicator-level Examinations
    (University of Waterloo, 2026-06-25) Wang, Elizabeth
    Background: Healthcare utilization among older adults is a valuable indicator of health status and provides a mechanism linking illness to healthcare costs. Cognitive function and epigenetic age—as indicators of nervous system and cellular integrity at a biological level—are both correlated with age and may be important predictors of healthcare utilization. It is unclear how strongly the two predictor categories are associated, however, and it is not known whether they are best understood as correlated processes under a general “systemic resilience” (SR) construct, or as separate factors with independent influence on healthcare utilization. In the present research study, I examine indicator-level and factor-level predictors of healthcare utilization, with a focus on cognition and epigenetics. In doing so, the factor-level and indicator-level associations with healthcare utilization are evaluated, with an eye toward testing the validity of a superordinate SR construct. Objectives and hypotheses: This study examined the factor structure of SR as a higher-order construct, encompassing epigenetic age and cognitive function. It compared factor-level associations with healthcare utilization (emergency department [ED] visits and hospitalizations) to those observed at the indicator-level, while evaluating age and sex as potential moderators. A priori hypotheses were that a higher-order model would best fit the data, the associations would be stronger for women (vs. men) and older (vs. middle-aged) adults, and significant pathways would emerge at both the factor and indicator levels. Methods: Data were drawn from the Canadian Longitudinal Study on Aging (CLSA) Comprehensive Cohort (n=30,097; age range=45-85 at enrolment), focusing on the subsample who completed epigenetic assays (n=1,478). Structural equation modelling (SEM) was used to evaluate competing structural configurations and predict healthcare utilization. Age and sex moderation were examined using multi-group analysis. Logistic regressions were used to examine indicator-level associations. Results: A correlated two-factor model representing epigenetic age and cognitive function as distinct but related constructs, rather than as components of a higher-order SR model or a single unified factor was selected as the most appropriate model based on fit indices and parsimony. Cognitive function emerged as a predictor of hospitalizations at the factor-level (b -0.254; 95% CI; -0.461, -0.046). Supplemental analyses suggested no significant sex moderation, while evidence for age moderation was inconclusive. At the indicator-level, analyses suggested the mental alternation test (MAT) and intrinsic epigenetic age acceleration (IEAA) were reliable predictors of ED visits. Similarly, the animal fluency test (AFT) was a predictor of hospitalizations. Conclusions: Cognitive function and epigenetic age may be best considered as correlated, but fundamentally independent processes in older adults. Among factor-level predictors of healthcare utilization outcomes, cognitive function was reliable but not epigenetic age. At the indicator level, mental flexibility and cell-intrinsic aging were predictive of select facets of healthcare utilization. These findings suggest that both cognitive and epigenetic markers have some value in predicting future healthcare costs among older adults, but that systemic resilience may be less useful at the whole organism level.
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    Engineering Development and Signal Processing Advancements in OCT Angiography: From Custom System Integration to Temporal Domain Denoising
    (University of Waterloo, 2026-06-24) Perez Paredes, Andrei Felipe
    Optical Coherence Tomography Angiography (OCTA) positions itself as a highly effective, non-invasive technique that provides depth-resolved visualization of vascular structure and function. With a continuously emerging need to transition from static angiography to functional, time-resolved imaging, researchers have identified interconnected challenges. This thesis fundamentally explores two of these challenges: speckle noise and processing latency. Typically, spatial filters used to suppress speckle and denoise images are computationally expensive and act as temporal low-pass filters, destroying the dynamic physiological signals they intend to isolate. This thesis presents the design, implementation, and in vivo validation of a streaming-compatible swept-source OCTA (SS-OCTA) architecture relying on a hardware/software co-design to overcome these limitations. Rather than relying on isolated downstream algorithms, the system described in this research establishes a validated quality baseline starting at the hardware level. The custom 1060 nm MEMS-VCSEL SS-OCT platform developed in this thesis, leverages an adaptive software flyback filter to assess fast-axis position derivatives, actively isolating and discarding corrupted scans prior to contrast processing. Building upon this stationary signal foundation, the thesis introduces Temporal Subband Decomposition and Amplification (TSDA). TSDA operates as a dual-rate infinite impulse response (IIR) filter along the per-pixel temporal axis, decomposing the signal into structural, flow, and high frequency speckle bands. This continuous formulation reduces computational complexity to O(1), bypassing the buffering requirements of discrete Fourier methods and aiming to isolate physiologically driven flow from coherent noise. The integrated hardware/software stack was validated against a microfluidic phantom and an in vivo 14-day-old chorioallantoic membrane (CAM) preparation. An ablation study reported here confirms the TSDA architecture achieves a processing latency within the 10 ms budget. Furthermore, the complete pipeline delivered a Peak Signal-to-Noise Ratio (PSNR) of 27.8 dB against a multi-frame average reference, while yielding statistically significant improvements in Vessel Contrast-to-Noise Ratio (VCNR). By replacing spatial averaging with targeted temporal band isolation, the integrated platform extracts OCTA contrast while preserving the temporal flow signal within the filter passband.
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    Huge Operators in Holography: BPS Sectors, Matrix Models, and Black Holes
    (University of Waterloo, 2026-06-24) Murali, Harish
    This thesis explores quantum gravity by studying large-N gauge theories and matrix models. In particular, it focuses on operators whose charges scale as N^2, which we dub huge operators, so that they are heavy enough to backreact on the dual bulk geometry. In the first part, we study protected sectors of N = 4 super Yang-Mills theory, where supersymmetry gives enough control to ask finite-N questions beyond the planar limit. We analyze huge 1/2-BPS operators and show that their exact combinatorics reorganizes, at large N, into matrix models and integrable HCIZ fluid flows. We also study the 1/16-BPS sector relevant for supersymmetric black holes, emphasizing the role of finite-N trace relations and analytic continuation in the number of colors. In the second part, we turn to simpler matrix models as laboratories for holographic ideas such as universality, and commutativity. We show that huge deformations can produce universal eigenvalue densities in strong-coupling regimes, and we clarify the role of fermions in ensuring commutativity at strong coupling. Together, these results give concrete boundary descriptions of backreacted geometries, finite-N effects, and strong coupling dynamics.