Grants and Contributions

Redesign of platform and interfaces to meet the need of high-net worth customers

The project aims to develop a method for tracking the position of x-ray imaging equipment during orthopedic surgery that seamlessly integrates with the operating room environment.

As part of the international consortium project “[Li-PICK]”, this project will develop a complete process for converting spent lithium ion batteries back into cathode active material (CAM), and battery-grade lithium carbonate.

SMARTBUILD is developing SMARTHEALTH, a total human health and safety platform for our construction management software. SMARTHEALTH features the first industry-specific wearable sensor that attaches to the ratchet suspension of any approved hard hat for monitoring worker health metrics, including body temperature.

Assessment and analysis of business growth plan including marketing and sales process development

The project focuses on developing numerical models (computational fluid mechanics and acoustophoresis) to predict the dynamics of plastic particles in water in the presence of acoustic forcing. The models to be developed as part of the project will identify and quantify the impact of acoustic forcing on the trajectory of microplastics in a confined environment, in order to control their trajectory under a wide range of conditions (temperature, current velocity, etc.). The model developed will then be validated in the laboratory by both the NRC and Polytechnique Montréal. The resulting tools will help the NRC design an instrument capable of controlling the movement of plastic particles and then measuring their size.

The project investigates the applicability and performance of fault-tolerant quantum computers in solving stochastic and partial differential equations motivated by generative modelling in artificial intelligence (AI). These differential equations arise as models of non-equilibrium dynamics in dissipative physical systems and provide the foundations of recent revolutionary AI models such as diffusion models. More generally, the project views the associated computational tasks as transports of ensemble states in stochastic thermodynamics and compares the performance of quantum algorithms with the fundamental limits of efficient generation of target ensembles by any machine, whether they are unitary and closed, or dissipative and open, quantum or classical, and artificial or biological.

The project investigates the applicability and performance of fault-tolerant quantum computers in solving stochastic and partial differential equations motivated by generative modelling in artificial intelligence (AI). These differential equations arise as models of non-equilibrium dynamics in dissipative physical systems and provide the foundations of recent revolutionary AI models such as diffusion models. More generally, the project views the associated computational tasks as transports of ensemble states in stochastic thermodynamics and compares the performance of quantum algorithms with the fundamental limits of efficient generation of target ensembles by any machine, whether they are unitary and closed, or dissipative and open, quantum or classical, and artificial or biological.

The aim of this Project is to support the development of an instrument that can be deployed in the marine environment and can detect, measure the size of and characterize ocean microplastics in situ and in real time, to improve the measurement and monitoring of this type of ocean pollution. This will entail the development in the laboratory of underwater spectroscopy and imaging techniques for detecting, measuring and characterizing particles under significant seawater flow conditions and the laboratory demonstration of this technology using a prototype.

First, an LCA-based environmental assessment is required for anticipated battery and battery material production processes in Canada to establish a baseline for benchmarking, but this has not been previously conducted. Second, an early stage LCA framework is required for the evaluation of new battery materials and processes proposed under the NRC’s Critical Battery Materials Initiative (CBMI). Third, the evaluation of both anticipated large scale battery production and new materials and processes requires Canadian background life cycle inventory (LCI) datasets including electricity, fuels, basic raw materials, chemicals, waste processing and water production.