Advancing Materials Data, Design, and Discovery
| Reference No. | 2025b007 |
|---|---|
| Type/Category | Grant for International Project Research-Workshop (I) |
| Title of Research Project | Advancing Materials Data, Design, and Discovery |
| Principal Investigator | Kulbir Ghuman（INRS (Montreal, Canada)・Associate Professor） |
| Research Period | |
| Keyword(s) of Research Fields | Materials Science, Artificial Intelligence, Machine Learning, Orbital-Free Density Functional Theory, Molecular Dynamics, Optimal Transport, global optimization algorithms, accelerated discovery of metal alloys, complex oxydes. |
| Abstract for Research Report |
Artificial Intelligence (AI) has sparked a paradigm shift in Materials Science, with Machine Learning (ML) enabling data-driven, informatics-based calculations, predictions, and discoveries. These advances, powered by extensive material databases, allow us to push beyond the limitations of traditional first-principles calculations. However, the successful application of AI in this field demands the development of novel methodologies that integrate insights from both materials science and information technology, fostering a close synergy between these two disciplines. The symposium will bring together a diverse group of computational and experimental materials scientists, as well as mathematicians, to explore the latest breakthroughs in materials research. Discussions will center on the application of computational chemistry and physics tools, including Density Functional Theory (DFT) and Molecular Dynamics, in combination with AI-driven approaches. Topics will encompass emerging computational techniques such as Orbital-Free DFT, as well as the integration of both experimental and computational methods to generate high-quality materials data. Particular attention will be given to current datasets, their inherent limitations, and potential strategies for enhancing their quality and applicability. The event will also explore new mathematical models and theories designed to tackle the complexities of active materials, functional molecules, and large-scale systems. The proposed symposium is the fourth installment of a series of conferences initiated in 2022 under the framework of the IMI Joint Usage Research Programs. The first edition, titled "Perspectives on Artificial Intelligence in Materials Science (PAIMS)," was organized by a subset of these co-organizers and held online due to the COVID-19 pandemic. It attracted 50 participants, including many students, and featured 12 speakers.The series has grown over the years, with the second edition held at Waseda University as a mini-symposium within the framework of the 2023 ICIAM. In 2024, the series expanded internationally and was organized by the INRS Montreal group, led by Prof. Kulbir Kaur Ghuman, as part of the CEMDI project. This edition saw a significant participation of speakers and attendees from Canada, Japan, and other countries. In 2025, the JP-Canada joint venture continues as we plan the fourth edition of the symposium at the Ito Campus. |
| Organizing Committee Members (Workshop) Participants (Short-term Joint Usage) |
Pierluigi Cesana（IMI・Associate Professor） Kenji Kajiwara（IMI・Professor, Director） Yu Kaneko（Daicel Corporation・Senior Research Scientist） Linh Thi Hoai Nguyen（I2CNER, Kyushu University・Assistant Professor） Daniel Packwood（Institute for Integrated Cell-Material Sciences, Kyoto University・Associate Professor） Yasser Salah Eddine Bouchareb（Institut National de la Recherche Scientifique, Center Énergie Matériaux Télécommunications (INRS-EMT)・PhD Student） Kulbir Ghuman（Institut National de la Recherche Scientifique, Center Énergie Matériaux Télécommunications (INRS-EMT)・Associate Professor） Aleksandar Staykov（I2CNER, Kyushu University・Associate Professor） |