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

Recycling of Urea-Formaldehyde Resin-Bonded Particleboard and MDF

The large global production quantity of particleboard and medium density fiberboard (MDF) creates equal quantity of particleboard and MDF waste after completing their service life. Given increasing demand for green products and the new government’s environmental policies, it is urgent to develop technologies to recycle these used composite panels into valuable raw materials for manufacturing composites again.
This research will focus on the development of recycling solutions for waste Urea-formaldehyde (UF) resin-bonded particleboard and MDF.
Thermohydrolytic (treated with steam and heat) treatment with chemical catalyst will be applied to recycle the waste particleboard and MDF. And the recovered particles or fibers will be used as raw materials with different substitution of fresh materials to manufacture particleboard or MDF panels. The quality of the resulting particleboards or MDF will be evaluated by determining their performance and formaldehyde emissions.
Moreover, this research will lead to develop a complete environmentally friendly recycling process. Waste mixture aqueous produced during the wood panels recycling, which is rich in chemicals, will also be separated and purified to recover the chemicals.
This project can accelerate innovation process for recycling waste UF-bonded wood composite panels and facilitate the collaboration between FPInnovations and the industry, governments and Laval University.

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Faculty Supervisor:

Alain Cloutier

Student:

Qilan Fu

Partner:

FPInnovations

Discipline:

Visual arts

Sector:

Manufacturing

University:

Program:

Elevate

Intelligence from Telemetry applied to Wildfire management and other applications.

Research in Machine Learning and Artificial Intelligence has been applied to image recognition. Weather modeling and prediction make use of distributed computing. Forestry research produces ground cover models and economic value predictions. These active research disciplines are all implicated in the emerging area of big data analytics as applied to the needs of the industrial partner: Tanka is advancing integrated analytics, bridging research in these fields to ingest maximally relevant data to produce valuable information for a variety of applications. Significant economic and social impact is expected as Tanka applies the research results first to early forest fire detection, and these advantages will carry over to adjacent areas such as ship detection at sea.

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Faculty Supervisor:

Nicholas Coops

Student:

Ildar Muslukhov

Partner:

Tanka Technologies Inc

Discipline:

Visual arts

Sector:

Forestry

University:

Program:

Accelerate

Variations of Redox conditions across the Cambrian-Ordovician GSSP (Green Point Formation) in western Newfoundland (Canada): implications from the Trace element, Mo-, U-, C-, S- and N-isotope signatures

The specific investigation of the redox conditions of the Green Point Formation sediments will allow modelling the paleoceanographic conditions on a global basis particularly because the investigated formation is the Cambrian?Ordovician GSSP, which adds to the value of the contributions of the study to understanding the global distribution of source rocks around that time interval.

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Faculty Supervisor:

Karem Azmy

Student:

Jie Li

Partner:

Nalcor Energy

Discipline:

Geography / Geology / Earth science

Sector:

Mining and quarrying

University:

Program:

Accelerate

Visual Analytic Tool for Lessons Learned Retrieval and Decision Making

According to the World Petroleum Council (WPC), the average age of employees in Oil and Gas companies is 50 years, and it is estimated that in the next 5 years 40-60% of them will retire. One consequence of this age-related crisis is losing the accumulated knowledge by retiring “gray-beards”. In this scenario, new software technologies are mandatory to retain decades of expertise and transfer it to new employees. The objective of this project is to start paving the way for developing a novel software system that supports timely decision-making using lessons learned and best practices in the oil and gas industry. The proposed project is focused on reducing the overhead of the complicated process of retrieving all necessary pieces of information to solve a problem. This system integrates textual information from different sources, such as manuals and lessons learned, to retrieve most of the related documents using natural language processing technologies. To achieve this goal, query correction and suggestion are followed by finding the most relevant documents to the query. TO BE CONT’D

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Faculty Supervisor:

Fernando Paulovich

Student:

Elham Etemad

Partner:

Waterford Energy Services Inc

Discipline:

