Symposium B-2
Frontiers in Data-Driven Structural Materials
Scope
This symposium aims to present and discuss the latest advances, challenges, and future directions in the rapidly evolving field of data-driven approaches to structural materials research and development.
Topics
- Materials Integration combining data and simulation
- AI-driven inverse design of materials and processing
- Microstructure analysis and generation
- Performance and microstructure prediction
Symposium Keynote
- Toshiyuki KoyamaNational Institute for Materials Science
- Microstructure design accelerated by phase-field method, image-based property calculations, and generative AI techniques
- So TakamotoPreferred Networks, Inc.
- Challenges and Progress in Universal Interatomic Potentials Toward Standard Tools for Materials
- Kyosuke YoshimiTohoku University
- A Data-Driven Design Framework for Accelerated Development of Advanced Ultratherm-Resistant MoSiBTiC Alloys
Invited Speakers
- Masanori Enoki, Shimane University: First-Principles Prediction of Nitride-Based Nanocluster Formation in Fe Alloys
- Satoshi Noguchi, JAMSTEC: Bayesian Inverse Inference with Image-Based Deep Generative Models
- Tatsuya Ito, Japan Atomic Energy Agency: Revealing the role of hydrogen in enhancing both strength and ductility of Type 310S austenitic steel via in situ neutron diffraction
- Masato Wakeda, National Institute for Materials Science: Atomistic Modeling and Analysis of Planar Faults in Metals and Alloys based on Data-Driven Approach
- Kenji Nagata, National Institute for Materials Science: GPU-Accelerated Variational Bayesian Inference for Comprehensive and Rapid Crystalline Phase Identification from X-ray diffraction
Organizers
- Representative
Masahiko Demura - National Institute for Materials Science
- Correspondence
Junya Inoue - The University of Tokyo
j-inoue[at]iis.u-tokyo.ac.jp
- Shigenobu OGATA
- Osaka University
- Goro MIYAMOTO
- Tohoku University
