Considering the continually growing energy demands and concerns about climate change due to anthropogenic CO2 generated from fossil fuels, there has been a global endeavor to transition towards low-carbon renewable energy sources, particularly photovoltaic technologies. Organic solar cells (OSCs) are ideal candidates for low-cost PV technologies thanks to the possibility of large-scale device fabrication by solution printing or coating techniques. Though OSCs cells have achieved remarkable progress in the last few decades, stability, efficiency, and cost issues hinder their commercialization.

The global demand for clean energy and energy security is increasing, in the context of extreme weather events and global unrest. Distributed and intermittent energy sources (e.g., solar, wind) can provide much needed renewable generation but complex power conversion and storage systems are required to transform raw unregulated power into quality power needed to supply loads and inject power into the grid uninterruptedly.

This research project aims to employ advanced machine learning and data science models for Developing Proprietary Natural Resource Business Models for Identification of Feedstocks Susceptible to a By-Product First Solution.

Carbon is a component of CO2, an important greenhouse gas (GHG) responsible for climate change. Forests store more carbon than is found in the atmosphere, with most of this stored in the soil. This ability to store carbon has led to many tree-planting projects across Canada including a large-scale tree restoration program led by Reckitt Benckiser Canada. But there are important knowledge gaps before forest soils can be counted towards emission targets. Critically, past land-use (e.g., agricultural) can influence a forest’s ability to store carbon.

The challenges brought by future smart grids require efficient and large-scale real-time cyber-physical simulation, which should utilize variable time-stepping algorithms and cyber networks. Heterogeneous hardware such as ACAP is a trending solution to deal with the challenges. The project is aimed to convert traditional FPGA-based real-time EMT simulation to a large-scale heterogeneous adaptive time-stepping simulation with the flexibility to integrate the cyber-layer simulation.

The Canadian Bank Note (CBN) is interested in a laser printing solution to create high resolution colour images in the bulk of ID documents. One approach the CBN will investigate in collaboration with the University of Ottawa is to use plasmonic nanoparticles that will generate colours upon laser irradiation. These nanoparticles will be embedded in a polymer matrix and irradiated with a laser to create colours.

Patients with end stage kidney disease require regular intermittent dialysis treatments to remove fluid and sodium. During hemodialysis, blood is pumped through a dialyzer containing semipermeable microfibers, while clean dialysate flowing along the outside these fibers removes waste products and fluid.
However, sometimes hemodialysis cannot effectively remove all sodium and fluid, resulting in a deposition in tissues and bone and a higher risk of cardiovascular complications.
This project investigates the efficiency of a combination of hemodialysis and peritoneal dialysis.

Today, construction activities have resulted in the depletion of vast amounts of non-renewable resources that cause climate change which is one of the most pressing environmental challenges of our day. The construction industry is a major source of greenhouse gas emissions globally. Sustainable construction is now mainstream, necessitating the investigation of environmentally friendly construction materials like cellulosic fibers. One of the potential applications of cellulose fibers is in development of cement-based composites.

NeoSpina Health Care Inc intends to contribute to unprecedented treatment techniques for LBP by developing a novel medical device and investigating acquired data from treatment procedures. Accordingly, the main objective of this project is to develop a non-invasive robotic device to treat a wide array of spinal conditions while reducing the treatment duration compared to conventional methods. The device will be equipped with motor actuators and force sensors, permitting interaction with the patient’s lumbar spine and data acquisition in real-time, which entails an appropriate design.

The Energy potential of water has been successfully harnessed to produce electricity since the late 19th century. In 2018, hydropower production accounts for approximately 61 % of the total electricity produced in Canada. To exploit this source of energy, water is stored in dams and is strategically used based on hydrological cycles. Over the years, researchers around the globed have devised sophisticated mathematical tools to efficiently manage hydropower systems thanks to advancement in both Mathematics and Computer Science.