Innovative Projects Realized

Towards an Overview of Industry 5.0 Supply Chain Performance Indicators

The objective of this project is to identify Industry 5.0 indicators applicable to supply chains. The concept of Industry 5.0 is relatively new, so companies still face the challenge of how to incorporate its three pillars—sustainability, resilience, and human-centricity—into their operations. Identifying performance indicators related to these pillars is a step forward, as companies use performance indicators to monitor their operations and determine whether they are aligned with their organizational strategy. This list of indicators can be used by Canadian and Colombian companies to aid in their decision-making process. Furthermore, given that the project involves researchers from both countries, it will provide different perspectives on the same issue, including the viewpoint of a developed country and that of a developing country.
Additionality, this project will strengthen collaboration between the Industrial Engineering Department at the Université du Québec à Trois-Rivières and the School of Engineering at Universidad de La Sabana, as researchers from both institutions share research interests in sustainability in the value chain. The results obtained in this project will be used in conducting semi-structured interviews with experts and entrepreneurs from Quebec and Colombia in a future collaboration between both institutions.

Framing Resilience through a multidisciplinary approach: reference, agency and metaphor in sustainability discourse

This project investigates how the concept of resilience is used and understood in Canadian sustainability discourse, especially in policy documents and public reports written in English and French. Resilience is a key term in climate and sustainability discussions, but its meaning often difficult to grasp; resilience can be used as a property of communities, governments, systems, or individuals and often remaining vague and abstract. Such indeterminacy can lead to confusion or miscommunication, especially when responsibility for resilience is unclear. This project will analyze how resilience is introduced, maintained, and framed by focusing on (i) reference, (ii) metaphoric and other non-literal imagery associated to resilience and (iii) explicit and implicit indicators of agency and responsibility. A bilingual corpus of Canadian and UN documents will be built and annotated using specialized tools to track how resilience is expressed and who is portrayed as responsible. The project will benefit participating institutions by providing new insights into how sustainability messages are shaped through language, helping improve communication strategies and policy development. Ultimately, the findings will help clarify how resilience is framed in public discourse and support more inclusive and accountable approaches to sustainability and climate governance.

The impact on paper quality and roll profile from stock activity on Fourdrinier

This project will focus on the very first stage of papermaking, where a watery mixture of fibers is spread onto a moving screen to form a sheet. The way the fibers move and mix during this step—called “stock activity”—has a big effect on how strong, smooth, and uniform the final paper will be. Right now, operators can see activity on the machine but have no reliable way to measure it. The intern will develop a method to measure this activity directly on Irving Paper’s machine, collect baseline data, and test different operating conditions to find the best settings. By doing this, the project will give Irving Paper new tools to improve paper quality, make rolls more consistent, and run the machine more efficiently, supporting both productivity and competitiveness.

The Full Cost of Commuting: Evaluating Transportation Affordability and Mode Shift Potential in London, Ontario

The City of London plans and manages a multi-modal mobility system to move people and goods in an affordable manner. Affordability is multi-dimensional however, from the private costs of residents, such as fuel and bus fare, to public costs such as road construction and maintenance. In order to meet its commitment to London residents, the City requires a clear understanding of the full cost of modal choices employed in transportation, including public costs, private costs, and external costs. This proposal is to conduct a full cost of mobility analysis of the costs London and Londoners pay for various modes of travel.
This analysis will empower City staff to make decisions and recommendations on providing an affordable multi-modal mobility system to London residents using empirical analytic results directly pertinent to the London context. Economically, it will benefit the City, and thus its residents, by holistically assessing the costs that various transportation modes incur and highlighting potential affordability gains available through transportation mode optimization. Socially, it will help not only City staff, but also residents through the City’s outreach and public participation, to understand the costs incurred by various modes of transportation.

Generalized Thermodynamically Admissible 13-Moment Equations

This project explores how to better model gas flows in situations where traditional fluid equations break down, such as in very small systems or low-pressure environments. Instead of relying on costly molecular simulations, the research develops advanced extensions of classical fluid models that remain mathematically stable and thermodynamically consistent, while being flexible enough to describe different gases. The student will spend time at a leading German institution to refine and test these models with international experts, combining rigorous theory with modern numerical methods. By bringing this expertise back to Canada, the project will strengthen national research capacity and support innovation in industries such as aerospace, vacuum technology, and micro-systems, while also deepening long-term collaboration between Canadian and German institutions.

Intelligence artificielle dans les entreprises B2B au Québec: défis et opportunités

Ce projet de recherche porte sur l’adoption de l’intelligence artificielle (IA) par les entreprises québécoises qui œuvrent dans le secteur du commerce entre entreprises (B2B). L’objectif est de mieux comprendre comment ces organisations intègrent l’IA dans leurs activités, quels bénéfices elles en retirent, mais aussi quels défis humains, financiers et organisationnels elles rencontrent. Pour y parvenir, une étudiante au doctorat mènera un sondage auprès d’un large échantillon d’entreprises. Les résultats permettront de dresser un portrait inédit de l’utilisation de l’IA dans ce secteur et d’identifier les meilleures pratiques. Pour l’organisation partenaire, une firme spécialisée en marketing B2B, ce projet offrira des données précieuses afin d’améliorer ses services et de mieux accompagner ses clients dans leur transformation numérique. De manière plus large, cette recherche contribuera à soutenir l’innovation et la compétitivité des entreprises québécoises et canadiennes dans un contexte technologique en évolution rapide.

