Projets novateurs réalisés

Explorez des milliers de projets réussis issus de la collaboration entre organisations et talents postsecondaires.

31 620 projets complétés

2978
AB
5221
C.-B.
856
MB
696
NL
899
SK
9419
ON
9858
QC
98
PE
619
NB
1192
NS

Projets par catégorie

An ecological economics analysis of Quebec Sustainable Mobility Plan

As part of the transition plan to low-carbon economy, the province of Quebec (QC) has become one of the 20+ regions and cities worldwide to announce a plan to electrify transportation which centers around setting up a ’complete electric battery ecosystem’ by 2050. While this plan poses a new phase of land appropriation and environmental degradation, through extensive mining and the provision of material and energy intensive grids, Quebec purports to distinguish the plan from the critiques based on renewable endowments such as hydroelectricity. My project, therefore, seeks to analyze the underlying narratives and the feasibility of the proposed strategies for a quick transition to a low-carbon economy based on hydroelectric capacity as well as a massive surge in the supply of critical and strategic minerals. To tackle my questions and objectives, I use multiple qualitative and quantitative methodologies. In the quantitative part of the analysis, which concerns my MITACS Global application, I check the metabolic changes that would result from the objectives underlined by the sustainable mobility. It is expected that metabolic analyses would shed light on the current biophysical metabolism of QC sectors under study (hydroelectricity, mining and battery manufacturing sectors).

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Superviseur du corps professoral :

Peter Brown

Étudiant :

Partenaire :

Central European University

Discipline :

Life Sciences

Secteur :

Sustainability & the Environment; Green/Alternative Energy; Transportation (excluding aerospace)

Université :

McGill University

Programme :

Globalink Research Award

Tarahumara (Rarámuri) Health Project

Blood pressure increases with age in Western societies; however, populations that live as hunter-gatherers and subsistence farmers rarely develop cardiovascular disease and do not have age-related increases in blood pressure. The mechanisms responsible for the maintenance of cardiovascular health with aging are not clear. A mismatch between the conditions that postindustrialized populations inhabit – low levels of physical activity, less daily and seasonal thermal stress and ultra-processed diets – likely drive the increasing blood pressure with age. By examining cardiovascular structure and function, blood volume and fight-or-flight activation in a cohort of rural Tarahumara subsistence farmers, recently urbanized Tarahumara in Chihuahua and Mestizo in Chihuahua, we will test the hypothesis that the urban populations, but not the Tarahumara subsistence farmers, will present increased arterial stiffness, reduced plasma volume and increased fight-or-flight activation with aging. This will help us to identify the underlying processes leading to high blood pressure in postindustrialized populations and direct avenues of future research to promote healthy aging.

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Superviseur du corps professoral :

Robert Shave

Étudiant :

Partenaire :

Universidad Autónoma de Chihuahua

Discipline :

Life Sciences

Secteur :

Health and Related Sciences & Technology

Université :

The University of British Columbia - Okanagan

Programme :

Globalink Research Award

Digital Twin of a Rotating Machine: Model Order Reduction and Artificial Intelligence for Hydroelectricity Production

Hydroelectric power units are more solicited today than in the past when they were usually operated at baseload. Because of this, their operating conditions include many starts and stops, and partial load conditions, resulting in premature and unpredictable failures. With a digital twin, these units can be properly monitored and accurately modeled in order to schedule maintenance and optimize usage to minimize wear.
The aim of my project is to create a digital twin for a vertical axis rotating machine (VARM) with similar dynamical properties to those of the hydroelectric turbine-alternator shaft line. This will be accomplished by building the experimental setup and developing the mathematical reduced-order model of the VARM using Proper Generalized Decomposition. We see the significance of this project in the fact that it will serve as a proof of concept, enabling companies and developers to overcome the same challenges required to develop digital twins for real industrial equipment using sensor data and physical modeling.

