Grant: Collaborative Science, Technology and Innovation Program - Collaborative R&D Initiatives
University of Calgary
$158,400.00
AI FOR SIMULATION AND DESIGN OF NANOCATALYTIC MATERIALS
FY 2019-20 · 2020-03-25
Summary
Modern technological materials are typically multi-component compounds with complex structures that determine their opto/electronic/chemical properties. The design of new functional materials has been greatly assisted by developments in efficient and accurate electronic-structure methodologies, most notably Density Functional Theory (DFT). But DFT is too expensive to perform the rapid screening of thousands of candidates required for the design of new high-performance materials. This project aims to harness the power of modern Artificial Intelligence to build on the success of DFT and ferret out optimal design parameters. This project is of prime socioeconomic importance, aiming to reduce the environmental footprint of the Alberta oil sands by designing new nanocatalysts for the chemical reactions involved in in-the-reservoir upgrading.
Department
Program
Collaborative Science, Technology and Innovation Program - Collaborative R&D Initiatives
Recipient
Location
Calgary, Alberta, Canada
Recipient Type
Academia
Business Number
108102864
Type
Grant
Source
Proactive Disclosure - Grants and Contributions
As published
Additional Information
This agreement has been amended 1 time(s). The end date of this agreements has been modified by 91 days.
Additional Information (French)
Cet accord a été modifié 1 fois La date de fin du présent accord a été changé de 91 jours.
Agreement End Date
2022-03-31
Agreement Number
947408
Agreement Start Date
2020-03-25
Agreement Title
AI FOR SIMULATION AND DESIGN OF NANOCATALYTIC MATERIALS
Agreement Title (French)
L’IA AU SERVICE DE LA SIMULATION ET DE LA CONCEPTION DES MATÉRIAUX NANOCATALYTIQUES
Agreement Type
Grant
Agreement Value
$158,400.00
Amendment Number
0
Description
Modern technological materials are typically multi-component compounds with complex structures that determine their opto/electronic/chemical properties. The design of new functional materials has been greatly assisted by developments in efficient and accurate electronic-structure methodologies, most notably Density Functional Theory (DFT). But DFT is too expensive to perform the rapid screening of thousands of candidates required for the design of new high-performance materials. This project aims to harness the power of modern Artificial Intelligence to build on the success of DFT and ferret out optimal design parameters. This project is of prime socioeconomic importance, aiming to reduce the environmental footprint of the Alberta oil sands by designing new nanocatalysts for the chemical reactions involved in in-the-reservoir upgrading.
Description (French)
Les matériaux technologiques modernes contiennent typiquement plusieurs composés et sont dotés d’une structure complexe qui détermine leurs propriétés optiques, électroniques et chimiques. La conception de nouveaux matériaux fonctionnels a grandement bénéficié du développement de méthodologies efficaces et précises applicables aux structures électroniques, en particulier de la théorie de la fonctionnelle de la densité (DFT). Mais l’application de la DFT au triage rapide de milliers de composants candidats dans le cadre de la conception d’un nouveau matériau hautes performances est une opération trop onéreuse. Ce projet vise à tirer parti de la puissance de l’intelligence artificielle pour exploiter le succès de la DFT et dénicher ainsi des paramètres de conception optimisés. Ce projet est d’une grande importance économique puisqu’il vise à réduire l’empreinte environnementale de l’exploitation des sables bitumineux de l’Alberta grâce à la mise au point de nouveaux nanocatalyseurs pour les réactions chimiques intervenant lors de la valorisation du brut en réservoir.
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.
Expected Results (French)
À court terme, les résultats prévus seront des collaborations renforcées entre l'industrie, le milieu universitaire et le gouvernement pour soutenir l'excellence en recherche. À moyen terme, les résultats attendus seront le développement de nouvelles technologies potentiellement perturbatrices avec des collaborateurs. À long terme, trouver des solutions collaboratives aux défis des politiques publiques et créer des systèmes d'innovation plus solides.
Federal Riding
Calgary Confederation
Federal Riding (French)
Calgary Confederation
Federal Riding Number
48005
NAICS Code
541710
Organization Code
nrc-cnrc
Organization
National Research Council Canada | Conseil national de recherches Canada
Program Name
Collaborative Science, Technology and Innovation Program - Collaborative R&D Initiatives
Program Name (French)
Programme de collaboration en science, en technologie et en innovation - Initiatives de collaboration en R-D
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.
Program Purpose (French)
Collaborer à des programmes multipartites de recherche-développement dans le but de profiter de la synergie entre la recherche transformatrice à haut risque et à haut rendement et le potentiel de découvertes scientifiques et de percées technologiques révolutionnaires dans des secteurs d’intervention prioritaires.
Recipient Business Number
108102864
Recipient City
Calgary
Recipient Country
CA
Recipient Legal Name
University of Calgary
Recipient Operating Name
University of Calgary
Recipient Postal Code
T2N 1N4
Recipient Province or Territory
AB
Recipient Type
S
Reference Number
172-2019-2020-Q4-947408