Grants and Contributions:
Title:
Modelling Raman spatial imaging with deep learning
Agreement Number:
998414
Agreement Value:
$319,000.00
Agreement Date:
Nov 30, 2022 - Mar 31, 2026
Description:
This project proposes to develop the capability to simulate the vibrational properties of 100k atom size systems using deep neural networks (DNN) methods. Such simulations will advance the ability to directly compute what is currently measured with novel Raman techniques. In this project, theoretical and experimental groups will collaborate to bring simulation tools to the next level, where generated data can be directly compared to experimental Raman spectra of complex matter. This testing platform will consist of Raman imaging of defective graphene sheets, systems that cannot be addressed with standard numerical methods because of the size of the problem. The goal is to develop AI-assisted tools to understand better the type of defects that cause a certain Raman response. These tools will use density-functional theory (DFT) simulations as input to guarantee the accuracy and predictability of the approach. These tools will help in the analysis of 2D materials. One possible use of 2D materials is in gas detection and having a better understanding of Raman signals on these surfaces before and after being exposed to certain gases will provide a guide on which materials have the better potential for this type of application.
Organization:
National Research Council Canada
Expected Results:
In the short term, anticipated outcomes will be strengthened collaborations across industry, academia, and government to support research excellence. In the medium term, anticipated outcomes will be the development of new and potentially disruptive technologies with collaborators. In the long term, find collaborative solutions to public policy challenges and create stronger innovation systems.
Location:
Montreal, Quebec, CA H3T 1J4
Reference Number:
172-2022-2023-Q3-998414
Agreement Type:
Grant
Report Type:
Grants and Contributions
Recipient Business Number:
108160995
Recipient Type:
Academia
Additional Information:
This agreement has been amended 1 time(s). The end date of this agreement has been modified by 485 days.
Amendment Date
Dec 12, 2024
Recipient's Legal Name:
Université de Montréal
Federal Riding Name:
Outremont
Federal Riding Number:
24053
Program:
Collaborative Science, Technology and Innovation Program - Collaborative R&D Initiatives
Program Purpose:
Collaborate on multiparty research and development programs to catalyze transformative, high-risk, high-reward research with the potential for game-changing scientific discoveries and technological breakthroughs in priority areas.
NAICS Code:
541710
Amendments: