About this Abstract |
| Meeting |
2026 TMS Annual Meeting & Exhibition
|
| Symposium
|
Artificial Intelligence Applications in Integrated Computational Materials Engineering (AI-ICME)
|
| Presentation Title |
AI for Alloy Design in Extreme Environments |
| Author(s) |
Jaafar A. El-Awady, Lori Graham-Brady, Paulette Clancy, David Elbert, Mark Foster, Todd Hufnagel, Axel Krieger, K.T. Ramesh, Tim Weihs, Tamer Zaki |
| On-Site Speaker (Planned) |
Jaafar A. El-Awady |
| Abstract Scope |
Accelerating the development of structural materials for extreme environments requires autonomous discovery platforms capable of efficiently navigating high-dimensional composition–processing–property spaces. This talk presents the Automated Materials Design for Extreme Environments (AMDEE) initiative at JHU, which integrates robotics, ML, and physics-based modeling to accelerate the materials design process. At the core of AMDEE is the AI for Materials Design Laboratory (AIMD-L), a fully integrated, high-throughput platform for autonomous materials discovery. AIMD-L combines robotic automation with rapid characterization tools, including X-ray diffraction, nanoindentation, profilometry, and laser microflyer impact testing, to assess materials across a broad range of strain rates and temperatures. Event-driven workflows enable real-time data collection, with continuous feedback between experiments, ML models, and physics-based simulations. This talk will highlight AMDEE’s current progress, including autonomous sample handling, multimodal data integration, and tightly coupled experimental and modeling loops, as well as our ongoing efforts toward full autonomy in materials research. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
ICME, Machine Learning, Mechanical Properties |