Projets novateurs réalisés

Population Survey and Mitigation of Amphibian Roadkill along Heart Lake Road

Heart Lake Road (Brampton, Ontario) bisects a Provincially Significant Wetland. Increases in traffic volumes on the road have led to large numbers of road kill during the spring migration. The TRCA has been monitoring the road kill for two years and has found that thousands of frogs and toads as well as hundreds of turtles, including species at risk (SAR) are killed every spring and early summer. The TRCA is looking to partner with York University to assess the significance of the mortality to the local population as well as mitigate the road kill by designing a wildlife passage under the road.

Development of advanced absorber/emitter for wireless power transfer thermophotovoltaic systems

The demand for wireless power transmission is growing due to the increasing costs of transporting conventional fuels for satellites, drones, and aerospace systems. A promising solution lies in Thermophotovoltaic (TPV) technology, with an impressive system efficiency of around 50%, converting heat from any high-temperature sources into electric power. TPV systems, which are lightweight and have no moving parts, are poised to play a crucial role in clean energy conversion. This project aims to integrate wireless power transmission and TPV technology, focusing on a novel monolithic absorber/emitter to capture specific wavelengths from laser sources and solar radiation. The absorber/emitters consist of tungsten substrates with thin films like YSZ, MgO, CaO, HfN, and AlN. Thorough thermal stability assessment and testing will ensure durability and efficiency. By making the PV cell independent of laser wavelengths, using low atmospheric attenuation lasers, and exploring diverse power transmission sources, this research pioneers a transformative solution, unlocking energy-efficient possibilities for aerospace missions. Our partners can benefit from these innovations by having access to lightweight and durable power solutions for their technologies, improving functionality and performance, and reducing reliance on traditional fuel sources.

Physics-informed Neural Networks for Time-Dependent Transport Equations

Companies can realize the cost-saving benefits of having access to large amounts of data provided they have digital tools that allow efficient and accurate extraction of information from the dataset. The goal of this project is
to conduct the research required for machine learning algorithms to provide reliable engineering predictions for industrial applications. To achieve the stated objectives, a diverse team of researchers will investigate several
fundamental questions about the interplay between neural networks and other simulation technologies currently used by the industrial sector. With its mandate to develop state-of-the-art tools for physics-based engineering
applications, SOTAES is well-positioned to develop an innovative product based on the outcomes of this research.

Hydrogen Embrittlement Susceptibility of Bainitic versus Martensitic High Strength Steels

The objective of this investigation is to systematically quantify and compare the hydrogen embrittlement susceptibility of austempered (bainitic) steels to that of standard quenched and tempered (martensitic) steels used for manufacturing high strength mechanical fasteners. It has been shown that correctly high strength bainitic steels exhibit measurably superior ductility and toughness as compared to martensitic steels of the same chemistry. These improvements in mechanical properties have made bainitic steel a viable and attractive option for making ultrahigh strength fasteners (e.g., 1400 – 1800 MPa tensile strength). Standard tempered martensitic steel fasteners do not exceed 1400 MPa tensile strength. The improved mechanical properties of bainitic steels have led many in the fastener industry to assume that bainitic steels must also exhibit greater resistance to hydrogen embrittlement. However, thus far there have been are no systematic comparisons of both materials at equal strength and/or hardness.

High-temperature plasma gasification of plastic wastes

Load-Bearing Behavior of Non-Metallic Reinforced Concrete Structures

Ecoacoustics and Land-Use

Cross-Domain Recommender Systems with Limited Human Annotated Data

Recommender systems are artificial intelligences that, as their name would suggest, make recommendations based on provided inputs. For example, recommending jobs a person can apply to based on their resumes. Existing research on recommender systems in the Job and Education domains have focused on a single domain. Our research focuses on bridging the gap between the Job and Education domains in an environment where we have little to no data created by humans. We demonstrate our methodologies by creating a recommender system for Prior Learning Assessment and Recognition (PLAR). PLAR is a system through which people can obtain college credits based on past life experience, such as job history. Our partner organisation hopes that such a recommendation tool can be used to streamline the PLAR process and promote education equity in Canada.

Experimental Plant Ecology in Southern Germany

Design of novel synthetic immune receptors

When cancer grows, tumors create a microenvironment around them, the TME or tumor microenvironment. This acts as a force field around cancer cells that blunts the immune system and allows cancer to escape its surveillance.
At Modulari-T we have developed a way to program the immune system to recognize and kill cancer cells which we call MARC cells. This project proposes to develop a new way to augment MARC cells to make them more active in the TME so that they can break through the barriers and destroy the tumor.

Les plans de gestion des déplacements comme compromis incertain

L’objectif de ce projet de recherche consiste à comprendre comment les entreprises coconstruisent un plan de déplacement en harmonisant des sous-objectifs organisationnels et des besoins sociétaux. Nous souhaitons ainsi étudier le phénomène à travers lequel une entreprise devient une « institution de la mobilité durable », un véhicule permettant la réalisation de thématiques sociétales de déplacements comme l’accessibilité, la réduction de la pollution et de l’auto-solisme ou encore l’étalement urbain. Pour réaliser cet objectif, notre projet de recherche repose sur une étude de cas à l’intérieur de laquelle le plan de déplacement est considéré comme un compromis intra- et inter-organisationnel faisant intervenir une grande variété d’acteurs et parties prenantes.

Sustainable Hydrogel Filters for Efficient Microplastic and Nanoplastic Removal in Wastewater

Micro- and nanoplastic (MP/NP) pollution is a pressing global issue resulting from the widespread use of plastics.
These minute particles, present in everyday products, accumulate in the environment, even being detected in
infant feces and blood. Addressing this concern is paramount, with wastewater treatment processes (WWTPs)
playing a pivotal role. However, conventional WWTPs encounter challenges in filtering out smaller MPs/NPs and
may even contribute to their generation. This project proposes a solution by integrating hydrogel materials with
existing filters. Capitalizing on hydrogels’ 3D networks and absorption capabilities aims to bolster filtration
systems, effectively capturing smaller MPs/NPs. The study evaluates performance and sustainability under
varying water conditions and particle dimensions. This research contributes significantly to addressing global
plastic pollution, directly impacting the health of the global community. It aligns with ongoing water remediation
research at BC Research, providing vital insights into the synergies between hydrogels and wastewater treatment.