Projets novateurs réalisés

Optimization of micropillar microfabrication process for heterogeneous integration

Advanced packaging and high-density chip stacking technologies are pivotal in the evolution of microelectronics, enabling enhanced performance through heterogeneous integration. As the industry moves toward reducing bump size and pitch, the bonding methodology has shifted from solder balls to Cu pillars. Although Cu pillars with solder caps have successfully replaced solder bumps, they encounter technical limitations below 30?µm pitch, introducing new challenges, particularly in terms of thermomechanical strength, electromigration resistance, and warpage accommodation.
This project aims to develop high-density ( Voir la description complète du projet

Polymer hybrid bonding for microelectronic assembly

Advanced packaging and high-density chip stacking technologies are pivotal in the evolution of microelectronics, enabling enhanced performance through heterogeneous integration. Hybrid bonding interconnection has increasingly been recognized as the unique bonding method that meets the demands for high-density chip stacking. Cu/SiO2?hybrid bonding is the standard packing interface recently introduced in the industry. However, it faces several challenges. Its low bonding strength due to interfacial water trapping can lead to delamination and failure under stress. Moreover, the overall process requirements – such as temperature, surface roughness, and cleanness – are incompatible with a reconstituted wafer.
This project focuses on polymer-based hybrid bonding technology to enable finer-pitch interconnections. Specifically, it aims to reduce surface cleaning requirements and simplify the manufacturing process. Replacing SiO2 with a polymer dielectric is anticipated to mitigate these issues due to the polymer’s softer mechanical properties, which can absorb contaminant particles into their matrix without damaging the bonding interface. This project proposes the development of polymer bonding processes to achieve the desired packaging interface. Detailed investigations on materials and processing challenges will be conducted to realize successful Cu/polymer hybrid bonding.

M-MIMO Channel Estimation using Federated Learning

examine the feasibility of an innovative solution that combines Federated Learning with Deep Reinforcement Learning (DRL) to optimize the selection of edge nodes for model aggregation. Through the proposed DRL-based client selection method, the system can actively select nodes that have shown superior performance based on their training quality, computational resources, and network conditions. This selection mechanism continuously interacts with the environment, learning and adapting to changes in network conditions and client states. The presented architecture employs DRL to screen edge node behavior and to facilitate the selection of nodes by considering multiple factors such as computational power, latency, data quality, and more. The client selection algorithm utilizes DRL to transform the device node selection problem into a Markov Decision Process (MDP), defining comprehensive action and state spaces as well as a reward function that is aligned with the primary objectives of efficient and effective FL. The customized reward function enables the RL agent to achieve faster model convergence. This innovation holds immense potential for diverse applications and is poised to be a game-changer in the IoT domain.

SI INTERPOSER PLATFORM FOR QUANTUM APPLICATIONS

Global transition to a digital society has billions using microelectronic technology in their day-to-day activities. The increasing demand for miniaturization, speed, and reliability must be satisfied with a compact combination of multiple microchips. The technical constraints are quickly surpassing the capabilities of conventional circuit boards. Thus, silicon interposers, a high-cost, high-performance packaging solution for integrating multiple kinds of chips, have gained popularity in research and commercialization. This proposal will develop and prove the first low-cost, accessible silicon interposer technology made-in-Canada.
This project aims to develop ultra-compact systems on interposer to advance the state of the art in quantum technology. As a result of this project, an established Canadian supply chain for interposers, involving national innovation facilities and university labs, will continue delivering this critical tool to enable the growing digital economy and to boost international competitiveness for over 10,000 microsystems developers in Canada.

Audio Hardware Calibration and Audiometry

This project is to focus on building an application that can be used to perform a audiology-grade calibration of consumer headphones (and microphones) on a mobile device (such as an iPhone or iPad). The intern will use mathematical techniques (such as spectral analysis) to help gather and analyze user information more efficiently in order to provide a fast, accurate assessment of the user’s hardware capabilities for the purposes of hearing testing. The benefit to the partner organization is the creation of an application that, with minimal modification, can be marketed to hospitals, hearing centers, and other medical-related fields; as well as to the general public. In addition the company will gain valuable benefits from working with academic partners such as access to sophisticated analysis and simulation software (such as MATLAB).

