About this Abstract |
| Meeting |
2026 TMS Annual Meeting & Exhibition
|
| Symposium
|
Accelerated Discovery and Insertion of Next Generation Structural Materials
|
| Presentation Title |
Simultaneous Design and Discovery of Functionally-Graded Alloys, Supported by Material Informatics and Rapid Testing |
| Author(s) |
Morad Behandish, Amir M. Mirzendehdel, George P. Harabin, Oishik Sen, Mathieu Calvat, Haoren Wang, Matthew Patterson, Eric Yeh, Jean-Charles Stinville, Kenneth Vecchio, Adrian J. Lew |
| On-Site Speaker (Planned) |
Morad Behandish |
| Abstract Scope |
Today’s one-material-per-part paradigm leads to vulnerabilities when highly engineered components demand locally optimized properties. Design, manufacturing, and qualification of parts made of functionally-graded materials, on the other hand, are hindered by the lack of reliable methods for on-demand discovery and high-throughput testing of new materials. The conventional test methods, based on decades-old techniques, are slow, costly, and not scalable to graded materials. Moreover, the existing part design tools are not able to explore material design spaces as material selection is often treated as an input.
We bridge this divide using a novel material-integrated design framework, informed by material feasibility, criticality, and performance criteria provided by data-driven materials informatics. To collect data on a range of advanced mechanical properties, we use high-resolution digital image correlation (HR-DIC) and AI-based methods to predict macroscopic long-term macroscopic behavior (e.g., fatigue and creep properties) from short-term microscopic observables, with a current focus on metallic alloys. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Additive Manufacturing, Modeling and Simulation, Mechanical Properties |