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Superviseur du corps professoral :

Frederick Gosselin

Étudiant :

Partenaire :

Arts et Métiers Sciences et Technologies

Discipline :

Engineering

Secteur :

Advanced Computing; Artificial Intelligence; Green/Alternative Energy

Université :

Polytechnique Montréal

Programme :

Globalink Research Award

Attractivité globale et innovation collaborative. Reconfigurer les capacités stratégiques d’un territoire en contexte de rupture

Dans un contexte de forte concurrence touristique, les destinations cherchent à se démarquer les unes des autres.
Pour faire face au défi de rendre leur territoire plus attractif, les acteurs touristiques, politiques, économiques,
géographiques, sociaux et culturels du milieu s’unissent pour concevoir une approche commune et partagée du
développement territorial. Dans l’objectif de réussir leur démarche d’attractivité, des territoires développent donc
des pratiques innovantes de développement et de marketing territorial pour créer de la valeur, et dont les impacts
peuvent se répercuter sur la diminution des coûts, l’amélioration de la notoriété, le développement d’un marché,
etc. Par conséquent, cette étude souhaite analyser les bonnes pratiques existantes en matière d’attractivité de
territoire, en l’occurrence, celui de l’Abitibi-Témiscamingue dans l’objectif que la région développe sa propre
stratégie pour devenir un territoire plus performant et attractif.

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Superviseur du corps professoral :

Mohamed Reda Khomsi

Étudiant :

Partenaire :

Association touristique régionale Abitibi-Témiscamingue

Discipline :

Sociology

Secteur :

Arts, entertainment and recreation; Professional, scientific and technical services

Université :

Université du Québec à Montréal

Programme :

Accelerate

Designing high entropy perovskites for sustainable ammonia synthesis using advanced computational techniques and artificial intelligence

Ammonia is the second most-produced chemical globally, most of which is used in the fertilizers industry. Currently, it is synthesized via the Haber-Bosch process operated at high temperature and pressure using a Fe-based catalyst, which contributes to the generation of 420 million tons of CO2 per year. Therefore, researchers worldwide are currently looking for inexpensive and efficient catalyst for sustainable ammonia production. Perovskites have been studied as effective, low-cost substitutes to expensive noble-metals-based catalysts. Different compositions of transition metals can be used in a perovskite material, making their physical and chemical properties highly flexible and providing a vast searching space for the potential High Entropy Perovskite (HEP) catalysts. This large area of study can benefit a lot from Machine Learning techniques. Until today, there have been only a few studies that analyzed perovskite-type oxides for electrocatalytic Nitrogen Reduction Reaction (NRR), which is one of the rate limiting steps of the ammonia synthesis reaction. The proposed project aims to expedite this research by using artificial intelligence and advanced computational chemistry techniques. We plan to investigate various compositions of HEPs, and manipulate them based on the expected physical and chemical properties of an ideal sustainable ammonia synthesis catalysts.

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Superviseur du corps professoral :

Kulbir Ghuman

Étudiant :

Partenaire :

Forschungszentrum Jülich

Discipline :

Physics

Secteur :

Green/Alternative Energy; Advanced Computing; Artificial Intelligence

Université :

Université du Québec : Institut national de la recherche scientifique

Programme :

Globalink Research Award

Metal mobility during carbon mineralization

Sequestration of atmospheric and industrial CO2 through carbonation of reactive waste minerals is a proven method for curbing emissions from the mining sector. Carbonation technologies have also been shown to be effective at reducing potentially toxic metal mobility in alkaline mine wastes. However, the molecular scale mechanisms of metal cycling associated with mineral transformation reactions during carbonation of mine tailings have been poorly constrained. Therefore, we aim to study the mobility of metals (e.g., Li, Fe, Ni) during accelerated carbonation of critical mineral phases {e.g., amorphous Ca-Mg carbonate, brucite [Mg(OH)2]}. To achieve this, the two interns, Avni Patel and Colton Vessey, will conduct experiments at the CNRS (Toulouse, France) using advanced techniques and methods (i.e., ?7Li and ?57Fe isotope analysis, and in situ Raman spectroscopy). This research will assist in understanding metal mobility within mine wastes and natural systems, and will support continued development of safe carbon capture, utilization, and storage (CCUS) methods.

