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Developing Advanced All-solid-state Lithium Organic Batteries
No full textAll-solid-state batteries (ASSBs) have attracted significant attention in recent years due to their enhanced safety, high energy density, and long-term stability compared to conventional liquid electrolyte-based systems. Meanwhile, organic batteries, which utilize redox-active organic compounds as electrode materials, offer additional advantages such as structural tunability, sustainability, and the potential for low-cost, large-scale production. However, their practical application has long been limited by the dissolution of organic materials in liquid electrolytes, leading to rapid capacity fading and poor cycle life. By replacing liquid electrolytes with solid-state electrolytes, this dissolution issue can be fundamentally mitigated, enabling more stable electrochemical performance of organic electrodes. In recent years, the development of all-solid-state lithium organic batteries (ASSLOBs) combining organic active materials with inorganic solid-state electrolytes has emerged as a highly promising direction. These systems not only retain the environmental and structural advantages of organic batteries but also benefit from the mechanical robustness and electrochemical stability of solid electrolytes.
This thesis begins with an in-depth review of the development of lithium-ion batteries, with particular attention to the evolution of electrode materials and electrolyte systems. The first section traces the development in the field, highlighting key progress in both cathode and anode materials, as well as innovations in liquid electrolyte formulation and optimization. The discussion then turns to organic electrode materials, which have attracted growing interest due to their structural tunability, environmental compatibility, and potential for low-cost production. However, their practical deployment remains limited by issues such as poor cycle life and dissolution in liquid electrolytes. To address these challenges, the latter part of the thesis explores the development of solid-state electrolytes, which not only offer improved safety and thermal stability but also effectively suppress the dissolution of organic active materials. Recent progress in integrating inorganic solid-state electrolytes with organic electrodes is examined, revealing a promising pathway that leverages the strengths of both components.
First, compared to oxide solid electrolytes and sulfide solid electrolytes, halide solid electrolytes have attracted increasing attention due to their wider electrochemical stability windows. The first work investigates the compatibility between the organic cathode material indigo and halide-based solid electrolytes. The results demonstrate that, for organic positive electrode materials, the selection of solid-state electrolytes cannot rely solely on the electrochemical stability window of electrolytes. Instead, the interfacial compatibility and specific interactions between the electrolyte and the electrode material must also be carefully considered to ensure stable electrochemical performance.
Second, a bifunctional indigo natural dye was investigated that serves as both an active material and a solid molecular catalyst in sulfide-based ASSBs, addressing these compatibility challenges. Contrary to the prevailing view that chemical reactions between OEMs and sulfide SEs are detrimental, our study reveals that controlled reactions between indigo and Li6PS5Cl (LPSC) SE catalyze their synergistic redox process after optimizing electrode microstructures. This strategy enables a high reversible capacity of 583 mAh g-1 (LPSC contribution: 379 mAh g-1) at 0.1 C, a high areal capacity of 3.84 mAh cm-2, and excellent cycling stability at room temperature. These findings highlight the potential of bifunctional OEMs in sulfide-based ASSBs to overcome the key challenges of OEMs in practical applications.
Subsequently, this work underscores the critical importance of chemical compatibility in achieving optimal battery performance, demonstrating that carefully regulated interfacial reactions between organic electrode materials and sulfide solid electrolytes can catalyze reversible S²⁻ anionic redox processes. This catalytic mechanism enables a high electrode-level energy density of 476.6 Wh kg-1 and stable cycling over 2,000 cycles at room temperature in all-solid-state organic batteries. Mechanistic investigations into the OEM-catalyzed S²⁻ redox chemistry reveal two essential criteria for effective catalysis: (1) the redox potential of the OEM must be appropriately aligned to oxidize S²⁻ species without inducing over-oxidation, and (2) low cation–S²⁻ bond covalency is necessary to localize electron density on sulfur atoms, thereby facilitating reversible redox activity. These insights address key limitations associated with OEMs in all ASSBs and offer a strategic framework for designing next-generation sustainable ASSBs with enhanced energy density and long-term stability
This thesis investigates the development of all-solid-state lithium organic batteries by exploring the interplay between organic electrode materials and solid-state electrolytes. It highlights the critical role of chemical and interfacial compatibility—beyond electrochemical stability windows—in achieving high energy density and long-term cycling stability.
Keywords: organic electrode materials, electrolytes, all solid-state batteries, sulfide solid state electrolytes, carbonyl electrode materials, redox mediato
W8banakiak Guides, Intergenerational Transmission, and Cultural Resilience: Experiencing Land and Knowledge in Odanak
No full textThis dissertation stems from collaborative research between the W8banaki Nation and
me, presenting the relationship between land and knowledge through the guiding
experiences of W8banakiak elders.
The thesis draws on oral history interviews that invited W8banaki narrators to share their
memories and thoughts on fishing, hunting, their relationship to their elders, their
relationship to the land, their experiences of guiding in private clubs, their relationships
with club members, and the ways knowledge of the land and Indigenous culture was
transmitted to them. At the heart of this study lie ten solo interviews and two group
interviews conducted between 2021 and 2024. The Ndakina Office generously gave me
access to seven oral history solo interviews with W8banakiak elders they had recorded in
2021. To this, I conducted and recorded 3 solo interviews and two groups interviews. The
interviews I recorded were with W8banakiak elders, their relatives, Ndakina Land
Guardians and members of the Ndakina Office, where we spoke about guiding history
and its meaning for the W8banaki Nation.
Adopting decolonial paradigms and collaborative research methodologies, this project
illustrates the continuation of W8banaki knowledge and wisdom of the land through the
intergenerational transmission of knowledge that demonstrates cultural resilience against
colonial and capitalistic pressures. Oral history interviews, collaboration and sharing
authority is embedded into this project’s throughout its various steps, where narrators and
collaborators were invited and welcomed to reflect on its content and methodology from
start to finish. Although guiding is no longer practiced in Odanak’s community, the elders
and their relatives interviewed detail the fond memories of times spent in the woods
while connecting to the land. This research leads me to affirm that the perpetuation of
intergenerational knowledge transmission of the land, transcending colonial pressures and
imperial territorial administrations, contributed to a sense of community, belonging and
cultural resilience amongst the W8banaki Nation
Mathematical Decomposition Techniques for Resource Allocation in Optical and 5G Networks
No full textTelecommunication companies use software with heuristic algorithms to plan their routing. However, with network demands increasing at such a rapid pace, the effectiveness of these heuristics becomes a critical issue.
Therefore, our research focuses on designing large-scale optimization models and algorithms for solving provisioning problems in 5G networks. Our works can be categorized into two main topics: provisioning problems at the physical layer and provisioning problems at the logical layer.
The first topic of the thesis focuses on the Routing and Spectrum Assignment (RSA) problem and is structured into three parts. In the first part, we propose a new decomposition exact modeling of the RSA problem, based on a link decomposition, in order to further improve the scalability of previous exact methods. Solution requires a column generation (CG) algorithm, a powerful decomposition technique, to derive proven epsilon-optimal solutions, with small epsilon values.
The second part presents a decomposition model that still aimed at maximizing throughput in the RSA problem, but subject to additional interference (also called. Optical Signal-to-Noise Ratio (OSNR)) constraints using the Gaussian Noise (GN) model. It is built upon the link-based decomposition model from the first part. The solution combines a Tabu Search (TS) to handle non-linear components within a Column Generation algorithm.
In the third part, we address the limitations observed in the second part, specifically the suboptimal solution of subproblems resulting from using TS. To overcome this, we propose a reformulation of the subproblems as Maximum Weight Independent Set (MWIS) problems to more effectively handle the non-linearities, and improve on both the scalability and the accuracy of the solutions.
The second topic addresses the challenge of ensuring protection for Service Function Chaining (SFC) requests in an Open Radio Access Network (O-RAN). We investigate two protection schemes (dedicated vs. shared) and two distinct objective functions (availability vs. latency), which both require handling non-linearities in an efficient manner in order to remain with scalable exact solution schemes
To What Extent Have the Mandates of Transportation Agencies Been Improved Regarding the Consideration of Biodiversity? An International Comparison
No full textTransportation infrastructure, particularly road networks, have significantly contributed to the social and economic development of many countries. However, roads also negatively impact biodiversity through habitat fragmentation, degradation, and wildlife-vehicle collisions. The project has two goals: to examine the global extent of biodiversity consideration in transportation agency mission statements and to identify barriers to integrating biodiversity, surveying Canadian and U.S. transport officials. Guided by the ‘polluter pays principle’, we ask: to what extent do agencies consider biodiversity, and what challenges or opportunities exist? We hypothesize that countries who signed the Convention on Biological Diversity (CBD) should show an increased openness to biodiversity consideration, 30 years after the agreement’s 1992 signing by 196 nations. Methods include a dimensional cluster analysis of 77 mission statements from Canada and its provinces, the U.S. and its states, and 13 CBD signatory countries. Hierarchical dendrograms and four linkage methods (‘Complete’, ‘Average’, ‘Single’, and ‘Ward.D2) were used to visualize similarities. France was the only country to explicitly mention ‘biodiversity’. Most statements emphasized human focused priorities like safety, economy, and quality of life, often omitting or vaguely referencing the natural environment. Survey findings revealed general openness to biodiversity inclusion but barriers such as public or managerial backlash, political constraints, misuse of funds, and concerns over greenwashing were cited. The mixed-methods approach aims to identify exemplary mission statements that can serve as biodiversity leadership models in the transport sector. It also seeks to provide strategies for overcoming identified barriers to biodiversity integration into agency mission statements worldwide.