Computer science

Sector:

Information and communications technologies

University:

Program:

Elevate

Surface testing: A solution for surface degradation of industrial materials in harsh environment

This project will demonstrate the cause and effect of industrial material failures in the harsh Newfoundland climate under the general umbrella of corrosion. Our main focus is materials used in the marine and oil & gas industries. By simulating real-world conditions in the laboratory, we will be able to apply cutting-edge materials analysis techniques to extract new and useful information, Our methods and results can be applied in future to real-world industrial samples and will be crucial for identifying and mitigating corrosion effects in industrial settings our laboratory techniques to show the different type of corrosion in industry materials, and the degree of corrosion with time (in days). We will mimic the environmental effects in the laboratory to show a prototype case of corrosio in the material. Our main focus is the materials of marine and oil & gas industries. TO BE CONT’D

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Faculty Supervisor:

Erika Merschrod

Student:

Abhijit Chatterjee

Partner:

qualiTEAS Inc

Discipline:

Chemistry

Sector:

Information and communications technologies

University:

Program:

Accelerate

Garment-based Neuroprosthesis, a non-invasive closed-loop neural extension for facilitating the human nervous system function

MYANT is a pioneer in the field of smart textiles, with the first connected e-textile ecosystem that can serve as a DSL cable connecting humans to their surroundings, others and themselves. This connected eco-system or platform is named SKIIN, representing a second skin, an intelligent interface, an augmentation of the human sensory and nervous system, through a textile medium. This is truly an exciting time to be witnessing such an evolution in textiles, the concept of connected textiles will be as ubiquitous and widespread as the smart phone.
From day one SKIIN has had the very welcomed attention of the medical industry. Partly for that reason and partly to satisfy our determination to only accept the highest standards, SKIIN as a platform is well on its way to becoming FDA and Health Canada approved. TO BE CONT’D

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Faculty Supervisor:

Milos Popovic

Student:

Idir Mellal

Partner:

Myant Inc

Discipline:

Engineering - biomedical

Sector:

Life sciences

University:

Program:

Accelerate

Green Chemistry for Green Solvents – Year two

A major contributor to smog formation is the release of volatile chemicals into the atmosphere which are emitted from many sources including automobile exhaust and consumer products such as paints. To combat the adverse effects smog has on air quality in North America, agencies such as Environment and Climate Change (Canada) and the Environmental Protection Agency (United States) enforce limits on the types and amounts of chemicals used in industrial applications and consumer products. Replacing chemicals that are known to contribute heavily to smog formation, with environmentally friendly chemicals are highly sought after targets. We propose to work with TBF Environmental to develop environmentally friendly alternatives, which will reduce harmful smog emissions when used in place of currently used industrial chemicals. We aim to produce environmentally friendly chemicals from renewable plant bio-mass.

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Faculty Supervisor:

Laurel Schafer

Student:

Joseph Clarkson

Partner:

TBF Environmental Technology Inc

Discipline:

Chemistry

Sector:

Alternative energy

University:

Program:

Elevate

Investigating the Paradoxical Adoption of Blockchain in Healthcare Data Sharing: The Patterns, Consequences and Mediating Mechanisms of Challenging yet Succumbing to Incumbents

In this Mitacs project, we examine how nascent technology advocators can successfully implement the technology in highly institutionalized settings. Using the implementation of Blockchain in healthcare data sharing as an example, we compare and contrast the implementation strategies of 6-8 start-ups or divisions of established companies, and examine how the different types of implementation strategies lead to different implementation outcomes. Based on this research, BI will learn about the key advocators of Blockchain for healthcare data sharing, their strategies and performance. Also, BI can reflect on its own experience and learn from others’ success or failure. In addition, BI will know how to position itself amongst other Blockchain advocators in healthcare data sharing.