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Superviseur du corps professoral :

Siobhan Sasha Wilson;Maija Raudsepp

Étudiant :

Partenaire :

Centre National de la Recherche Scientifique (CNRS)

Discipline :

Earth science

Secteur :

Achieving Net Zero; Environmental Science and Technology; Mining

Université :

University of Alberta

Programme :

Globalink Research Award

Advancing Post-Secondary Opportunity for Autistic Students

Using simplified language understandable to a layperson, provide a general, one-paragraph description of the proposed research project to be undertaken by the intern(s) as well as the expected benefit to the partner organization. (100-150 words)
The project has been developed in concurrence with the Sinneave Foundation’s aim to improve outcomes in education, employment and housing for autistic youth and adults. Post-secondary educational supports and access have been identified as key areas to develop to support the autistic population in their goals. As part of the project, interns will participate fully in Phases 1-3 of the project to provide the foundation framework and data to forward the project’s aim of inclusively developing and refine ‘on the ground’ strategies and guidelines for post-secondary engagement and support for students with autism.

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Superviseur du corps professoral :

David Nicholas

Étudiant :

Partenaire :

Sinneave Family Foundation

Discipline :

Sociology

Secteur :

Health and Related Sciences & Technology

Université :

University of Calgary

Programme :

Accelerate

Geochemistry and structure of the Moss Lake Au deposit, Northern Ontario

This study will investigate the volcanic and structural architecture, petrography, and alteration chemistry of a portion of the Shebandowan greenstone belt in the Wawa subprovince of Northern Ontario to better constrain the gold mineralization and to develop vectors towards mineralization. The principal methods employed in this study will be fundamental geological mapping and logging, combined with traditional and state-of-the-art analytical techniques, which will characterize the structures, mineralization, and alteration system associated with mineralization of the Moss Lake area. The research will be completed by three highly qualified personnel (2 master’s students and one postdoctoral fellow), who will be trained to use modern digital field methods and high-quality microanalytical instruments, making them highly skilled assets for industry, academia, or government surveys. The tools generated within this project will help Canadian mining companies enhance exploration efficiency and reduce both the time and capital cost for the discovery of mineral resources.

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Superviseur du corps professoral :

Pete Hollings;Noah Phillips

Étudiant :

Partenaire :

Goldshore Resources Inc.

Discipline :

Earth science

Secteur :

Mining

Université :

Lakehead University

Programme :

Accelerate

The Development Machine Learning Techniques for the Detection of Trace Pharmaceutical Compounds

The goal of this project is to train and test a machine learning algorithm to detect pharmaceutical contaminants in water. Surface nanodroplets will be generated for several key compounds. These, will be used as independent extraction medium with varying contaminant concentration. The large number of droplets will enable collection of a high quality training data set. Potential chemicals to be investigated include: antibiotics, pesticides and flame retardants. Utilizing surface nanodroplets allows for a sufficiently large training set, one of the main limitations in applying machine learning to chemistry. The various machine learning techniques and parameters will be attempted in order to obtain a predictive regression model for concentration based on spectroscopy data. By the end of the project, we aim to have an algorithm that can determine concentration of trace contaminants in an unknown sample of pharmaceutical wastewater. If sufficient time is available then we will investigate extending the library of supported chemicals to include other pollutant categories.

