Grants and Contributions:
Title:
Accelerating design and development of high entropy alloys using machine learning
Agreement Number:
969088
Agreement Value:
$280,000.00
Agreement Date:
Apr 1, 2021 - Mar 31, 2024
Description:
High entropy alloys (HEAs) are a new class of metallic materials that contain five or more metals in equimolar or near-equimolar ratios, which have higher strength, ductility, fracture toughness, and catalytic activity compared to traditional alloys that are made by solution hardening, precipitation hardening, and grain refinement. Considering that there are 75 stable elements that are not toxic, radioactive or noble gases, millions of new alloy systems are possible.
The main goal of this Project is to develop and apply machine learning techniques for discovery, design and development of HEAs with desired properties for high-temperature structural, and catalytic applications. This Project will speed up the exploitation of the subtle relationships between the composition and properties of materials, and machine learning (ML) will help screen candidate HEAs that have desired mechanical and functional properties. In this Project, candidate materials will be synthesized and optimized, with the research team intending to design and develop new HEAs for high-temperature structural applications (e.g. in gas turbine), and functional applications (e.g. catalysts for CO2 reduction to methane and methanol).
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:
Toronto, Ontario, CA M5G 1L5
Reference Number:
172-2021-2022-Q1-969088
Agreement Type:
Grant
Report Type:
Grants and Contributions
Recipient Business Number:
108162330
Recipient Type:
Academia
Additional Information:
This agreement has been amended 1 time(s). The end date of this agreement has been modified by 365 days.
Amendment Date
Jan 25, 2023
Recipient's Legal Name:
The Governing Council of the University of Toronto
Federal Riding Name:
University–Rosedale
Federal Riding Number:
35110
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: