Controllable Synthesis and Mechanism Investigation of Catalysts with Atomic-Level Reactive Sites for Energy Conversions

The energy crisis and environmental concerns stemming from fossil fuel use have emphasized the urgency for sustainable energy solutions, spurring the development of advanced catalytic materials for electrochemical processes. Catalysts with atomic-level reactive sites (CALRs) have gained significant attention due to their 100% atomic utilization, greatly reducing precious metal costs. Additionally, CALRs with multiple active sites offer unique advantages for catalyzing complex reactions. However, CALRs still face several challenges: (1) rational design and synthesis of CALRs, and (2) understanding the interaction mechanisms. This thesis focuses on the controlled synthesis of CALRs with multiple active sites using atomic layer deposition (ALD) and mechanism investigation via advanced characterization and theoretical calculations. Firstly, we employed a well-designed phosphorus modified atomic layer deposition (P-ALD) strategy to anchor atomic phosphorus sites coordinated one-to-one A-B bimetallic dimer structures (Pt1W1-P dimer) on various substrates. The Pt1W1-P dimer catalysts demonstrated a unique interatomic hydrogen adsorption mechanism, revealing W sites as the primary site for hydrogen adsorption, subsequently extending to the Pt single atom, leading to a 60-fold improvement in mass activity compared to commercial Pt/C for hydrogen evolution reactions (HER). Secondly, by incorporating an additional oxygen cycle modulation into the P-ALD technology, we successfully synthesized a one-to-one-to-one A-B-C trimetallic trimer catalyst (Ru₁Pt₁W₁ trimer). The ternary active sites facilitated optimal adsorption and desorption of intermediates in complex reactions, outperforming dimer catalysts and commercial Pt/C in hydrogen oxidation reactions (HOR) and HER. Thirdly, we examined the effects of coordination environment and interatomic spatial arrangement on metal site interactions. The three-dimensional asymmetrically coordinated one-to-one A-B bimetallic dimer catalyst (Pt1Fe1-TAC) dimer showed superior HER performance due to strong interatomic interactions and a unique electron transfer pathway from Fe to Pt site. Lastly, we investigated how changes in the coordination structure of atomic sites during reactions impact catalyst performance and stability. A surface stress engineering strategy was proposed, coating RuO₂ with a ~1 nm atomic W layer, forming WAL-RuO₂ catalyst. The W layer undergoes site reconstruction, transitioning from tensile stress that enhances catalytic activity to compressive stress that stabilizes the RuO₂ lattice, thereby achieving outstanding efficiency and durability for acidic oxygen evolution reaction (OER). These findings provide valuable insights for developing low-cost, high-performance electrocatalysts for energy conversions

Explaining deep learning-based anomaly detection in energy consumption data by focusing on contextually relevant data

Detecting anomalies in energy consumption data is crucial for identifying energy waste, equipment malfunction, and overall, for ensuring efficient energy management. Machine learning, and specifically deep learning approaches, have been greatly successful in anomaly detection; however, they are black-box approaches that do not provide transparency or explanations. SHAP and its variants have been proposed to explain these models, but they suffer from high computational complexity (SHAP) or instability and inconsistency (e.g., Kernel SHAP). To address these challenges, this paper proposes an explainability approach for anomalies in energy consumption data that focuses on context-relevant information. The proposed approach leverages existing explainability techniques, focusing on SHAP variants, together with global feature importance and weighted cosine similarity to select background dataset based on the context of each anomaly point. By focusing on the context and most relevant features, this approach mitigates the instability of explainability algorithms. Experimental results across 10 different machine learning models, five datasets, and five XAI techniques, demonstrate that our method reduces the variability of explanations providing consistent explanations. Statistical analyses confirm the robustness of our approach, showing an average reduction in variability of approximately 38% across multiple datasets

Characterization of Metal-organic Frameworks via Wideline and High-resolution Solid-state NMR Spectroscopy

