About this Abstract |
| Meeting |
MS&T26: Materials Science & Technology
|
| Symposium
|
Joining/Bonding of Dissimilar Materials
|
| Presentation Title |
Computational Design Strategies for Functionally Graded Materials |
| Author(s) |
Brandon Bocklund, Nicholas Ury, Aurelien Perron, Kaila Morgen Bertsch |
| On-Site Speaker (Planned) |
Brandon Bocklund |
| Abstract Scope |
The design of functionally graded materials (FGMs) via additive manufacturing (AM) presents unique challenges and opportunities that extend beyond traditional alloy design. Calphad-based approaches have enabled more rigorous exploration of the non-equilibrium processes inherent to AM from solidification to post-processing. While path planning algorithms for FGMs have advanced considerably, predictive models that capture how process conditions influence phase and microstructure evolution throughout a part’s lifetime are still lacking, limiting our ability to prospectively design composition and property gradients.
This talk will review the current state of the art in computational FGM design, focusing on the interplay between thermodynamic modeling, kinetic considerations, and algorithmic path planning. I will highlight recent developments at LLNL and elsewhere, including methods for predicting composition paths that obey phase-, property-, and process-aware constraints. Emphasis will be placed on the current gaps and opportunities towards achieving predictive, computationally-driven FGM design.
Performed by LLNL under Contract DE-AC52-07NA27344 |