Projects Funded in 2026

Forecasting and Resilience of the Arctic through Smart Technologies and Artificial Intelligence

FROST-AI

UdeS Dissertation
Principal Investigator: Alexandre Langlois (Faculty of Arts and Humanities, UdeS)
Co-Principal Investigator: Antoine Séjourné (GEOPS - UMR 8148, CNRS)

CNRS Dissertation
Principal Investigator: Antoine Séjourné (GEOPS - UMR 8148, CNRS)
Co-advisor: Samuel Foucher (Faculty of Arts and Humanities, UdeS)

The FROST-AI project aims to understand and anticipate the impacts of climate change in the Arctic using artificial intelligence and remote sensing. It is structured around two complementary dissertations: the first develops AI models to detect and map features associated with permafrost thaw (lakes, landslides) using multi-temporal satellite imagery, in order to track changes in the Arctic landscape since the 1950s. The second thesis applies machine learning techniques to model and predict the habitat quality of Peary caribou, incorporating environmental variables (snow, rain on snow, vegetation) derived from remote sensing and physical modeling. This innovative project combines French and Quebec expertise in geosciences, remote sensing, and AI, while incorporating the local knowledge of northern communities. The goal is to provide predictive tools for environmental monitoring, the sustainable management of Arctic territories, and the resilience of ecosystems and populations in the face of rapid climate change.

Thematic Area: Responsible Innovation, Transitions, and Biodiversity

A New Perspective on the Reactivity of Additional Cementitious Materials

LUCAS

UdeS Dissertation
Principal Investigator: Fabien Georget (Faculty of Engineering, UdeS)
Co-Principal Investigator: Christophe Labbez (ICB - Carnot Interdisciplinary Laboratory of Burgundy - UMR 6303, CNRS)

CNRS Dissertation
Principal Investigator: Christophe Labbez (ICB - Carnot Interdisciplinary Laboratory of Burgundy - UMR 6303, CNRS)
Co-Principal Investigator: Fabien Georget (Faculty of Engineering, UdeS)

Supplementary cementitious materials (SCMs) aim to reduce the carbon footprint of cement. This project will develop and validate a reactivity test (SLiM) to characterize the thermodynamic and kinetic properties of SCMs, which will enable the formulation of high-performance, low-carbon concretes from an early age. Two research areas are being explored: (1) the quantification of dissolution and precipitation phenomena, particularly for calcined clays, through studies on dissolution rate, surface composition, and the impact of iron and sulfate on reactivity; (2) extending the thermodynamic and hydration model to a wide range of MCS, including the definition of a standardized protocol for industry and an advanced model for research. The methodology combines experimental analyses of solid and liquid phases with thermodynamic modeling. The activities are divided between two doctoral theses: one focused on the physicochemistry of reactive interfaces, the other on the validation and adaptation of the test to various materials. A new early-age hydration model will be developed to optimize binder formulations. Expected results include a robust protocol and modeling tools for the optimization of low-carbon cements.

Thematic Area: Sustainable Chemistry and Circularity of Materials – Responsible, Low-Carbon Materials for Sustainable Construction

Self-Powered Electrochemical Systems Using Micro-Gas Turbines for the Sustainable Treatment of Contaminated Water

Turb'Eaux

UdeS Dissertation
Principal Advisor: Mathieu Picard (Faculty of Engineering, UdeS)
Co-Advisor: Emmanuel Mousset (GEPEA - UMR 6144, CNRS)

CNRS Dissertation
Principal Advisor: Emmanuel Mousset (GEPEA - UMR 6144, CNRS)
Co-Advisor: Mathieu Picard (Faculty of Engineering, UdeS)

In response to water scarcity and the growing presence of emerging pollutants (pesticides, pharmaceutical residues, PFAS), the Turb’Eaux project aims to design an innovative water treatment system combining an advanced electrochemical reactor and a gas microturbine. The originality of the project lies in the utilization of the gases produced during electrolysis (H₂, O₂, Cl₂, fluorinated gases): these gases power a micro-turbine that converts their chemical and mechanical energy into electricity, enabling the process to be self-powered and reducing overall energy consumption. Two complementary doctoral theses are planned: one on the development of a 3D-printed ceramic injector for the microturbine (UdeS), and the other on the design of a reactive electromixer that promotes gas generation and recovery (CNRS). This collaboration aims to validate a prototype for water treatment with a low energy footprint, contributing to the carbon neutrality of wastewater treatment plants and the sustainable protection of water resources.

Thematic Areas: Micronanotechnologies | Sustainable Chemistry and Circularity of Materials - Responsible, Low-Carbon Materials for Sustainable Construction

Neuromorphic Electronics Based on Eco-Designed Hybrid Memristor-Memcapacitor Memories for AI with Reduced Environmental Impact

UdeS Thesis
Principal Investigator: Fabien Alibart (Faculty of Engineering, UdeS)
Co-Principal Investigator: Yann Beilliard (Laboratory of Microelectronics Technologies - UMR 5129, CNRS)

The project aims to experimentally demonstrate innovative neuromorphic computing methods implemented on circuits that co-integrate memristors and ferroelectric memcapacitors as hybrid synapses. The neuromorphic computing demonstrations will aim to maximize the performance-to-energy ratio. This approach seeks to develop the technological building blocks for a new generation of AI with significantly reduced environmental impacts from energy consumption. The project’s objectives will be to (i) develop CMOS-compatible ferroelectric memcapacitors offering analog synaptic behavior (multi-level programming, non-destructive readout) and (ii) co-integrate the memcapacitors with TiOx-based memristors on CMOS circuits to create neuromorphic computing primitives and architectures on which new types of neural networks will be implemented, leveraging the hybrid memristor-memcapacitor synapses.

Thematic Areas: Responsible Innovation, Transitions, and Biodiversity | Micronanotechnologies