Metal-organic frameworks (MOFs) are a class of porous materials composed of metal centers and organic linkers. MOFs have diverse applications, including gas storage/separation, catalysis and energy storage, due to their unique properties such as high specific surface area, tunable topologies and good stabilities. Understanding the relationship between MOF structure and properties is crucial for enhancing performance and developing new materials. In this thesis, solid-state NMR (SSNMR) spectroscopy combined with theoretical calculations have been utilized to characterize the local structure of MOFs and adsorbed guest molecules. In the first part of this thesis, the local structures of several representative MOFs were studied with wideline NMR. The local environments of Cu(I) ions in Cu-MOFs regarding the coordination numbers, phase changes, oxidation states, and anion exchanges, were characterized using 63/65Cu SSNMR. The Zr centers in Zr-MOFs were examined with 91Zr SSNMR at high magnetic field of 35.2 T and 19.6 T, providing insights into the local site symmetry and short-range ordering around Zr centers. 91Zr NMR is very sensitive to structural variations in MOFs caused by guest molecules, linker substitution, and post-synthetic treatments. The 209Bi and 127I SSNMR spectra of bismuth- and iodine-containing MOFs were acquired at magnetic fields up to 36 T, with breadths ranging from 8 to 50 MHz, pushing the boundaries of ultra-wideline NMR. Cl-containing MOFs with different metals and organic linkers were studied with 35Cl SSNMR. The correlation between 35Cl NMR parameters and both local bond lengths and bond angles were obtained. 35Cl SSNMR was also used to identify an unknown product from chemical reactions. MOFs can be tailored for applications such as Xe and Kr separation. The co-adsorption behavior of Xe and Kr in five MOFs including the adsorption locations, binding strength, guest-host interactions and exchange dynamics was investigated with 129Xe and 83Kr SSNMR aided by molecular simulations. The second part of this thesis features two examples of high resolution SSNMR applied to MOFs. (i) We demonstrate that combining new cryogenic MAS probe technology and performing NMR experiments at a high magnetic field leads to significant signal enhancement for 67Zn SSNMR. The multiple non-equivalent Zn sites with very similar local environments in two MOFs, ZIF-4 and α-Zn3(HCOO)6, were well-resolved by natural abundance 67Zn 3QMAS NMR technique. (ii) The structure of a defective MOF MIL-120(Al) was investigated by multinuclear (1H, 13C, and 27Al) SSNMR spectroscopy. The local structure around defective Al sites was directly probed by 27Al 1D and 3QMAS NMR

Northern Tornadoes Project. Annual Report 2024

The Northern Tornadoes Project (NTP) 2024 Annual Report provides a comprehensive overview of the project\u27s operations, research, and findings over the past year. In 2024, NTP continued its mission to improve tornado detection, documentation, and public awareness across Canada. A significant milestone was the establishment of the Canadian Severe Storms Laboratory (CSSL) at Western University, supported by a $20 million contribution from ImpactWX. The CSSL serves as a hub for severe storm research and data collection, integrating multiple projects, including NTP, the Northern Hail Project, and the newly launched Northern Mesonet Project. Key advancements in 2024 included the release of a new tornado dataset (1980–2023) and an Advanced Dashboard for detailed event analysis. NTP recorded 129 tornadoes and 86 downbursts, utilizing ground surveys, high-resolution drone and satellite imaging, and crowdsourced data. Notably, four billion-dollar storms struck Canada, including a record-breaking GTA flash flood and a potential fire tornado in Jasper, AB. Additionally, the Michael Newark Digitized Tornado Archive was launched, preserving historical tornado records. With increased media engagement and scientific publications, NTP remains a leader in severe storm research. Moving forward, the project aims to refine detection methodologies and enhance public safety efforts through data-driven insights

Corrosion And Mechanical Wear Of Biomedical Metallic Implants And Corresponding Health Aspects

Total hip and knee arthroplasties are crucial for the restoration of damaged joints. If they fail in function or cause detrimental body reactions, this has devastating consequences for the patient. The complex chemical and mechanical conditions in the human body might influence the function and longevity of metallic implants. There is a mutual relationship between degradation of metallic alloys and corresponding biological responses. Both implant and patient-specific factors impact the failure of metallic alloys, resulting in early revision. This research aims to better understand, quantify, and ultimately prevent corrosion and tribocorrosion of materials and implants of relevance for hip and knee arthroplasties. Further, it aims at better diagnosing resulting metal allergies. In this study, the pattern and levels of biological damages on the hip trunnions and knee tibial baseplates were categorized and quantitatively evaluated by proposing standardized scoring systems based on optical microscopy (OM) and scanning electron microscopy (SEM). Tribocorrosion was predominantly observed across both implant types. Knee implants were more severely damaged than hip implants, except for tibial baseplates with optimized locking mechanisms. Patient-specific factors, comorbidities, and implant factors significantly correlated with the extent of damage. The effects of passivation with nitric acid and surface roughness on the corrosion of additively manufactured Ti6Al4V alloys, fabricated via laser powder bed fusion (LPBF), in benign (protein) and harsh (hydrochloric acid) solutions were studied. Rough surfaces provided a greater surface area favorable for more protein adsorption. The amount of metal ion release reduced after passivation. The LPBF Ti6Al4V alloys exhibited a reduced mechanical and chemical wear than wrought Ti6Al4V, resulting from finer microstructure, higher microhardness, and faster re-passivation. To evaluate current metal allergy diagnostic methods, chemical speciation modelling was used to study the bioavailable fraction of different aluminum and chromium salts under varying sweat pH and composition and suggest improvements to current diagnostic practices. Metal salt type, concentration, and sweat conditions alter the amount of bioavailable ions and influence the success of diagnosing related metal allergies. In all, this research contributes to improving and better utilizing orthopedic joint implants

Dual Processes for Social Rank: A Relational Perspective of Dominance and Prestige

