This program will focus on the detailed characterization of the luminescence of a series of next-generation doped phosphors for lighting applications. These narrow-band-emitting, high-efficiency phosphors have demonstrated outstanding potential for use in phosphor-converted light emitting diodes. This technology is poised to replace traditional incandescent lights and it is expected to lead to an outstanding reduction of 15% in global energy consumption in the lighting sector with substantially greater long-term reductions.
Le stockage de l’énergie renouvelable variable et le remplacement du gaz fossile pour le chauffage des procédés industriels sont deux des plus grands défis techniques de la transition énergétique. Un système économique de
stockage de chaleur à haute température pourra répondre simultanément à ces deux besoins. Ce projet vise à reprendre la technologie de stockage aux sels fondus déjà employés dans les immenses centrales solaires à concentration, et de l’adapter aux besoins des usines canadiennes.
Sensor Based Sorting is a relatively new technology for the mining industry. The ability to use sensor to classify particles or bulk materials ahead of expensive downstream grinding and separation has many benefits including reduced energy and water usage, reduced operating costs and improved metal recoveries. Testing to assess sorting for a mineral deposit is normally conducted by the technology companies and there are no standard approaches to conducting such studies. The proposed study builds off of more than 20 years of research
experience to advance sensor based sorting.
The proposed research aims to 3D print a series of heat exchangers in plastic and metal to optimize the pressure drop and heat transfer. An initial prototype will produce experimental data to validate a numerical model, which can then be used to rapidly evaluate future heat exchanger designs. Optimizing the pressure drop and heat transfer will lead to an increase in energy efficiency of the heat exchanger.
This project is a collaborative effort between an industry partner and Memorial University to address the issue of oil spill detection and monitoring using predictive modeling approaches. The project is partly funded by MITACS and in part by an industry partner. The input data are taken from the literature and also captured by some physical monitoring devices such as drones, active/passive cameras and sensors, and satellites. Some smart models will be developed, trained, and tested during the course of this project, and will be used for forecasting and monitoring the oil spill incidents.
Financial institutions ensure borrowers’ ability to repay the loan before lending them for the pursuing projects. The ESSAFIN Logic 1.0 software tool is available for evaluating loan proposals based on the Environment, Social, and Governance (ESG) criteria. The tool has a potential for improvement to account for the lack of critical practical application and evidence-based literature support.
Enabling Analog Artificial Intelligence by the systematic generation of Analog Neural Networks from well-known Artificial Intelligence software tools. The circuits and methodologies developed here enable “AI at the Edge” meaning local, low power, analog AI that provides, for example, medical devices that analyse signals to asses the need for intervention; voice recognition devices that do not send recordings to the internet; smoke detectors that recognise the chemical composition of gas in the air and similar.
As Internet usages are proliferating communications networks are faced with new shortcomings. Future networks will have to support in 2020 mobile traffic volumes 1000 times larger than today and a spectrum crunch is anticipated. Wireless access rates are today significantly lower than those of fixed access, which prevents the emergence of ubiquitous low cost integrated access continuum with context independent operational characteristics. Communication networks energy consumption is growing rapidly, especially in the radio part of mobile networks.
Closed landfills are a source of uncontrolled methane (CH4) emissions negatively add to the impact of greenhouse gas emissions. These methane emissions can continue for decades after biogas extraction systems reach end-of-life. Successful land reclamation projects, such as turning an old landfill into a park, depends on low-maintenance technologies that can cope with these emissions.
Ananda Devices has developed an innovative technology to produce high-throughput organ-on-chip technology for
commercialization in the pharma industry and cosmetic industry. For cost effective and fast commercializing the device, semi
automation/automation is required for the high throughput data analysis. Further validation of the automation algorithm is
required for data accuracy.