The excellent mechanical properties and its lightness make graphene a revolutionary material as efficient audio transducers for speakers and headphones. Several studies have reported the superior performance of graphene diaphragm in electrostatic and thermoacoustic transducers [1-2]. However, these graphene diaphragms are produced from expensive methods with low scalability and are not suitable for application in the more popular mechanical transducer.

This research will develop an easy to implement compounding process to produce thermoplastic composites containing delaminated graphene platelets, starting from a proprietary exfoliated graphite product (MesographTM). MesoGraf is a highly-exfoliated product that contains near defect-free, few-layered and multi-layered graphene. Graphene nanoplatelets have high mechanical and conductive properties and can thus impart high strength, electrical and thermal conductivity when combined with suitable polymer matrices.

In this project, the effective life of advanced Li-ion batteries will be assessed using experimental tools and predictive modeling. Li-ion batteries have emerged as an alternative source of energy on-board cars, i.e., electric vehicles (EVs). Unlike internal combustion engine (ICE) vehicles, EVs suffer from performance degradation over driving and idle time posing limitations on their widespread deployment in the market.

Our vision is to develop fiber-optic high-frequency ultrasound generation and detection system for ultrasonic and photoacoustic imaging in biological and biomedical applications such as intravascular imaging in ICU for patients with real-time imaging and monitoring capability.The research will be conducted with our partner organization iNano Medical to provide the need of the spatially resolved ultrasound imaging, for which better location and identification of cancer cells could be offered using our ultrasound generator and detector.

Ultra-High Performance Fiber Reinforced Concrete (UHP-FRC) material, can be considered a promising way to innovate in the management of Low and intermediate level radioactive waste (LILW) storing industry. UHP-FRC exhibits exceptional mechanical, serviceability, and durability characteristics in comparison to its traditional concrete counterparts. The current proposal focuses on the use of UHP-FRC in a new design of high integrity nuclear waste containers considering drop-impact and fire effects. The conceptual design of waste container will be performed using ABAQUS software.

Sanexen Environmental Services Inc. is a Quebec-based industrial partner, specializing in the environmental management of contaminated site remediation and water main rehabilitation. Over the past 30 years, the company has developed a profound expertise, as well as technologies to meet the needs of private and public organizations facing various environmental issues.

Waste heat boilers provide an important function in many industries, taking hot process flows and cooling them down while at the same time creating valuable steam which can be used to save power in other parts of the plant. This project will use Computational Multiphysics Simulations (CMS) to model the inner workings of these important boilers. CMS uses a mix of theoretical and experimental equations to model real world fluids, particularly how they move, boil, and spread heat.

This project is focused on the production of improved deck tiles made of foamed recycled polypropylene (PP) base mat and recycled and virgin polystyrene (PS)/ high impact polystyrene (HIPS) slats that are assembled to the base mat. The current product is available in 12” x 24” and 12” x 12” configurations in a variety of colors. This product is typically installed on high-rise balconies, house porches or decks. Recently, it was reported that the tiles tend to deform after a while. The deformation is usually in the form of center bow down.

Steel production in a modern steel rolling mill involves many steps. A hot rolling process typically starts from a reheat furnace to heat the cold metal to high temperatures (800 to 1000 C or above) so that the softened metal take different shapes when it is pressed. The end products will be used to make, for instances, automotive parts or will be further processed such as to be welded to make pipes. A steel production system may be operated 24/7 non-stop except for scheduled periods of time for system maintenance, etc.

This work focuses on generation a framework to employ a set of 3D coordinates, as the input dataset to the model, and generate the 3D heat map based on the 3D shape. The generated 3D heatmap aims to define the most probable areas for fault categories on the 3D surface. To develop such a system, the 3D shape is printed and the 3D coordinates of simulated faults are recorded using a tool tracker. Then, a machine learning platform is employed to use the 3D fault datasets as the input and produce the probabilities of different fault categories on the given location.