AI-based anomaly detection for computer network security

This project will develop an intelligent tool that helps protect computer networks from cyber-attacks. Cyber-attacks are becoming more advanced and harder to detect, so traditional methods often miss new, unknown threats. Using artificial intelligence (AI), this project will create a system that can spot unusual activity on a network, which might indicate an attack. The tool will be tested and improved using real data provided by IntelliSec, a cybersecurity company. The project also tackles the challenge of ensuring that the AI system can still perform well even if the data used to train it is not clean. The expected benefit for IntelliSec is a stronger, more reliable defense system that can better protect their clients from cyber threats.

Thermal Mapping of Cold Water Refugia Using RPAS

Can the refinement of existing drone image acquisition and processing steps lead to improved absolute accuracy of calibrated radiometric thermal orthomosaics in order to more accurately identify salmon thermal refugia?

Pratiques adoptées, retombées positives et autonomisation des entrepreneur-es liées à l’accompagnement en développement durable

La SADC de Nicolet-Bécancour a conçu le programme d’accompagnement PROAction, pour faciliter la transition vers le développement durable des PMO de son territoire. L’objectif est d’obtenir un effet structurant en matière de pratiques de développement durable chez ces PMO, de susciter une autonomie d’actions et des retombées positives. Six (06) ans après sa création, il convient d’évaluer PROAction aux fins de savoir si cet objectif est atteint. Il s’agit en outre de mettre en évidence les succès pratiques obtenus par les PMO et les ressorts cognitifs qui soutiennent leur transition vers le développement durable. Pour ce faire, un rapport d’évaluation de PROAction et des fiches de cas concrets d’organisations ayant complété le programme seront réalisés. Ils permettront à la SADC de réaligner éventuellement PROAction et de valoriser les succès obtenus. Par ailleurs, des publications scientifiques exploreront l’autonomie d’actions et le volet cognitif de la transition vers le développement durable des PMO.

Optimizing Banknote Distribution to Reduce GHG Emissions at the Bank of Canada

One of the main responsibilities of the Bank of Canada (BoC) is to ensure that sufficient inventories of each currency denomination are maintained nationwide. To achieve this, the BoC operates 39 regional distribution centers (RDCs), each with a specified limit on the total currency value it can hold without incurring penalties. Local banks interact with these RDCs through withdrawals and deposits, and the BoC may recall currency that is no longer suitable for re-circulation or exceeding storage capacity. This creates a complex inventory management problem, requiring the BoC to balance demand while minimizing the risks of stock shortages and exceeding inventory limits. The BoC utilizes multiple modes of transportation (air and ground) for banknote distribution; however, ground transportation constitutes a small portion of these operations, with the majority relying on air transport, which produces significant GHG emissions.
The BoC employs an adapted weekly (s,S) inventory management policy to minimize the total number of shipments. This research aims to optimize this policy to reduce the GHG emissions associated with banknote distribution. This can be done by reducing shipments and employing more environmentally friendly modes of transportation where feasible.

Trend and Uncertainty Analysis of Climate Change Trends for Spencer Creek, Ontario

There are however, a range of GCMs, future climate scenarios and downscalingtechniques that can be used and each yields different results. Due to this uncertainty, itis regarded as best-practice to use a collection of individual projections to develop“ranges” that characterize future climate conditions. The aim of this internship is toconduct this analysis for the variables of precipitation and temperatures, which will beused directly by the HCA in their assessment of impacts and hydrologic modeling

AI/ML enhancement of a quasi-Newton acceleration scheme for computational multi-physics

Multi-physics considerations are important for many engineering applications. For example, we may want to know at what rate heat is transferred between two different systems or how a fluid and solid interact with each other for applications such as turbo-machinery, parachutes, or blood flow through an artery. Engineers often rely on numerical methods to solve these problems, which combine multiple single-physics solvers, and resolve the physical interactions between the various solvers using an iterative approach. Unfortunately, this approach can often be numerically unstable. A generic technique which can be applied to stabilize the iterations is a data-drive quasi-Newton approach. However, the method can be prohibitively expensive in some situations. There is also a reliance on linear algebra techniques using past information to attempt to capture data which is often nonlinear.

The proposed project will investigate the use of AI/ML technology to compress the operating space of the quasi-Newton algorithm and provide a more natural filter for data which is no longer relevant to the algorithm.

Exploring the Integration of Environmental Studies in Chinese High School History Classes

This project aims to look at how Chinese teachers integrate environmental studies into their high school History classes. Throughout the course of this research, this project will also explore the strategies that Chinese teachers use to engage the students within their class. In a time of pressing environmental concerns, this project will provide greater insight into how teachers can teach students about the environment and inspire them to take action. Through learning from another country’s educational system and seeing different perspectives, this project aims to bring new ideas and teaching practices back to Canada to further student learning.