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Faculty Supervisor:

Victoria Lemieux

Student:

Chang Lu

Partner:

Boehringer Ingelheim

Discipline:

Computer science

Sector:

Pharmaceuticals

University:

Program:

Accelerate

Identification and characterization of new antimicrobial chemical series

Antibiotic resistance represents a major health problem for society. With the expanded use of antibiotics, microorganisms have developed various mechanisms of resistance to overcome the effects of once highly effective agents. There is therefore an urgent need to identify new therapies to counteract resistant strains. The intern will design and identify new drugs that are capable of treating patients infected with bacterial strains showing resistance to current drugs used in the clinic. The new drugs’ activity will be tested using microbiology assays on bacterial strains that have shown resistance to current drugs. The project will allow the partner organization to better understand ways to overcome microbial resistance and to develop new antimicrobial drugs.

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Faculty Supervisor:

Pat Forgione

Student:

Ghazaleh Imani Shakibaei

Partner:

Paraza Pharma Inc.

Discipline:

Biochemistry / Molecular biology

Sector:

Life sciences

University:

Program:

Accelerate

Air Ambulance and Pre-Hospital Emergency Care in Northern Labrador: An Evidence Mobilization Project

In rural regions of Canada, many patients live far from hospital emergency departments and specialty services. When urgent medical care is required due to a health crisis, access to pre-hospital care and the distance to an emergency department can have a major impact on morbidity and mortality. The primary objective of our study is to examine demographic patterns and clinical characteristics of medevac service use in the northern Newfoundland and coastal Labrador region accompanied by a strong knowledge mobilization plan.

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Faculty Supervisor:

Shabnam Asghari

Student:

Elnaz Bodaghkhani

Partner:

International Grenfell Association

Discipline:

Medicine

Sector:

Medical devices

University:

Program:

Accelerate

Improving Resource Estimation and Reconciliation with Machine Learning

Models quantifying the grade and tonnage of mineral deposits form the basis of important and costly decisions for planning, optimization and extraction of a natural resource. Models are initially generated from sparse exploration sampling; however, information is continuously collected until resource extraction. Predicted values that reconcile well with true values following extraction instill confidence in the production forecasts. Failure to meet production forecasts can have crippling effects on cash flow and ultimately result in failure of the project.
In this research a neural-network-based prediction framework is proposed that incorporates production information to the predictive algorithm to improve forecasts of future production, thereby improving reconciliation at a mining project. The proposed method could be used to continually update resource models to improve decisions being made at all scales. This research will benefit the partner company since the incorporation of a wide array of data in manual reconciliation is complex. The proposed research will simultaneously simplify the workflow for the practitioner and improve reconciliation by improving predicted values in unmined areas. This will generate value through increased operational efficiency.

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Faculty Supervisor:

Jeff Boisvert

Student:

Ryan Martin

Partner:

Teck Resources Ltd

Discipline:

Engineering - petrochemical

Sector:

Mining and quarrying

University:

Program:

Elevate

Development of Thermal Models Towards Reliability Assessment in Energy Delivery Network at FortisBC

The main mission of FortisBC is delivering energy (in the form of electricity and natural gas) safely and reliably at the lowest reasonable cost with lowest emissions. Any maloperations or unexpected interruptions in equipment of the energy supply network may lead to unreliable and unsafe conditions of power delivering to the consumers. For this purpose, continuous monitoring of the condition of the significant elements of the network is a vital need. This project aims to focus on two main components of the energy network, i.e., Power Transformers, and Transmission Pipelines. Aging of power transformers and operating the gas pipelines in cold temperature-areas increase the risk of failures in the energy delivery network. A comprehensive study will be carried out to explore the significant factors that impact the reliable operation of each system. A cost-effective and practical tool based on thermal science and engineering approaches will be developed to predict the life expectancy of power transformers and the minimum temperature of the transmission pipeline to prevent or minimize the corresponding failures in energy network.

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Faculty Supervisor:

Mohammad Arjmand

Student:

Ehsan Ebrahimnia Bajestan

Partner:

FortisBC

Discipline:

Engineering - other

Sector:

Energy

University:

Program:

Accelerate

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