Innovative Projects Realized

Developing Correlative Microscopy Workflows in Metallurgy

Understanding the performance of metals is related to its structure at many different length scales, from the atomic level all the way up to the macro-sized object. Being able to knit these length scales together for their chemistry, microstructure and defect structure is critical to deisgning new parts for high performance applications, sch as power generation and aerospace. Correlative microscopy uses multiple techniques to image the same material at different length scales but knitting all of this information together is not straightfowarded. In this project, we will work on developing correlative microscopy techniques and workflows related to metallurgical applications.

Assessing the Impacts of Preparation Techniques on the Properties and Performance of Fuel Cell Catalysts

Hydrogen fuel cell technology plays an important role in reducing our reliance on fossil fuels, helping to meet Canada’s Sustainable Development Goals. Fuel cell performance largely relies on the composition of its catalyst layers, which contain carbon supported nanocatalysts and an ion-conducting polymer. The catalyst layer facilitates generation of electricity from the combination of hydrogen and oxygen gases. This project will use many complementary techniques to expand our understanding of key interactions between the ion-conducting polymer and other components of the catalyst layer. Of particular importance is its influence on the performance and, possibly, poisoning of the catalyst. A series of ion-conducting polymers of interest to the partner organization will be evaluated through comprehensive studies. The outcomes of this work will guide the design of materials and methods for the scale-up production of catalyst layers (e.g., roll-to-roll processes) for manufacturing fuel cells in a manner that saves time and resources.

Intégration de matériaux 2D sur wafer de silicium

La découverte récente de matériaux bi-dimensionnels (2D) possédant une structure stable a révolutionné la physique de la matière condensée. Ils permettent d’obtenir un confinement des porteurs et une réduction ultime des tailles des composants microeélectroniques. L’exemple le plus connu est le graphène qui est composé d’une couche monoatomique d’atomes de carbone d’hybridation sp2 « flottant » sur un substrat, stabilisé par le couplage anharmonique entre les modes de flexion et de tension, induisant une corrugation intrinsèque de la couche. Le GR possède des propriétés remarquables : une structure de bande en cône de Dirac et une mobilité des porteurs inégalée.
L’objectif de ce projet est de démontrer l’intégration de GR monocristallin homogène sur les substrats de silicium sur isolant (SOI) qui ont récemment remplacé les plaquettes en silicium massif comme substrats conventionnels de la microélectronique.
Durant le stage, l’étudiant étudiera l’épitaxie de GR sur un substrat de germanium, puis sur cette couche tampon de Ge sur SOI pour permettre son intégration dans les composants microélectroniques. Les propriétés physiques des différentes couches seront étudiées par microscopie en champ proche, microscopie électronique, analyses de surface. Les systèmes réalisés seront évalués au regard de leurs caractéristiques opto-électroniques.

What Makes TikTok Tic? A Comparative Study of Social Interaction Models Across Platforms

This project will investigate the impact of TikTok’s emergence as a platform characterized by de-contextualized, algorithm-driven content. Understanding the distinctions between TikTok’s design principles and those of other platforms is essential for comprehending their influence on user interactions, from constructive engagement to polarization. The research will employ agent-based models of opinion dynamics, calibrated using data from platforms like Twitter, Reddit, and TikTok, leveraging advances in optimization techniques. It will also utilize language models for precise multi-target opinion prediction. The project aims to create a robust simulation environment, offering insights into social behavior and serving as a testing ground for constructive platform interventions, ultimately enhancing our understanding of digital interaction dynamics and fostering healthier online communities. This will help both institutions understand how social platforms shape our social behaviour, and help to improve public policy for digital communications.

Black Women in STEM Entrepreneurship in the Prairies

STEM programs grew after 2018 in Canada, but only a fraction of graduates worked in a STEM field (CFI, 2022). Less women enter the STEM field and even less in the field are Black women who face challenges finding employment in the industry, leading to a small number pursuing STEM careers, including those STEM careers built around entrepreneurship. Since there is limited understanding of the challenges and opportunities for Black women entrepreneurship in STEM fields in the Prairies and more broadly in Canada, this project aims to provide a better understanding of the opportunities and challenges facing Black women STEM graduates’ access to Entrepreneurship roles in Canada.

L2M – SilicoLabs

SilicoLabs’ software revolutionizes psychology/neuroscience research by harnessing XR to create real-world simulations. Researchers import their 3D models, video, audio, images and creating dynamic interactions between them and the participant – all without writing a single line of code! Researchers determine which variables they want to track (e.g., number of times an object is picked up) and how they want to deliver the simulation. Using the variable system, simulations not only capture comprehensive behavioural data but also seamlessly integrate biosensor information, such as brain waves via EEG. The resulting datasets hold immense value, as they can be analysed using machine learning techniques, uncovering patterns and predicting human behaviour. Further, AI agents can be trained on these datasets and tested within the same simulations, closely emulating human cognition (Sun et al, 2022).

