| About this Abstract |
| Meeting |
2024 TMS Annual Meeting & Exhibition
|
| Symposium
|
An Atoms to Autos Approach for Materials Innovations for Lightweighting: An LMD Symposium in Honor of Anil K. Sachdev
|
| Presentation Title |
Atomistic Kinetics in the Early Stage of Aluminum Alloy Natural Aging |
| Author(s) |
Harold A. Smith-Perez, Penghao Xiao, XiaoXiang Yu |
| On-Site Speaker (Planned) |
Harold A. Smith-Perez |
| Abstract Scope |
The natural aging of aluminum alloy significantly impacts the materials’ formability and paint bake response. Previous work suggests that solute element clustering plays a role; however, this process is challenging to characterize.
This work provides atomistic insights into this shelf-life problem from a computational lens. Thousands of atomic structures are generated and their energies are obtained via density-functional theory (DFT) calculations. This provides a large training data set to create a surrogate Hamiltonian through the cluster expansion (CE) method or convolutional neural networks (CNN). Based on the surrogate model, kinetic Monte Carlo (KMC) is then used to simulate the time evolution of the clustering process to the timescale of seconds, giving insight into how Si and other dopants interact with one another, Al and vacancies. The results are used to predict synthesis pathways that minimize this unintended clustering, extending the shelf life of these alloys. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Aluminum, Computational Materials Science & Engineering, Mechanical Properties |