About this Abstract |
Meeting |
2nd World Congress on High Entropy Alloys (HEA 2021)
|
Symposium
|
2nd World Congress on High Entropy Alloys (HEA 2021)
|
Presentation Title |
ON DEMAND: Factors Affecting Stacking Fault Energies in Concentrated Alloys Using Density Functional Theory and Machine Learning |
Author(s) |
Gaurav Arora, Anus Manzoor, Dilpuneet S. Aidhy |
On-Site Speaker (Planned) |
Dilpuneet S. Aidhy |
Abstract Scope |
Recent experimental work has shown that addition of specific elements can lower the stacking fault energy (SFE) of certain high entropy alloys thereby breaking the strength vs ductility tradeoff. In order to design alloys with desired SFEs, understanding the mechanisms that control SFE is critical. In this work, using density functional theory (DFT) calculations, we isolate the role of atomic radii, valence electron charge, electronegativity and nearest neighbor environment on SFE in 3d, 4d and 5d doped Ni-based alloys. In particular, we find that the difference between the radius of the dopant and the matrix element is the most important factor contributing to SFE. Furthermore, we illustrate a machine learning model that is able to predict SFE in complex alloys from a database of simpler alloys thereby enabling data-science based design of alloys. |
Proceedings Inclusion? |
Undecided |