Keywords: Biodiversity, Transportation infrastructure, Mission statements, Polluter pays principle, Convention on Biological Diversity (CBD), Dimensional cluster analysis, Barriers to biodiversity integratio
The Trickster Thread: Using the Arts as a Tool for Individual and Social Transformation
No full textABSTRACT
The Trickster Thread: Using the Arts as a Tool for Individual and Social Transformation
Sue Proctor
Doctor of Philosophy (Individualized Program in Social Science) Concordia University, 2025
The history of Commedia dell’arte and the Trickster is centuries long. The archetype of Clown and Trickster continues in many shapes and forms (Green & Swan 1993; Holm 1998; Mawer 1932; McCormick 2010; Nye 2016; Towsen 1976; Proctor 2013). In the arts, through performing, teaching, working in healthcare and personal development as a clown, I have encountered and engaged with the Trickster. This thesis traces the thread of the Trickster through these multiple practices to realize what the Trickster might have to offer in the present day.
Commedia and the Trickster (or Clown) have inspired much of my work, from the Manitoba Developmental Center (MDC) where the tools of Commedia and clowning were effective in facilitating creative drama with adults diagnosed with severe intellectual and physical disabilities, to my work with children and others through the Manitoba Artists in the Schools program (AIS), Manitoba Theatre for Young People (MTYP), the Arts Ability Project with the Canadian Centre on Disability Studies (CCDS) and presently with Arts Inclusion at the Crescent Arts Centre (CAC). The improvisation, mime, masks and puppetry from Commedia dell’arte followed me as did the sense of humour, play, reversal and paradox from the storytelling Trickster. Based on my personal journey, this thesis brings together aspects of this comedic practice in literature, performance and socially engaged arts to envision an approach that is able to revitalize arts process, practice and performance to make the arts more meaningful, accessible and inclusive to the public
Early Modern Portraits of Elderly Women and the Enigmatic Legacy of Sofonisba Anguissola
No full textSeveral portraits of elderly women have been attributed to the Renaissance artist, Sofonisba Anguissola as self-portraits in old age despite a lack of strong evidence to support these attributions. This thesis paper aims to shed some light on these incorrect attributions by examining how the “mythology” that has been created around Sofonisba’s life (e.g.: beliefs and stories related to her biography) might have made these attributions to seem plausible to earlier scholars. First, this thesis will go through the provenance of the misattributed portraits to better understand how and when these paintings were connected to Sofonisba. Second, this thesis will look at how the life and career of Sofonisba and how that has been discussed in scholarship since the Early Modern Period. This thesis will highlight aspects of her career that may have contributed to the belief that Sofonisba extended her career as a painter of self-portraits into old age. The late career of Sofonisba is obscure compared to her early career, as little is known about the artist after she entered the court of Philip II in 1559. Similarly, early modern portraits of elderly women are an underdeveloped topic in art history scholarship, and this thesis aims to contribute to this area of study. This thesis will explore how Sofonisba might have become associated with portraits of elderly women through inaccurate narratives in her biographies. I will also speculate about what these inaccuracies reveal about the negative manner in which art historians have treated elderly artists and old age in visual culture
Agency Co-Creation in Speedrunning: A New Form of Community Driven Value Creation Through Transgressive Behaviors
No full textWhile prior literature has studied how communities can co-destroy value when producers and consumers are misaligned in their goals, little research has focused on how transgressive consumer behaviors—behaviors that go against a producer’s intent—can create value. To this end, I study the speedrunning community, a subset of the gaming community focused on beating games as fast as possible, through any means available. In their search for faster times, they often find themselves radically altering games against producers’ intents. My findings reveal ways in which communities can co-create a new temporary agency for games—speedrunning—that is to say new ways to interact with them, by altering either the gameplay offerings of their games, or by introducing new forms of sociability. Speedrunning creates value by extending the longevity of products, increasing their customizability, as well as offering expanded social opportunities that deepen individuals’ connection with the game. By creating a new temporary agency, speedrunners find themselves more fulfilled as both individuals and consumers. The findings deepen our understanding of co-creation and co-destruction, demonstrating that transgressive behaviors can create value
Disentangling the AI Black-Box Model: From Direct to Indirect Influence
No full textDue to the widespread use of artificial intelligence and machine learning models across numerous domains that directly impact individuals’ lives, it is essential to ensure that these models are making their decisions in a non-discriminatory manner. That is, biases encoded in the underlying training data are not reflected in the output of the model. This is, however, often hard to control since the predictive accuracy of these models come at the cost of interpretability.