Ylid functionalization of carbon suboxide

This project deals with chemical reactions between carbon suboxide and strong carbon-based bases. Carbon suboxide is the bigger relative of carbon dioxide with two more carbon atoms between the outer oxygen atoms which makes it much more reactive. The reactivities of carbon monoxide to common organic molecules have been reported mid-to-end of last century. The reactivity exploration compared to carbon dioxide however is still very poor. Therefore the utilization of carbon suboxide is still very limited. In this project, we will synthesize carbon suboxide and react it with two types of compounds: Metalated ylids and ketenyl anions, whichof both can be classified as nucleophiles with negatively charged carbons. We will isolate adducts between the gaseous molecule and strong carbon nucleophiles and thereby enrich the explored chemical space. Ideally we hope to isolate unique organic molecules that can be used as building blocks for further functionalization such as drug design.

Learning Legible Human-Robot Handovers

Object handovers, which involve the action of giving and receiving objects, are an integral task for human-robot collaboration. Current human-to-robot handover systems rely on learning from sampled human expert trajectory data [5]. These data are usually difficult to gather, as two humans must hand over many different objects while recording the human motion with a sophisticated motion capture system. Generalization can be achieved by injecting noise into the data and forcing the learning algorithm to extract the relevant signal. We propose to devise and implement a diffusion algorithm that learns from an existing handover dataset to dramatically improve performance and generalizability.

Strategic Planning for Cumulative Impact Assessment in Metlakatla Territory

The proposed research program is a planning process that will help to enable the Metlakatla Development Corporation to meaningfully participate in regional development. There are 29 major projects proposed in the traditional territory of the Metlakatla First Nation and these projects will have significant costs and benefits. The current project-based cumulative effects assessment as required in environmental assessment legislation is not able to adequately address potentially significant environmental and socioeconomic changes that accumulate from individual projects. Our research team will develop a methodology for project evaluation that incorporates Metlakatla values and goals into the review process, assesses regional cumulative effects of proposed projects in Metlakatla traditional territory and develops strategies to manage adverse impacts and maximize potential benefits. The proposed project will provide the Metlakatla First Nation with a valuable framework to participate in future industrial development in a manner that meets their economic, environmental, cultural, social, and health goals and objectives.

Incorporating the offspring sex into estimates of reproductive costs for women in pre-industrial Quebec

Chez les espèces à reproduction sexuée, les individus peuvent être divisés en deux catégories : les mâles d’un côté, les femelles de l’autre. Parmi les espèces où les mâles sont plus grands et lourds que les femelles, les besoins énergétiques masculins sont généralement plus élevés. Une telle différence peut apparaître très tôt dans le développement. Par exemple, chez l’humain, les femmes qui attendent un fils consomment 10% d’énergie en plus pendant la grossesse par rapport à celles qui attendent une fille. Une question clé en biologie évolutive est de savoir si ces différences entre sexes conduisent à des coûts en termes de valeur sélective pour les parents. Dans quelques populations préindustrielles, les femmes qui ont davantage de fils ont une longévité réduite, mais une telle relation est absente dans la plupart des cas. Il est possible que le sexe des enfants ait des conséquences sur la reproduction future de la mère plutôt que sur sa longévité. Ce projet vise à examiner pour la première fois cette idée en utilisant un jeu de données à long-terme issu d’une population préindustrielle au Québec. Ainsi, ce projet propose d’intégrer pleinement le sexe des enfants dans l’étude des coûts de la reproduction.

Use of sound to affect fish movement to reduce bycatch and impingement.

Canada’s fishing and hydropower industries struggle to reduce the harming of fish not used by either industry, known as bycatch or incidental take, and are under increasing regulation to limit these impacts. Working with industrial partners the interns will test acoustic technologies to drive unwanted fish away from capture areas while preserving the desired catch for the fishing industry and reducing clogging of hydropower intake screens. Our two partner organizations have been trying to develop this technology but need our participation to bring it to biological reality. Upon successful completion this project will enable our partners to market their technology to industries that are vital to the Canadian economy.

L2M – Addressing Challenges in Healthcare Workforce Recruitment and Career Advancement: A Comprehensive Solution for Healthcare Organizations, Newcomers, and Non-medical Education Background Individuals

A Comprehensive Solution for Healthcare Organizations, Newcomers, and Non-medical Education Background Individuals.

The product aims to address the root cause problem of bias in healthcare workforce recruitment and create a more inclusive and efficient healthcare workforce in Canada through the implementation of an AI-powered Healthcare Recruitment and Career Journey Solution.