Reference number : 172-2023-2024-Q4-1013508, amendment number : , agreement type : G, recipient legal name : The Royal Institution for the Advancement of Learning/McGill University, recipient country : CA, recipient province : QC, recipient city : Montreal|Montréal, recipient postal code : H3A 2M7, program name english : 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 english : 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., agreement title english : AI-assisted photovoltaic and thermoelectric materials design for energy harvesting applications, agreement title french : Conception de matériaux photovoltaïques et thermoélectriques assistée par l’IA pour des applications de collecte d’énergie, agreement number : 1013508, agreement value : 198000.0, agreement start date : 2023-12-01, agreement end date : 2025-12-01, description english : Organic semiconductors have been intensely investigated in the last two decades because of their wide variety of prominent commercial applications. The device fabrication process and performance heavily depend on the inherent properties of organic semiconductors.  In this project the McGill team will collaborate with a team from the NRC and from NYMCTU on developing and applying machine learning (ML) methods and models to condense the available data on organic semiconductors into a ‘computational compass’ to guide the optimization of materials needed for high-performing, stable, and ‘green’ organic photovoltaic (OPV) and thermoelectric (TE) devices. This goal will be achieved by combining datadriven ML approaches with physics-based (but ML-enhanced) simulation that will fill in the details of manifestation of structural diversity and help encode the necessary morphology-function relationships into generative ML models which will be used to propose hypothetical materials. Synthesis, purification, and characterization protocols will be developed for the experimental realization of these novel materials. The work will be done in a close collaboration between the McGill and the NRC teams with HQP visiting the NRC facilities regularly and with the computational effort supported by the experts on the NRC team. The outcomes expected from this work include machine learning models for design of novel OPV and TE materials, new synthesis, purification, and characterization protocols, and ultimately new OPV and TE devices., description french : Conception de matériaux photovoltaïques et thermoélectriques assistée par l’IA pour des applications de collecte d’énergie, expected results english : 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., additional information english : nan, additional information french : nan, owner organization : nrc-cnrc, owner organization title : National Research Council Canada | Conseil national de recherches Canada