The purpose of this thesis is to investigate and apply methods for interpreting black-box machine learning models to bring more transparency into their decision-making process by analyzing both the direct and indirect influence of input features on model predictions. We begin by studying the theoretical background of the SHAP (SHapley Additive exPlanations) framework, Shapley values, and their implementation in measuring direct influence. We explore the SHAP Python package for both local and global explanations and visualization of direct feature influence on both synthetic and real-world datasets. We then transition to studying indirect influence using the Disentangled Influence Audit procedure, which uses adversarial training to learn disentangled latent representations for auditing hidden dependencies. After presenting all the background information, we implement this procedure and evaluate these methods through numerical experiments on synthetic functions and real-world datasets including the Adult Income and the Montréal Housing datasets. In addition to these experiments, we also examine how “data-hungry” these auditing methods are by examining their convergence as a function of the number of samples required. Our results demonstrate the importance of auditing both direct and indirect pathways of influence to promote interpretability and fairness in complex models
Can You Hear the Trees Talking? A collaborative arts-based methodology to listen to survivors of sociopolitical violence
No full textCan you hear the trees talking? is a research-creation project developed in collaboration with Comunidad, a musician and cultural leader from Tumaco, Colombia. It stems from the research question: How to listen effectively and with care to survivors of sociopolitical violence while collaborating on creative work based on their life stories? The project proposes and analyzes an oral history and art-based methodology for conducting dialogical interviews while drawing trees. Initial curiosity about Comunidad’s experiences linked with his forced displacement prompted interviews and experimentation with drawing, aiming to foster a sense of comfort and safety. As the project evolved, the motivation expanded to understanding how our differing social, racial, gender, and cultural contexts have shaped our experiences of the armed conflict in Colombia.
Through the creation of two audiovisual works, “From the Balso to The Cununo” and “Eucalipto,” the project integrates personal, collective, and ancestral stories by centering the symbolic significance of the Balso and Eucalyptus trees in our lives. The findings highlight a transformative shift from one-sided conversations to reciprocal dialogue, fostering a space for trust, mutual curiosity, and creative exchange. The project underscores the role of art as an essential element for transitional justice in a country grappling with the legacies of colonialism, racism, patriarchy, and systemic inequality. It contributes to the broader discourse on the ethics of socially engaged art, emphasizing the importance of listening with care in collaborative artistic processes with survivors of sociopolitical violence
Advanced Deep Learning Architectures for Automated Heart Sound Classification
No full textAutomatic heart sound classification is a longstanding and challenging problem in the research field of biomedical engineering due to the fact that heart sound is very complex and highly nonstationary.
The most machine learning-based heart sound classification methods achieve limited accuracy and are primarily developed using a segmentation-based approach. Since they depend on single-domain feature information and also tend to focus equally on each part of the signal, rather than employing a selective attention mechanism.
Additionally, the existing studies rely on single-stream architectures, overlooking the advantages of multi-resolution features. Apart from this, these methods rely solely on early, late, or intermediate fusion, which often fail to fully integrate the diverse and multiscale features required for robust classification.
The proposed framework addresses these problems through three core components of deep learning architecture design: the selection of diverse feature representations combined through an effective feature fusion strategy, a learning mechanism that leverages multi-resolution feature fusion, and the utilization of multi-scale representations.
In this thesis, three novel deep learning architectures and methods are developed that do not require a segmentation approach to deal with the existing limitations in the field of heart sound classification.
First, we propose a novel multimodal attention convolutional neural network (MACNN) that incorporates a feature-level fusion strategy. The architecture consists of three parallel branches, each employing low-complexity convolutional neural networks combined with attention mechanisms to process different feature domains. This design enhances feature diversity and enables more effective multi-feature fusion.
Second, we designed a novel attention fusion-based two-stream vision transformer (AFTViT) architecture that captures long-range dependencies and diverse contextual information at multiple scales. A novel attention block is then used to integrate cross-context features at the feature level, enhancing the overall feature representation.
Third, a novel hierarchical multiscale swin (HM-Swin) transformer network with attention fusion is developed. The proposed model benefited from extracting hierarchical multiscale features from swin transformer backbone, which are further fused using a dynamic fusion block. This approach ensures the effective capture of interdependencies.
Comprehensive experiments are conducted on publicly available datasets to demonstrate the efficiency of MACNN, AFTViT and HM-Swin architectures. The results show that these methods consistently outperform existing state-of-the-art approaches in terms of classification accuracy while maintaining a minimal number of training parameters