Grants and Contributions

This project follows 2 previous, successful IRAP projects (959593 VPT HRES-SI Prototype Sprint 1, 959593 Proof of Concept). In the first project the original hardware was developed & the Inverter prototype was built. In the 2nd, the HRES-SI component went from a mechanically proven prototype to a working proof of concept.

In this project the architecture will be adapted to a standalone inverter product, complete the programming, continue safety analysis, and develop the inverter through a series of demos and tests and the resulting product revisions. The Firm will also identify and prove out integrating products like grid tie switches, batteries, microinverters, solar panels and the inverter case and cabling.

The project will focus on the development of predictive intelligence software functionality which will utilize business process automation metadata to provide Salesforce product owners with product recommendations to help them increase their return on investment from Salesforce purchases.

The ongoing race to carbon net-zero is a global effort to resolve the
challenge of climate change. Carbon neutrality can be achieved by reducing
emissions and removing the CO2 in industry exhaust as well as the
atmosphere. Removing carbon in the atmosphere is called direct air carbon
capture (DACC) and can be viewed as an emerging industry producing
carbon credit.
This project seeks to design a novel DACC system based on fibrous
material. The alkaline solution is dispensed by fiber networks and reacts
with and captures the CO2 in the atmosphere. Optimal design for such
processes is prohibitively demanding for conventional methods,
experimental or computational, due to the drastic scale difference (e.g.,
from alkaline droplets and liquid film of micrometers to meters long fibers
and reacting chamber) in the system. Developing a universal framework
combining artificial intelligence and physical laws within this project will
facilitate faster optimal designs and scaling-up for future DACC system
development.

The goal of this Project is to develop membrane electrode assemblies (MEAs) at scale, comprised of advanced ionomers which allow for high efficiency and durability in an optimized CO2 electrolyzer architecture. This Project leverages progress made at the University of Toronto (UofT) and Simon Fraser University (SFU) in device and material development. At UofT, tremendous progress has been made in terms of system, cell, and component design. At SFU, expertise in the creation of new materials and extensive material screening and characterization for CO2 electrolyzers has allowed creation of a high-performance ionomer chemistry platform. CO2 electrolysis durability and component testing capabilities at contributing NRC facilities, as well as their experience in scaling up cell production will enable knowledge transfer from academia to industrial partners. Two Canadian SMEs (CERT Systems Inc. and Ionomr Innovations Inc.) that are committed to the commercialization of CO2 electrolyzers will ensure scalability of the approach and provide economic perspective for material and cell development that will lead to a pilot scale CO2 electrolysis technology.

With TRANSIS V5, the Firm will design and develop an integrated OT (Operations Technology)/IT (Information Technology) transport information management system for commuter trains, buses and tramways, which manages both operational and passenger information.

The project will support development of intellectual property capacity within the firm.

Implement new generative content and match Canadians with the most suitable financial product providers more accurately and efficiently.

The creation of a semi-continuous battery slurry mixer and related components (feeders) to integrate slurry materials and to extract the slurry to produce battery cells for the EV market. The system will allow for variable mixing volumes and include advanced data tracking, which is currently not offered by others. The project will work with a battery manufacturer to test the battery slurry mixer in a manufacturing environment.

Development of AI prototypes for Factory Bucket's transition from a 'Product-enabled service provider' to a 'Product provider'. The AI Assistant will allow manufacturers to develop applications on the Cohesiv platform.

This project involves optimizing the mechanical performance of food-waste derived biopolymers to meet processing and lifecycle requirements.