Grants and Contributions

The design of a high-performance micro-electromechanical system (MEMS) requires extensive design simulation to optimize its performance. Complex MEMS implementations, such as in adaptive optics (AO) systems, have multiple competing specifications and structural parameters to optimize. Skilled designers often spend many months of effort to develop such MEMS systems, with design effort often stopping when performance is sufficient as opposed to fully optimized. This slows and limits innovation in applied MEMS technology areas. This Project will focus on the development of AI using multi-objective optimization to automate the design and optimization of complex MEMS systems. The multi-objective MEMS performance problem is one where AI will provide dramatic benefits and significantly accelerate innovation.

The aim of this Project is to generate flexible-use, automated devices for rapid and efficient SARS-CoV-2 genome sequencing in order to enable early detection and molecular epidemiology studies to inform public health policies. The device will be based on the PowerBlade system and should be able to perform complex molecular steps, from virus RNA reverse transcription, to PCR amplification and library preparation for rapid sequencing by nanopore technology. The Loop-mediated isothermal amplification (LAMP) reaction will also be adopted in combination with nanopore sequencing and applied in the form of a sequencing based rapid molecular test. These devices will be suitable for rapid deployment in the case of COVID-19 threats, as well as future threats in public health laboratories, diagnostic laboratories in hospitals, genomics laboratories and sequence service providers in academia, and the private sector, as well as suitable for point-of-need deployment, including remote locations. The combination of PowerBlade and Nanopore represents a potential flexible, mobile solution, which allows deployment in locations that do not have substantial genomics infrastructure, and therefore, enables the wide use of this system. This should enable low cost-fast turnaround genome sequencing and targeted sequencing in order to identify high risk SARS-CoV-2 virus variants in response to outbreaks and inform public health authorities.

Yellow pea is one of the key pulses grown in Western Canada with considerable interest from the food industry.

The use of robotics in orthopedic surgery substantially reduces the patient recovery time and enhances the operation’s efficiency, reliability, autonomy, and standardization. Despite these advantages, issues such as cost, safety, and training must be addressed before Robot-Assisted Orthopedic Surgery (RAOS) becomes widely available. This Project will employ a digital twin approach to help reduce the cost and increase the safety of RAOS technology. Offline and in-process computer simulations are a key part of the current RAOS systems. This Project seeks to enhance these simulations by integrating the process physics (e.g. forces, temperature, vibrations). Specifically, the Project focuses on combining physics-based and data-driven methods to develop high-fidelity and high-efficiency models of the process physics during RAOS. These models will then be used to develop a pilot software, ultimately leading to the envisioned digital twin.

This project aims to develop a novel Thermographic Phosphor Streak Velocimetry (TPSV) diagnostic capable of non-invasive, simultaneous 2D temperature and velocity measurements. With ultra-high spatial resolution, it is capable of unprecedented accuracy and applicable to a range of complex real-world problems such as heated jets, boundary layers, and two-phase flows.

The signal
classification and novelty detection will enable rapid response to new interfering events ensuring DRAO remains a unique location able
to carry out transformative radio science in Canada.

The group at OVGU Magdeburg will lead the development of the proposed Thermographic Phosphor Streak Velocimetry technique. The team will apply the diagnostic to heated laminar and turbulent air and validate it against the conventional Thermographic Particle Image Velocimetry. Additional experiments on a heated boundary layer will be set-up in Magdeburg to apply the technique in a challenging near-wall configuration, and the results will be compared the results of synthetic streak simulations performed at Polytechnique Montreal. The team at OVGU Magdeburg will also work closely with the NRC to both implement the TPSV system at the NRC and set up the two-phase flow experiment.

To characterize the performance of the proposed thermographie phosphor streak velocimetry (TPSV) technique, high-fidelity numerical
flow simulations will be performed at Polytechnique Montréal. The flow configuration will consist of a turbulent boundary layer
developing over a heated fiat plate. Synthetic TPSV measurements will be implemented using a particle tracing algorithm to provide
fine-grained validation and characterization of the experimental technique. Furthermore, the synthetic measurements will provide
information otherwise inaccessible from experiments, such as the rôle of 3D effects and potential slip velocity between the particles
and the surrounding flow.

The National Research Council of Canada (NRC), in collaboration with Environment & Climate Change Canada (ECCC), Health Canada (HC) and Natural Resources Canada (NRCan), is seeking solutions for the manufacture of compostable disposable surgical masks and compostable disposable respirators to be used by healthcare workers.

In cannabis, specialized structures on flowers produce unique compounds with medicinal importance. This project will investigate the physical and chemical landscape of these surface structures through the application of 3D imaging and synchrotron light technologies, revealing how the broad range of medicinal compounds are sequestered on cannabis flowers. Funds will be used for research costs related to chemical testing of plant samples.