Innovative Projects Realized

Explore thousands of successful projects resulting from collaboration between organizations and post-secondary talent.

13270 Completed Projects

1072
AB
2795
BC
430
MB
106
NF
348
SK
4184
ON
2671
QC
43
PE
209
NB
474
NS

Projects by Category

10%
Computer science
9%
Engineering
1%
Engineering - biomedical
4%
Engineering - chemical / biological

Direct Lithium Extraction (DLE) from brine solution using electrochemical method

The demand for lithium-ion batteries (LIBs) is on the rise, mainly due to increased interest in portable devices, electric vehicles and grid-storage applications. The key component in such rechargeable batteries is lithium, which is trivial from the name itself as well, as lithium-ions shuttle back and forth during charging/discharging process. Consequently, lithium production demand has increased significantly as well over the past few decades. Lithium is usually extracted from minerals or water sources etc. Due to the limited availability of minerals and high-production cost. Therefore, most of the lithium is extracted from its water sources (such as salt lakes, seawater etc.). Likewise, most of the current industries extract lithium via solvent-evaporation method. This method takes a long time (12 – 18 months) to produce battery-grade lithium, which is inefficient, costly and highly weather dependent. Therefore, over the past few decades, new methods have been developed. Among them, using an electric force to capture and release lithium-ions selectively has gained interest of several investigators due to its simple operation, low cost and eco-friendly nature. Similarly, LiEP energy has recently used this technique to develop a cost-effective method to produce battery-grade lithium.

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Faculty Supervisor:

Venkataraman Thangadurai

Student:

Majid Rasool

Partner:

LiEP Energy

Discipline:

Chemistry

Sector:

Professional, scientific and technical services

University:

University of Calgary

Program:

Accelerate

Implementation of an Optimal System for the Detection and Avoidancesystem on an Unmanned Aircraft System

Remotely Piloted Aircraft System (RPAS) will be essential in developing and monitoring Canada’s territories. This is in part due to a lack of suitable human pilots due to skill shortages and difficult conditions making recruitment difficult; there are also “dull, dirty and dangerous” aspects of the missions that make a remote pilot operation safer. Miniaturization, machine learning and robotics are all fields which may contribute to overcoming these challenges in new and affordable ways. In this research project, we propose to research and implement an obstacle avoidance system which allows the unmanned aircraft to detect and avoid flying obstacles using an air-to-air radar setup.

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Faculty Supervisor:

Witold Kinsner

Student:

Hongru Li

Partner:

Aurora Solutions

Discipline:

Engineering - computer / electrical

Sector:

Manufacturing

University:

University of Manitoba

Program:

Accelerate

A computer-aided decision-making tool for Powder Bed Fusion AdditiveManufacturing (PBF-AM) process selection using Multi-Criteria DecisionAnalysis (MCDA)

Precision ADM is a global engineering and manufacturing solutions provider who uses Additive Manufacturing as a core technology, complemented by multi-axis machining to manufacture high value components and devices for the medical, aerospace, energy, and industrial sectors. Precision ADM specializes in PBF based additive manufacturing. For that reason, Precision ADM wants to design and develop a cost-effective and customized computer-aided decision-making tool for the AM process selection, particularly for powder bed fusion additive manufacturing (PBF-AM) processes. The tool would consider the manufacturability of parts by additive manufacturing, and the selection of an optimal method based on capabilities of PBF-AM processes.

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Faculty Supervisor:

Qingjin Peng

Student:

Waleed Safdar

Partner:

Precision ADM

Discipline:

Engineering - mechanical

Sector:

Manufacturing

University:

University of Manitoba

Program:

Accelerate

Long-term rattlesnake population trends in response to land management regime changes

Monitoring of wildlife populations is essential for identifying declines or changes, especially in response to habitat changes or disturbance. By comparing historical and modern populations, we can quantify long-term trends. In this study we are comparing historical data from the mid-1980’s to modern to identify trends within a population of Western rattlesnakes (Crotalus oreganus). During the previous study, the landscape was managed as cattle grazing land with negligible human presence. Immediately following the study in 1985, management of the landscape changed so that half of the rattlesnake population remained on grazing lands, and the other half are now within the boundaries of a provincial park dedicated to recreation. This allows for a comparison of how the population has changed over 35 years, and how these different land management styles may have affected these changes. Working with Coldstream Ranch as part of this research, we will create a best management plan that helps educated rangeland employees on rattlesnakes and promotes stewardship and safe working environments for humans and wildlife. We also will develop a seasonal habitat use map to identify areas of high importance to rattlesnakes to inform future grazing plans to protect both livestock and threatened rattlesnakes.

