Grants and Contributions

Zinite has developed a specialty n-type thin film transistor with excellent performance suitable for adaptation to work with microwave PCB boards and substrates for compatibility with VCSEL array integration. In turn, this will support high-performance phased-array antenna strucutres suitable for radar and other defence applications.

Remote Canadian defense camps depend on diesel generators that are costly, difficult to supply, and carbon intensive. e-Zinc is developing a breakthrough zinc-based energy storage technology that can provide reliable, multi-day power using abundant, sustainable materials. This project will evaluate how e-Zinc’s long-duration storage can be integrated with renewable generation to create resilient, low-emission microgrids for defense operations in remote environments. The work will define a clear pathway for deploying this innovative solution to strengthen energy security while reducing environmental impact.

Ultimarii will enhance its Canadian-hosted AI platform to support Protected B information handling in support of federal major projects. The project will implement and validate stronger security capabilities, including identity and access controls, data isolation, encryption, audit logging, monitoring, and secure cloud configuration aligned with PBMM requirements. This will strengthen the platform’s ability to operate in government environments where sensitive information, traceability, and secure deployment are essential, while expanding Ultimarii’s ability to support federal departments and related major project initiatives.

Further developing the dual-use atmospheric observation capabilities of the Eagle RPAS drone. The system can replicate threats as well as collect important data on wildfires data for the CSA, ECCC and for globally-respected organizations such as NASA and the US Naval Research Laboratory (NRL).

The firm is developing a smart brake system that prevents rollaway accidents, improving safety and modernization for defence, municipal, and industrial air brake vehicles.

Quantum error correction (QEC) is a central topic in modern quantum science. At its core, QEC is concerned with protecting encoded quantum information from the errors and noise of quantum systems. Operator quantum error correction (OQEC) and the higher rank numerical range (HRNR) compression formalism combine to provide a unified language where QEC code spaces, subsystems, noise processes, and fault-tolerant symmetries are analyzed as compression problems on Hilbert space. In this framework, the numerical range of an operator and its signature norm allow stabilizer, nonadditive, and subsystem QEC code constructions to be treated on equal footing alongside general, non-Pauli noise models. The goal of the Project is to translate this formalism into a practical toolkit for code discovery and analysis. Simultaneously, the Project will develop AIassisted, data-driven workflows to classify and co-design nonadditive and subsystem codes that are optimized for specific noise environments.

The project is a effort to develop A.S. prototypes for Falcon technology verification. Specialized composite fabrication and prototyping support will be provided by an Ontario-based engineering and manufacturing firm with expertise in advanced composite structures for aerospace and defence applications.

This project will advance Canada Rocket Company’s readiness to engage with Canada’s defence sector.

This project explores operational integration for a novel balance and mobility assessment technology aimed at fall prevention and aging in place. Using pressure-sensitive tiles and computer vision with predictive algorithms, the system generates objective, interpretable mobility metrics in community settings. It addresses limitations of current assessments, which are often reactive, subjective, or restricted to specialized labs. The research evaluates these tools and potential implementation pathways such as physiotherapy clinics, senior centers, and long-term care facilities. Grounded in translational research, the project bridges lab-based innovation with real-world application, emphasizing scalable, privacy-conscious solutions that integrate into existing
care workflows. The goal is to leverage machine learning-enabled technology to improve awareness, early detection, and management of functional decline, support caregivers and clinicians, and empower older adults to monitor their mobility and wellness. Findings will inform strategies for broader adoption of digital health tools and commercialization, contributing to sustainable, community-based aging solutions that enhance independence and quality of life.

The aim of the project is to develop new approaches to differential equations with an aim of providing clear exponential advantages for problems in plasma physics, geo physics, optimization, financial mathematics and chemistry. The project will extend current approaches to handle stochastic differential equations and build quantum algorithms for inverse problems where a partial solution is known at different times in the dynamics. These will open up applications in geophysics and financial mathematics that at present are impossible on quantum computers. The team will develop a new mathematical formalism that proves bounds on information propagation speed to simplify both quantum and classical differential equation algorithms, also leading to new methods of simulating relativistic dynamics on quantum computers. Finally, the project will examine applications of these ideas to the aforementioned domain sciences and aim to show clear evidence for an end-to-end quantum advantage that could revolutionize the Canadian economy and scientific community.