Droit international de l’investissement et développement durable

Le projet s’inscrit dans la thématique “Durabilité et environnement”. Il analyse les interactions entre le droit international de l’investissement et les impératifs de développement durable. Dans un contexte marqué de plus en plus par l’urgence climatique et environnementale, force est de constater que l’ensemble des Etats, y compris le Canada sont confrontés à des défis écologiques majeurs. Pour préserver ces intérêts sociaux et environnementaux, les Etats prennent des mesures, parfois susceptibles de porter atteinte aux intérêts privés des investisseurs. Ces derniers ne tardent pas à traduire les Etats qui s’engagent dans la durabilité, devant les tribunaux arbitraux, en usant des standards de protection des investissements solides prévus par les traités d’investissements, à l’instar du Traitement juste et équitable. Concrètement, le projet vise à analyser de manière critique les mutations du droit international à la lumière des impératifs du développement durable. Pour ce faire, il identifie les solutions innovantes permettant d’intégrer des obligations substantielles à la charge des investisseurs, qui sont jusque-là exemptés. La doctrine contemporaine dénonce cette asymétrie du droit international de l’investissement et le projet vise à enrichir cette réflexion dans le but de contribuer à cette transformation du droit international de l’investissement.

Microwave-Assisted Degradation of Organic Contaminants and Regeneration of Granular Activated Carbon in Water Treatment

This project explores microwave-assisted thermal treatment as a sustainable method to both degrade organic contaminants and regenerate granular activated carbon (GAC) used in water treatment. The goal is to determine whether high-power microwaves can desorb and break down pollutants from spent GAC while preserving its structure and extending its adsorptive life.

A range of micropollutants including pharmaceuticals, phenols, dyes, and pesticides, will be tested on coal, coconut, and wood-based GAC under controlled 2.45 GHz microwave exposure. By promoting desorption and thermal transformation, this approach could reduce reliance on chemical regeneration or full mineralization while enabling multiple reuse cycles of GAC.

AGP Dynamic Solutions Inc., a Canadian leader in industrial microwave systems, is the industry partner. With expertise in high-power microwave technology, AGP is evaluating how its systems can support on-site GAC regeneration, cutting operational costs and carbon waste for water utilities and industries.

Led by an intern with advanced research training in water filtration, the project will use advanced analytical tools to assess regeneration efficiency. The outcomes could drive scalable, innovative solutions that lower waste, support cleaner water, and align with circular economy and public health goals.

Adaptive Digital Twin for Optimizing Repositioning, Routing, and Matching in Private Floating Fleets

Private charter fleets are valuable mobile assets that, when efficiently managed, can generate substantial revenue for operators and owners. A key factor in maximizing profitability is achieving a high asset utilization rate. We propose the development of a large-scale adaptive digital twin for supporting private floating fleet repositioning, routing and matching decisions. The digital twin is designed to connect thousands of charter aircraft and passengers in real time in a virtual private air travel network. Metaheuristic repositioning/routing/matching algorithms will be designed to optimize floating fleet assignments. These algorithms will account for various operational constraints and costs, including regulatory compliance, insurance, fuel surcharges, crew fees, and airport charges.
The digital twin will employ a microservice-enabled multi-agent system architecture to model key components—operators, passengers, aircraft, airports, and more. This back-end infrastructure will enable the industrial partner to monitor dynamic supply and demand, optimize routing and repositioning decisions, evaluate and validate a wide range of strategic, operational, and pricing scenarios. It will also be designed to be integrated with the industrial partner’s existing software systems. Additionally, the proposed platform can support the development of advanced market mechanisms such as empty-leg auctions, group bidding, and revenue-sharing models among collaborating charter operators.

Attitude Determination using Dual-Purpose SSA Payload

Wide Field of View (WFOV) cameras can be deployed in the space environment to allow for opportunistic observation of Resident Space Objects (RSOs) for Space Situational Awareness (SSA). This project aims to deploy a WFOV camera in a cubesat, which will increase the observation window compared to the previous near-space and stratospheric missions.

Studying formation and destabilization mechanisms of pickering emulsions encapsulated with bioactive compounds via confocal/STED microscopy

Bioactive compounds are naturally occurring food components that can promote human health, but they often lose their effectiveness because of problems such as low stability, low solubility, and poor absorption in the body. Encapsulation in emulsions is one promising way to protect these compounds and help them reach their target tissues, but the main limitation is that emulsions are not always stable and can separate over time. Pickering emulsions, which are stabilized by solid particles rather than traditional surfactants, have been shown to offer better stability and lower toxicity, making them highly attractive for food and nutraceutical applications. However, there is limited understanding of the exact mechanisms by which they become unstable, particularly when bioactive compounds are encapsulated inside them. To address this knowledge gap, the project will use advanced imaging methods, such as confocal and STED microscopy, to capture high-resolution images of emulsions at different stages of formation and destabilization. The images will be analyzed using quantitative tools to provide information on droplet size, shape, distribution, and the arrangement of encapsulated compounds. By combining this information, the project will build new understanding of how emulsion stability is related to its microstructure and the role of protein nanoparticles as stabilizers.

Automation, Data Processing, and Validation of Spectral Measurements in Molecular Degradation Research

This project develops automated pipelines for processing Raman and UV-Vis spectral data collected during studies of molecular degradation. The focus is on improving reproducibility, accuracy, and efficiency in monitoring antioxidants such as BHT and PAN derivatives. The workflows will perform spectral baseline correction, peak fitting, smoothing, and feature extraction, enabling rapid interpretation of large experimental datasets. Validation against quantum chemical simulations ensures consistency between experimental observations and theoretical models. Automated routines will allow scalable, high-throughput analysis, reducing manual errors and accelerating discovery. Outcomes include standardized tools for processing spectroscopic measurements, integration with quantum-derived reference spectra, and improved reliability of degradation monitoring in industrial oils and complex matrices. Students will gain experience in coding, algorithm development, and data–experiment integration, strengthening their skills in spectroscopy, automation, and applied sensing technologies.