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Faculty Supervisor:

Karl Larsen

Student:

Marcus Atkins

Partner:

Coldstream Ranch

Discipline:

Environmental sciences

Sector:

Other

University:

Thompson Rivers University

Program:

Accelerate

Weed and Crop Leaf Area Estimation for Variable Rate Applications

Precision agriculture practices increase productivity while rationalizing farm inputs. It mitigates the adverse impacts of chemical inputs on the environment. The variable rate is one of the commonly used precision agriculture practices where inputs are applied based on site-specific needs. CropPro Consulting uses soil properties like electrical conductivity, topography, and water flow patterns to generate a single layer SWAT map categorizing land into 10 zones. These SWAT maps are used for variable rate seeding and fertilizers. The goal of this research project is to develop deep learning models for variable rate herbicide using limited ground imagery and SWAT maps. A pilot study had already been conducted to explore this potential. This research project will extend the concept for a wide range of crops in Prairies and integrate the developed solution in the SWAT map workflow. The developed workflow will help CropPro Consulting in commercializing variable rate herbicide application.

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Faculty Supervisor:

Abdul Bais

Student:

Muhammad Hamza Asad;Vincent Chan

Partner:

CropPro Consulting

Discipline:

Engineering

Sector:

Agriculture

University:

University of Regina

Program:

Accelerate

Nanophosphor-based coatings for high resolution microLED displays.

MicroLED displays are of growing interest and are seen as a next generation display technology for leading-edge displays of all sizes, from head-mounted displays for virtual reality through portables (watches and cell phones) to televisions and wall-size displays.
Red, green and blue light emission from blue-emitting Light Emitting Diodes (LEDs) would replace the use of discrete red, green and blue-emitting LEDs to simplify the construction of microLED displays. Currently, such LEDs are made using gallium indium nitride, gallium indium aluminum phosphide and gallium arsenide compounds that are expensive to produce. Instead we are seeking to use low cost blue light emission from gallium indium nitride LEDs only, combined with phosphor colour conversion nanophosphor pastes to be used in this project.

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Faculty Supervisor:

Adrian Kitai

Student:

Samuel Peter

Partner:

DTEK

Discipline:

Engineering

Sector:

Manufacturing

University:

McMaster University

Program:

Accelerate

Effect of carboxylated cellulose nanocrystals on the mechanical properties oflatex-based pressure sensitive adhesives

This project proposes the use of carboxylated cellulose nanocrystals (CNCs) – developed and manufactured by Anomera Inc. from Canadian forests – as nano-inclusions to tailor a set of properties in latex-based PSA nanocomposites towards enhanced performance. Due to their unique properties, CNCs can significantly enhance the mechanical performance of latex-based PSAs.
Project results are expected to promote the use of Anomera’s CNC material in the adhesives industry, as well as to promote the Canadian forest sector as Canada is considered among the global leaders in the exportation of forest products.

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Faculty Supervisor:

Marc A Dubé

Student:

Vida Gabriel

Partner:

Anomera

Discipline:

Engineering - chemical / biological

Sector:

Manufacturing

University:

University of Ottawa

Program:

Accelerate

Microbial carbonate precipitation by autotrophic and heterotrophic bacterial species for crack prevention of overlaying concrete

Because of the crack’s appearance in concrete over time, the concrete strength decrease. To prevent deterioration and heavy costs of reparation, concrete chemical additives are usually added but their cost are prohibitive and not very sustainable along time. Successful research projects have been using encapsulated bacteria in the concrete which reactivate at the contact of air and water -when cracks appear. These bacteria multiplicate in the cracks and die which create a precipitation and fill the cracks. These bio-based solutions make it possible to consider a self-healing concrete, which is more sustainable.
Our research project aims to assess cyanobacteria’s precipitation properties for self-healing concrete. Photosynthetic cyanobacteria grow by capturing carbon dioxide and have already shown their great potential of microbial precipitation. Longer and real tests in concrete should be done to estimate their performance and capacity to heal cracks compared to other existing additives.

