Grants and Contributions

Victory Advanced Technologies Inc. (VAT) will conduct exploratory research to assess opportunities in the rapidly growing unmanned aerial vehicle (UAV) sector, with a focus on heavy-lift drone propulsion and related technologies.

This project strengthens the company's readiness to enter the Canadian defence market by building on its IDEaS demonstration and related ecosystem activities. It focuses on developing defence‑specific technical materials, engaging with CAF, DND/DRDC, and industry partners, mapping defence market opportunities, and initiating security and compliance preparations for future contracts.

This project will assess how the firm's underwater robotic platform can be adapted to support defence and Coast Guard vessel inspection and in-water hull maintenance.

Adapting our custom stealth battery electrical side by side from agriculture market toward military variant will allow for secure supply chain platform that is modular and scalable with integration of defense technology. The 100% Canadian IP platform has evolved to allow for simplistic manufacturing and NATO friendly drivetrain integration to allow for robust manufacturing plan for defense. The rugged drive performance, power of the initial vehicle allow for a harsh/variable drive conditions that can include steep inclines, mud/sand/snow, heavy payload under towing. The initial design upgrade has included an autonomy kit to allow for driverless steering options for things such as soldier retrieval or perimeter monitoring/drone defence.

The project aims to classify high-performance quantum codes by developing and evaluating a suite of benchmarks based on the arithmetic and memory operations required for cryptographic applications. These benchmarks will provide a systematic way to compare different quantum error-correcting codes in terms of their computational efficiency and practicality for large-scale use. By focusing on performance metrics relevant to cryptographic workloads, the project will identify which codes best balance qubit efficiency with computational capability. The outcomes will support informed decisions on the suitability of emerging quantum codes for real-world applications and guide future directions in quantum computing and security research.

The project strengthens Canada’s domestic capability in technical PPE design and production of protective equipment for remote, resource-constrained, & northern operating environments experienced in defence operations. The initiative supports supply chain resilience, operational readiness and Canada’s manufacturing.

The measurement of analyte concentration in aqueous media is typically performed by analytical laboratory methods, which are slow and costly. Applications such as indoor farming, including hydroponics, require a solution that can provide nutrient analyte measurements in real-time, on-site and in a cost-effective manner. Quantum materials, such as graphene and carbon nanotubes (CNTs) where the material is surface, combine quantum transport properties with sensitivity to surface chemistry ideally suited to sensing applications. Consequently, graphene and CNT sensors have enabled many improvements in sensor response. The Project is aimed at developing new concepts in graphene field effect transistor (FET) based sensors to simultaneously achieve the sensitivity, selectivity and stability required for applications such as controlled environment agriculture. This work leverages the expertise, experience and infrastructure of the applicants at McGill University, Université de Montréal, Cégep de SaintJérôme, and the NRC.

This project aims to purchase a tractor, irrigation system, work tables and garden supplies to provide more food to Moisson Montreal and partner organizations for distribution to at-risk communities.

This project aims to purchase and install greenhouses in community gardens.

Support: The project aims to finance the development of bocce courts located in the major parks of the Borough of Saint-Léonard, as well as at the Saint-Léonard Sports Complex.