Dominance and prestige are two fundamental processes to obtain social rank and influence. Previous research, largely taking a social consensus view, has advanced knowledge on the outcomes of leaders adopting dominance- and prestige-oriented strategies. In this dissertation, I adopt a relational perspective in studying the nature and consequences of dominance and prestige. In two series of studies, I examined the behavioural components of dominance and prestige processes in horizontal teams (Chapter 2), and how follower subjective experiences and work relationships were impacted (Chapter 3). Chapter 2 provides a multiperspective (Smith et al., 2024) investigation on dominance and prestige. Adopting a relational focus, I utilized social relations models to analyze dominance and prestige as dynamic interpersonal processes rather than treating variance across raters as systematic errors. Using important social behaviours to exemplify and highlight the merit of the multiperspective, Study 1 (N1 = 478; N2 = 637) showed that dominant partners were viewed as more assertive, more likely to engage in toxic work behaviours, and less cooperative. Dominance was associated with less cooperativeness from partners. In contrast, prestigious partners were viewed as more assertive and more cooperative but less toxic. Prestige was associated with higher cooperativeness from partners. Despite divergent behavioural signatures, both dominance and prestige facilitated leader emergence at the reputational level. However, only prestige predicted leader emergence at the relational level. Study 2 (N = 1736) showed that prestige contributed to more sustainable work relationships at the relational level. Overall, these findings highlight the consequences of dominance and prestige for productive working relationships. Chapter 3 focused on the important role of follower experiences. Using observational (N = 250) and experimental (N = 277) designs, the results highlight that follower psychological need satisfaction (i.e., need for competence, relatedness, and autonomy) helped to explain the relationship between leader dominance/prestige and willingness to continue working with that leader in the future (i.e., dyadic viability). Working with a dominant leader impeded follower need satisfaction, whereas the opposite was true for working with a prestigious leader. Overall, this dissertation provides important insights on how dominance and prestige operate through dyadic interactions

Kolmogorov–Arnold recurrent network for short term load forecasting across diverse consumers

Load forecasting plays a crucial role in energy management, directly impacting grid stability, operational efficiency, cost reduction, and environmental sustainability. Traditional Vanilla Recurrent Neural Networks (RNNs) face issues such as vanishing and exploding gradients, whereas sophisticated RNNs such as Long Short- Term Memory Networks (LSTMs) have shown considerable success in this domain. However, these models often struggle to accurately capture complex and sudden variations in energy consumption, and their applicability is typically limited to specific consumer types, such as offices or schools. To address these challenges, this paper proposes the Kolmogorov–Arnold Recurrent Network (KARN), a novel load forecasting approach that combines the flexibility of Kolmogorov–Arnold Networks with RNN’s temporal modeling capabilities. KARN utilizes learnable temporal spline functions and edge-based activations to better model non-linear relationships in load data, making it adaptable across a diverse range of consumer types. The proposed KARN model was rigorously evaluated on a variety of real-world datasets, including student residences, detached homes, a home with electric vehicle charging, a townhouse, and industrial buildings. Across all these consumer categories, KARN consistently outperformed traditional Vanilla RNNs, while it surpassed LSTM and Gated Recurrent Units (GRUs) in six buildings. The results demonstrate KARN’s superior accuracy and applicability, making it a promising tool for enhancing load forecasting in diverse energy management scenarios

The Air of the Now and Gone

This publication accompanies the 2025 exhibition The Air of the Now and Gone, curated by Kirsty Robertson and Sarah E.K. Smith. They ask: in the face of the “wicked problem” of climate change, which precludes easy solutions, how can we move forward? How can we address a crisis that prompts apathy and disconnect? In their introductory essay, Robertson and Smith discuss the works of the artists, who refuse detachment and simultaneously complicate idealism. Like the artists, the curators seek to encourage diverse responses to the realities of climate change, moving beyond apathy and despair to engage empathy, wonder, joy, attentiveness and connection. In their text, Siobhan Angus and Elaina Foley offer a meditation on air and breathing amidst multiple connected climate crises. Kristi Leora Gansworth foregrounds Anishinaabe onáchigewin (prophetic teachings) and inákonigéwin (a concept that denotes action and consequence) in her essay. These she shares as strategies for developing worldviews in line with the Earth’s spark. Editors and coordinators: Kirsty Robertson, Sarah E.K. Smith, Heather Anderson, Sandra Dyc

A qualitative study of the role of hearing aid use and physical fit accessories in a sample of older adults

Objective: The purpose of the study was to qualitatively describe the experiences of hearing aid and physical fit accessories use during physical activity and exercise participation in a sample of older adults with hearing loss. Design: A prospective qualitative research design was employed with the use of focus groups with older adult participants who were fitted with hearing aids and physical fit accessories. Study Sample: Twelve older adults with hearing loss (six experienced and six new hearing aid users, age range 64 – 88 years) were recruited in this study. Results: The barriers to hearing at physical activity and exercise environments were related to reverberation, loud music, and instructor’s location and position relative to exercise members, whereas facilitators were aided hearing, the instructor projecting their voice and demonstrating the moves. The most preferred physical fit accessories were the retention lock and the corded and cordless hearing aid sleeves. The least preferred accessories were the hearing aid-to-glasses connector and stick ’n stay tape. Conclusions: Individual differences and needs were factored into different perspectives on hearing aid and physical fit accessory use, emphasizing patient-centered approach when coaching and counselling on device use for physical activity and exercise