Grants and Contributions

This project will test hypotheses and experiment with new mechanisms to establish a reproducible and scalable business process that could lead to new commercial methods in the field of beekeeping.

The project relates to integration of molecular techniques for molecular diagnostics into a fully automated and integrated flow that can be executed with little or no human intervention. The process includes sampling which can cover aerosol or liquid sampling, or liquid sample injection; sample lysis and capture which relates to extraction of biological materials, in particular RNA and/or DNA.

This project aims to develop a scalable white-label reuse platform by creating new consumer-facing systems, client-operated backend infrastructure, and next-generation reusable packaging technologies.

The Project is for rigorous testing of innovative cathode material chemistries developed by the NRC. Innovative cathode materials need validation in high-capacity pouch cell prototypes that can withstand rigorous evaluation for fast-charging performance, thermal stability, and long-term degradation. McMaster University’s role will focus on advanced characterization of prototype cells with novel cathode materials produced by the NRC. The Project will evaluate the new cathode materials using industry-standard application protocols, thereby advancing the technology readiness level of the new chemistries. The Project will include an in-depth evaluation of the prototype cells through thermal, temporal, and spectral analysis. It will provide an insight into the impedance and degradation issues that may arise in the prototype cells during driving and fast charging cycles.

This project will optimize and scale-up the production of the client's proprietary advanced adhesive coating product designed to protect structural assets like steel and concrete from corrosion, fouling and environmental fatigue in a variety of application industries.

Averian will develop an AI Assisted Network Operations solution as part of the SUSTAINET Advance consortium. The project delivers an AI agent powered by fine-tuned LLMs and document embeddings that integrates securely with other Network Management System.

Portcon modernizes port operations by optimizing berthing, communications, and planning; this project deepens those capabilities for greater efficiency and safety.

Software development and pilot demonstration project of an AI-powered Enterprise Asset Management (EAM) platform for public transit agencies. By using predictive analytics, the system will shift transit agencies from reactive to proactive maintenance, extending vehicle lifespan and improving fuel efficiency. This will reduce operational costs, improve service reliability, and lower greenhouse gas emissions by reducing the need for new vehicle manufacturing and decreasing tailpipe emissions. The project supports the growth of a Canadian clean technology solution.

Recent advances in sensor technologies allow the firm to develop a new and unique set of sensors for detecting common aquatic pollutants common in urban and agricultural runoff. Such pollutants are currently measured using expensive and time-consuming laboratory methods. Instead, the firm will create small and inexpensive pollution sensors that take advantage of miniaturized optics, to create a multi-function spectrometer that can detect the new types of harmful algal blooms and climate change-driven increases in dissolved organic carbon that are affecting water treatment plants.

Previous research (funded by CSTIP QSP-019-2) allowed for the development of a brain monitoring device based on advanced time-resolved Near-Infrared Spectroscopy (trNIRS) technology, which demonstrated the ability to measure metabolic activity in the brain-equivalent layer of realistic head models mimicking adult human anatomy. The Project aims to refine the technology and validate its capability to noninvasively monitor cerebral metabolism in adults. The Project Team will conduct a carotid occlusion study in a pig model of the adult head, inducing measurable changes in cerebral metabolism. Data collected with trNIRS probes positioned on the scalp will be compared against direct brain measurements to assess accuracy. Additionally, the device will be tested in adult volunteers performing finger tapping tasks to detect subtle cerebral metabolic changes with trNIRS probes on the scalp, over the motor cortex. The Project will also investigate integrating superconducting nanowire single-photon detectors (SNSPDs) into the trNIRS device to enhance brain sensitivity.