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Superviseur du corps professoral :

Xuehua Zhang

Étudiant :

Partenaire :

Kyungpook National University

Discipline :

Engineering

Secteur :

Artificial Intelligence; Global Health; Pharmaceuticals

Université :

University of Alberta

Programme :

Globalink Research Award

Well-Defined Silica-Supported Titanium Catalysts for Introducing Nitrogen Functional Groups

Nitrogen is a key component in many molecules used as medicines, materials and fertilisers. Adding nitrogen into molecules is currently inefficient and expensive: it requires multiple steps and creates a lot of waste. Alternatively, it is possible to introduce nitrogen by processes called hydroamination and hydroaminoalkylation. These reactions are 100% atom efficient (all of the atoms put into the reaction are used in the products), so no waste is made. Current state-of-the-art methods for hydroamination and hydroaminoalkylation require a catalyst to make the reaction happen but the catalyst is difficult to separate from the products of the reaction. This makes purification of the products too expensive for large scale industrial processes. It is also very difficult to reuse the catalyst. In this project, we will trap the catalysts onto surfaces, which will enhance their performance in reactions and make it easier to separate and reuse the catalyst, as the product can be washed off and the catalyst reused. This technology will enable the efficient and sustainable production of nitrogen containing molecules in industry.

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Superviseur du corps professoral :

Laurel L Schafer

Étudiant :

Partenaire :

Centre National de la Recherche Scientifique (CNRS)

Discipline :

Physics

Secteur :

Achieving Net Zero; Clean Technology; Sustainability & the Environment

Université :

The University of British Columbia

Programme :

Globalink Research Award

Process intensification for production of rVSV

To prevent diseases such as coronavirus disease 2019 (COVID-19) and Ebola virus disease vaccines are the most effective tool. For this, the promising viral vector recombinant vesicular stomatitis virus (rVSV) is applied as production platform. Using suspension HEK293 cells, rVSV-based vectors are currently only produced in batch mode. However, the establishment of perfusion cultivations at high cell concentration would clearly reduce the footprint in plants and increase flexibility in virus vector manufacturing. Thus, we seek to intensify the production of rVSV-based vectors by first obtaining higher concentrations of suspension HEK293 cells in perfusion mode and second applying monitoring and control strategies to achieve maximum infectious virus yields at reduced medium consumption. For this, one bioreactor run in batch mode and two production runs in perfusion mode are planned. The first perfusion cultivation will comprise the use of a cell retention unit coupled to a hollow fiber membrane. For the second perfusion culture, a membrane allowing for continuous virus harvesting and storage of infectious virions will be incorporated.

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Superviseur du corps professoral :

Amine Kamen

Étudiant :

Partenaire :

Max Planck Institute for Dynamics of Complex Technical Systems

Discipline :

Engineering

Secteur :

Biotechnology; Global Health; Pharmaceuticals

Université :

McGill University

Programme :

Globalink Research Award

AI for catalyst discovery

In this project, we will develop innovative AI tools to speed up the process of catalyst discovery, in particular in the domain of renewable energy. Specific catalysts are essential to applications such as the efficient synthesis of solar fuels and fertilizer. However, many known catalysts are suboptimal in their efficacy or require scarce elements. Currently, catalyst development is held back by the computational cost of the quantum chemistry simulations used to guide experimentation, as well as the very high-dimensional search space of potential catalysts. AI offers the opportunity to significantly accelerate the discovery of catalysts, both by performing fast approximate simulations to assess the efficacy of individual catalysts and by intelligently searching for optima in the space of candidate materials. Specifically, we will build AI algorithms that operate on the graphical structure of chemical compounds, incorporating chemistry-related constraints and integrating into larger AI-based materials discovery pipelines.

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Superviseur du corps professoral :

Yoshua Bengio

Étudiant :

Partenaire :

Inria Saclay - Île-de-France Research Centre

Discipline :

Computer science

Secteur :

Artificial Intelligence; Green/Alternative Energy; Achieving Net Zero; Quantum Science

Université :

Université de Montréal

Programme :

Globalink Research Award

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Mitacs est financé par le gouvernement du Canada, le gouvernement de l’Alberta, le gouvernement de la Colombie-Britannique, Research Manitoba, le gouvernement du Nouveau-Brunswick, le gouvernement de la Nouvelle-Écosse, le gouvernement de l’Ontario, Innovation PEI, le gouvernement du Québec, le gouvernement de la Saskatchewan, le gouvernement de Terre-Neuve-et-Labrador et le gouvernement du Yukon.