| About this Abstract |
| Meeting |
TMS Specialty Congress 2024
|
| Symposium
|
Accelerating Discovery for Mechanical Behavior of Materials 2024
|
| Presentation Title |
Elucidating Aging Effects in Alloys Through High Throughout Experiments Using Diffusion Multiples, Nanoindentation, and Machine Learning |
| Author(s) |
Andrew K. Hoffman |
| On-Site Speaker (Planned) |
Andrew K. Hoffman |
| Abstract Scope |
With the development of AI tools and the advent of an era where complex alloys (such as high entropy alloys) have been discovered to address difficult dynamic environments, a new approach to how we perform materials design has been enabled. We will show an example case study understanding the effects of alloy chemistry on aging in FeCrAl alloys. The study shows the design of experiments using diffusion multiples, suggests new methodology from literature on how one can design such experiments, and how techniques like nanoindentation or micro mechanical testing can be used to obtain insights into mechanical behavior. A look into the future as to how this data can be used with lower throughout but higher fidelity techniques will also be discussed. |
| Proceedings Inclusion? |
Definite: Other |