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Faculty Supervisor:

Maria Dittrich

Student:

David Aceituno-Caicedo

Partner:

Antex Western

Discipline:

Geography / Geology / Earth science

Sector:

Construction and infrastructure

University:

University of Toronto

Program:

Accelerate

Investigation of interactions between biobased wax emulsions and pMDI wood adhesives

Wax emulsions are widely used in conjunction with wood adhesives to improve overall dimensional stability of the resulting wood products. In this study, we will investigate kraft lignin and waste tallow as sustainable, biobased partial replacements for fossil fuel derived wax. These renewable, hydrophobic materials can be formulated into a wax emulsion using conventional emulsification chemistry. Due to the chemical structural difference between a fossil fuel derived wax and kraft lignin and tallow, we will explore interactions between these biobased wax emulsions and pMDI resin, with a special focus on curing characteristics and wood bonding performance. Results from this project will shed light on potential chemical and physical interactions among various components of the wax emulsions and pMDI adhesives. Insights gained from this study will be highly beneficial for designing new biobased wax emulsions for the wood products industry.

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Faculty Supervisor:

Ning Yan

Student:

Heyu Chen

Partner:

Walker Emulsions

Discipline:

Forestry

Sector:

Manufacturing

University:

University of Toronto

Program:

Accelerate

Geometric Deep Learning of Volatility Surfaces

Options are financial instruments that are used to manage risk, hedge investments, and speculate. The value of these options depends on the price of the underlying asset and a multitude of different variables. As a result, pricing models can become complex, requiring infeasibly expensive routines or simulations to be run to price a single option. One reason this procedure can be slow is that the model’s parameters need to be tuned to the market’s current conditions, reflected by an implied volatility surface (IVS), which gives the value of options with different parameters. While the IVS has been researched extensively, it is still not understood well. We propose the use of deep learning to better understand the IVS, and plan to release our models to the public for future research. Riskfuel creates options pricing tools using deep learning, and will be using the model for accelerating pricing.

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Faculty Supervisor:

Andreas Veneris

Student:

Nicholas Fung

Partner:

Riskfuel

Discipline:

Engineering - computer / electrical

Sector:

Professional, scientific and technical services

University:

University of Toronto

Program:

Accelerate

Algorithmic and Interface Advances in Computer Algebra

Computer Algebra Systems (CAS), with their unique ability to analyze and solve mathematical problems, are gathering new communities of users, who challenge them with more and more complex tasks. It is necessary, therefore, that the core engines of CAS implement state-of-the-art algorithms. At the same time, CAS need to build new bridges to specialized software and to develop interfaces to emerging research areas. This proposal capitalizes on the research conducted by academic partners at the University of Western Ontario in order to strengthen and extend the technology of their industrial partner, Maplesoft, the developers of Maple, one of the leading CAS world-wide.

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Faculty Supervisor:

Marc Moreno Maza;Robert Corless;David Jeffrey;Gregory Reid

Student:

Mohammadali Asadi;Ana C. Camargos Couto;Delaram Talaashrafi

Partner:

MapleSoft Inc.

Discipline:

Computer science

Sector:

Information and cultural industries

University:

Western University

Program:

Accelerate

Geomicrobiological assessment of advanced customizable leach columns

Acid mine drainage (AMO) is a significant environmental concern at many hard rock mines. Laboratory-based predictive tests are used to determine if AMO will be generated by mine wastes, but these tests do not generally examine the role of microbes in acid-generating processes. This study will extend the capabilities of the advanced customizable leaching columns (ACLCs) developed by M.A. Okane Consultants Inc. to include microbiological factors. We will use a combination of geochemical, mineralogical, and microbiological analyses to compare the ACLC tests to field waste rock conditions. The results will be used to improve existing methods used for predictive testing and enhance Canada’s capacity to manage mine waste responsibly in the future. The two interns will be trained in setup and sampling of ACLCs, and the projects will provide them with experience analysing data from these systems, and the opportunity to build their network and gain some hands-on industry experience.

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Faculty Supervisor:

Benoit Plante;Joyce McBeth

Student:

Gary Schudel;Colin Burelle

Partner:

M.A. Okane Consultants Inc.

Discipline:

Environmental sciences

Sector:

Professional, scientific and technical services

University:

Program:

Accelerate

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