About this Abstract |
| Meeting |
2026 TMS Annual Meeting & Exhibition
|
| Symposium
|
Accelerated Discovery and Insertion of Next Generation Structural Materials
|
| Presentation Title |
Automated High-Throughput Characterization of Structural Materials for Extreme Environments |
| Author(s) |
Todd C. Hufnagel, Lori Graham-Brady, Jaafar A El-Awady, David Elbert, Axel Krieger, K.T. Ramesh, Tim Weihs |
| On-Site Speaker (Planned) |
Todd C. Hufnagel |
| Abstract Scope |
AI-driven approaches to materials exploration and discovery are driven by advances in automated laboratories that can rapidly generate statistically-significant quantities of data. Structural materials poses particular challenges for automated experimentation, because mechanical properties are inherently linked to both microstructure and the length scales associated with the samples and measurement techniques.
We describe here the Artificial Intelligence for Materials Design Laboratory (AIMD-L), a unique facility for automated high-throughput characterization of materials for extreme environments. Central to AIMD-L are two custom instruments: A laser-driven microflyer impact system for testing response to shock (including at elevated temperatures), and a focused high-energy transmission x-ray diffractometer for microstructural characterization. The laboratory is fully automated, with sample transfer by a centrally-controlled robotic system and with autonomous data streaming and cross-task data contextualization created by a unifying semantic model. We give examples of experimental campaigns on structural metals and ceramics using the unique capabilities of AIMD-L. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Characterization, Mechanical Properties, Other |