This project aims to advance soft robotic research by developing innovative control mechanisms built from a gelatin-based biogel. Soft robots can deform to navigate through constrained spaces and perform complex tasks in unstructured environments, without the need for complex control. This makes them ideal for a wide range of applications in dynamic environments, including medical […]

This project focuses on improving the component quality after Laser Beam Machining (LBM) for HS188 (AMS5608), a superalloy critical in aerospace and power generation due to its high strength and corrosion resistance. LBM often leaves a recast layer, a residue of resolidified molten material on the side edges, which weakens the material’s strength and corrosion […]

The budding field of soft robotics, robots made of elastic materials such as rubbers or silicone, currently represents a 1.48 billion market size with a compound annual growth of 34.45%. The problem is that there is no specialized tool for the design and simulation of soft robots. Our research has already demonstrated a promising simulation […]

Dissimilar-material joining is becoming increasingly sought after in several industries – including automotive, aerospace, and rail – due to the potential to improve vehicle weight reduction and efficiency while maintaining safety and structural strength. Resistance Spot Riveting (RSRTM) is a novel joining technology designed to enable inexpensive, efficient, and effective dissimilar-material joining. As it stands, […]

The development of low-power, printed gas sensors is revolutionizing the monitoring of harmful gases like CO2 across various industries. This innovative technology offers a real-time, advanced, and cost-effective solution for detecting and measuring gas levels, significantly enhancing environmental monitoring and industrial process optimization. Utilizing resistance-based and electrochemical sensing approaches, these sensors are part of a […]

Printed electronics has the potential to deliver low-cost, high-volume fabrication of electronic devices, but is currently held back by the lack of a specialized quality control solution. Today, verification of functional properties such as conductivity is done with teams of technicians using simple multimeter probes, lacking the speed and accuracy required to characterize roll-to-roll production. […]

Graphene is a promising new nanomaterial, single layers of graphite, with superior physical and electrical properties making it an ideal candidate for electrical applications; however, current graphene production methods are expensive and complicated. As a result, new materials that have similar properties to graphene, but are more amenable to high-yield production are currently being investigated. […]

Computational chemistry is a powerful tool in the development of new pharmaceuticals, materials, and batteries. With accurate and fast computational methods, one can predict the physical and chemical properties of a molecule without having to prepare it in a laboratory and perform experiments, which can yield dramatic time and cost savings. However, the chemistry of […]

Il s’agit de la réingénierie des processus d’affaires du service de l’Ingénierie, plus particulièrement des processus de développement de produits dans le domaine de la fabrication dans le transport ferroviaire. Révision et mise à jour selon les dernière pratiques dans le but d’atteindre les objectifs stratégiques de l’entreprise.

While OLED displays are now a relatively-mature technology, they have been almost exclusively targeting consumer electronics. As such, the ultimate goal of this ambitious collaboration will be to: Evaluate the technology and supply chain readiness of actual OLED and other emerging display technologies. Assess their potential for cockpit (critical) and cabin (passenger-level) aeronautics and train […]

Assurer un processus de production capable de maintenir une stabilite dimensionnelle des produits fabriques avec un minimum de variance, en reduisant l’ecart de longueur standard entre le min et le max, en minimisant les pertes provoques pour les productions hors norme et etre le plus innovant dans les procedes et les methodes de travail. Le […]

This project aims to develop a large, labelled dataset of normal canine behaviour for use in developing machine learning algorithms to detect abnormal animal physiological behaviour. These machine learning algorithms will enable veterinarians to collect high-quality data of their patients in their natural environments. This innovative solution has the potential to improve the quality of […]