Liquid Crystal Elastomers (LCEs) are shape-changing polymers that contain asymmetrical liquid crystal molecules chemically bonded to the polymer chains in an ordered fashion. Heat and light can be used to change this molecular order, which results in the polymer changing its shape. LCEs show promising applications in remotely controlled soft robotics and actuators, such as […]

Chemical property predictions using quantum machine learning (QML) lie at the intersection of machine learning, quantum computing, and computational chemistry. QML models often use parameterized quantum circuits (PQCs) that abstract gate-level quantum operations but offer limited flexibility in adjustable parameters. To enhance QML model performance and generalizability, incorporating pulse-level operations, which lie below gate-level in […]

This project investigates the brain mechanisms underlying schizophrenia and altered cognitive states using advanced computational models inspired by physics and machine learning. It focuses on understanding how the brain’s activity, thought to operate in a balance between order and disorder (known as criticality), may shift away from this balance in schizophrenia and in the psychedelic […]

Ce projet vise à développer des matériaux composites 100% cellulose pour des applications dans l’emballage électronique biosourcé et biocompostable. L’idée consiste à plastifier le diacétate de cellulose par greffage chimique des chaines de polycaprolactone (PCL) flexibles afin de fabriquer la matrice CA-g-PCL. Les greffons PCL ont l’avantage d’avoir une température de transition vitreuse basse (Tg […]

Gravitational lensing occurs when a massive object, such as a galaxy cluster, bends the fabric of spacetime, turning it into a magnifying glass that focuses the light from a distant object behind it. This phenomenon allows astronomers to observe faint astronomical objects and some of the earliest faraway galaxies or black holes that would otherwise […]

Regular physical activity confers robust health benefits, but many people are insufficiently active. Common cited barriers include a perceived lack of time and access to equipment and facilities. “Exercise snacks” are a style of physical activity characterized by isolated bouts of vigorous exercise lasting =1-min and performed sporadically throughout the day. They can include simple […]

Finding reliable sources of the metals needed for the energy transition is one of the biggest challenges in the minerals sector. This research project focuses on identifying critical metals such as indium, gallium, and germanium in zinc deposits in the Grenville Province (Ontario). These metals, often present as trace elements in sphalerite (zinc ore), are […]

The proposed scientific collaboration is toward developing a new class of porous structure using mathematical design. The structure must be lightweight and capable of removing heat. This structure is advantageous in engineering, such as heat enhancement, heat exchangers, and biomedical engineering (hip, jaw, or femur replacement). The global importance of the proposed research is in […]

Continuous Integration is a software development practice where each member of a team work independently and then merge their changes into a common codebase, at least daily. Each of these integrations is verified through an automated build pipeline, whick consists of a sequence of actions such as compilation, testing, addition of third-party components. The key […]

The Quetico shear zone is an ancient, large, dextral, strike-slip shear zone which has accommodated hundreds of kilometers of displacement. The shear zone has been exhumed from greenschist facies conditions (depths of ~15km) and represents an ancient analogue for active deformation along the San Andreas fault. We plan to use the Quetico shear zone as […]

The research focuses on designing and optimizing hydrogen supply chains (HSC), from production to consumption, to enhance the flexibility, efficiency, and cost-effectiveness, contributing to the global energy transition towards renewable sources. The project will develop and refine mathematical models, validate these models with real-life data, and integrate sustainability metrics to ensure environmental and economic viability. […]

This research aims to advance the field of federated learning by addressing privacy, domain shifts, and personalization challenges, particularly in the context of mobile and digital healthcare. By developing robust and scalable solutions, the proposed framework has the potential to significantly enhance patient care, diagnostics, and personalized treatment while maintaining stringent privacy standards