Organizers:
- Marco Maurizi, University of California Berkeley
- Xiaoyu (Rayne) Zheng, University of California Berkeley
- Sid Kumar, TU Delft
- Dennis Kochmann, ETH Zurich
Description:
Architected materials, or metamaterials, are engineered systems whose macroscopic properties – unattainable in traditional monolithic materials – emerge from the geometric design of their microstructure. Advances in manufacturing techniques and the integration of artificial intelligence (AI) and machine learning (ML) have revolutionized the design, discovery, and fabrication of material systems such as cellular solids, lattices, and architected composites. These technologies enable the creation of materials with tunable, programmable properties, opening doors to unprecedented functionalities. The combination of AI/ML with numerical simulations, fabrication, and characterization methods has dramatically accelerated progress in this field, offering enhanced capabilities for material design and analysis.
This symposium will explore the latest breakthroughs and innovations at the intersection of AI/ML and architected materials, fostering discussions on emerging methods and applications.
Topics of interest:
Topics of interest include, but are not limited to:
- Data-driven design of architected materials
- Physics-informed AI/ML approaches for architected materials engineering
- Topology optimization for architected materials
- Accelerated metamaterial discovery and simulation through AI/ML
- Multi-scale metamaterial design enabled by AI/ML techniques
- Integration of AI/ML with traditional computational frameworks
- AI/ML-assisted manufacturing of complex structures
- AI/ML-guided experimental design and characterization of metamaterials
- Predictive and explanatory models for architected materials
- Physical artificial intelligence using metamaterials