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About MacSphere

MacSphere is McMaster University's Institutional Repository (IR). The purpose of an IR is to bring together all of a University's research under one umbrella, with an aim to preserve and provide access to that research. The research and scholarly output included in MacSphere has been selected and deposited by the individual university departments and centres on campus.

To contribute to McMaster's Institutional Repository, please sign on to MacSphere with your MAC ID.

If you have any questions, please contact the MacSphere Support Team.

Students wishing to deposit their PhD or Masters thesis, please follow the instructions outlined by the School of Graduate Studies.

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Recent Submissions

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    MOLECULAR CATALYSIS FOR ELECTROCHEMICAL NITRATE CONVERSION TO AMMONIA
    (2026) Noor,Navid
    Electrochemical reduction of nitrate (NO3⁻) to ammonia (NH3) offers a pathway to decentralized nitrogen cycle remediation and sustainable NH3 synthesis. This thesis advances the application of molecular catalysts in electrochemical NO3⁻ reduction to NH3 by elucidating how active site coordination and the local atomic environment govern activity, selectivity, and stability. Across three manuscripts, (i) the impact of second shell coordination on metal-N4 macrocycles beyond first-shell electronics was established (ii) the active phase identity and degradation pathways of Fe- and Cu-based phthalocyanine/porphyrin catalysts under cathodic potentials were resolved, (iii) Design challenges of dual site molecular catalysts were identified using CuPc and FePc, and (IV) the impact of electronic properties and catalyst wettability on the performance of molecular catalysts in NO3- reduction using a series of functionalized FePc-R/CNTs was decoupled. Methodologically, in situ X-ray absorption spectroscopy was integrated with post-mortem microscopy/diffraction, density-functional theory, and coupled mass-transport/reaction modeling, and electrochemical evaluation was performed to identify performance descriptors in molecular catalysts. New discoveries include: (1) metal identity and second shell (porphyrin vs phthalocyanine) in molecular catalysts impacts the stability and activity (2) revealing peripheral substituents affect electronic properties and wettability and that electronic trends are frequently masked, or amplified, by local hydrophobicity, (3) a tandem Fe-Cu design paradigm, translated from molecular insights, that identify key challenges in dual site catalysts designs and key factors playing a role in obtaining synergy between the active sites. The major emphasis of the thesis is that coordination chemistry and local environment co-determine selectivity in an eight-electron nitrate reduction reaction, and that operando-validated molecular models can provide transferable rules for scalable architectures. The contributions to knowledge are actionable: design principles linking Hammett-type substituent metrics and wettability to NO3- reduction kinetics; operando criteria to validate active-phase identity; and a blueprint for dual site catalysis that bridges molecular precision with device-relevant performance.
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    Double Exponential Cubature Kalman Filtering: Theory and Applications
    (2026) Butler, Quade
    Gaussian filtering supports many estimation tasks, yet real systems present nonlinearity, outliers, and model mismatch. This thesis advances the methodology and practice of such filters in two parts. First, it develops the Double Exponential Cubature Kalman Filter (DECKF), which evaluates Gaussian-weighted moments using a double exponential cubature rule with positive weights and a scalable point set. The analysis clarifies accuracy and stability as the number of cubature points grows, observes positive-definiteness behavior in the prediction and update steps, and provides tuning guidance that accommodates cubature point count, process and measurement covariances, and numerical conditioning. An additional robust correction strategy, the Double Exponential Sliding Innovation Filter (DE-SIF), constrains the measurement update within a sliding boundary layer to limit the influence of abnormal innovations while preserving the standard Kalman structure and compatibility. Second, the thesis studies performance in a demanding condition monitoring problem. The DECKF is combined with an interacting multiple model framework and is compared against the EKF and UKF on a mode-switching magnetorheological damper governed by Bouc-Wen dynamics. The study quantifies force-estimation accuracy, correlation with reference force, detection performance across operating modes, and statistical consistency via normalized innovations and related tests. Results show that the IMM-DECKF delivers strong force tracking and consistent innovations with competitive detection performance, and that its benefits grow with careful cubature point selection and covariance tuning. Beyond the specific damper experiment, the proposed DE cubature rule and sliding innovation strategy apply to broader estimation tasks where Gaussian filters are standard, including target tracking, navigation, and control, and offer practical guidance on stability, tuning, and diagnostics.
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    Decentralized and Intelligent Estimation: Theory and Applications
    (2026) Alsadi, Naseem; Gadsden, S. Andrew; Mechanical Engineering
    Contemporary technological development has had a profound impact on the architecture and operation of modern systems. In particular, smart systems, defined by their capacity for adaptation, have emerged as a dominant paradigm across various sectors. This dissertation presents two complementary surveys that establish the conceptual foundation for the technical contributions that follow. The first is a comprehensive examination of smart system architectures, framed through the lens of cognitive dynamic systems, which decomposes smart systems into five core components: control, perception, knowledge, communication, and security. The second is a focused survey on Intelligent Estimation, which explores the intersection of estimation theory and learning-based systems. Motivated by the increasing reliance on secure and distributed inference, the first technical contribution introduces Decentralized Estimation (DeEst), a novel data-driven decentralized estimation framework that integrates data-driven local inference with blockchain-based federated consensus. In DeEst, each node maintains a local estimator informed by historical observations and contributes parameter updates to a shared global model via a blockchain-federated learning protocol. This architecture eliminates the need for a central aggregator while ensuring robustness to communication failures, malicious nodes, and node data heterogeneity. The second contribution focuses on estimator robustness at the node level through the development of the Sliding Sigmoid Filter (SSF), an extension of the Sliding Innovation Filter (SIF). By incorporating a nonlinear sigmoid-based saturation function, the SSF enables smoother transitions across innovation magnitudes, improving estimation stability in the presence of abrupt deviations or measurement outliers. The SSF’s capacity to modulate updates adaptively makes it particularly well-suited for decentralized implementations, where maintaining local estimator reliability in the face of system faults is essential to ensuring system-wide accuracy. The final contribution presents a novel learning paradigm, referred to as Intelligent Estimation, which reinterprets neural network training as a probabilistic filtering problem. In contrast to conventional gradient-based optimizers such as SGD or Adam, which often suffer from poor convergence in noisy settings, Intelligent Estimation employs estimation methods, such as the SSF, to adaptively scale weight updates based on innovation magnitudes, enabling context-aware and noise-resilient learning. The approach is empirically validated across diverse benchmark datasets, demonstrating improvements in both convergence behavior and generalization performance.
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    Horizon-scanning brief: Health-system innovations for British Columbia
    (2022-08) Wilson MG; Bhuiya AR; DeMaio P; Lavis JN
    Insights from key-informant interviews, evidence documents and the experiences of jurisdictions in Canada and internationally that help explain why a particular topic related to the issue of health-system innovations for British Columbia may warrant attention. This brief was designed to inform horizon-scanning panel deliberations.