About this Abstract |
Meeting |
7th World Congress on Integrated Computational Materials Engineering (ICME 2023)
|
Symposium
|
ICME 2023
|
Presentation Title |
First-principles and Data-driven Discovery of High-entropy Alloys for Corrosion Protection |
Author(s) |
Andrew Neils, Nathan Post, Cheng Zeng, Jack Lesko |
On-Site Speaker (Planned) |
Cheng Zeng |
Abstract Scope |
Corrosion has a wide impact on society, causing catastrophically damage to structural engineered components. High-entropy alloys are emerging materials for superior corrosion performance. However, experimental search for corrosion-resistant materials is time consuming and expensive. Machine learning models trained on first-principles data holds the promise in acceleration of materials design and discovery by predicting materials properties at a low computational cost. In this work, we use first-principles calculations to identify thermodynamic and kinetic metrics for corrosion behaviors of metals. Based on those metrics, we then employ a data-driven approach to guide the autonomous discovery of high-entropy alloys for corrosion protection. Limitations and improvements of the proposed methods will be discussed. |
Proceedings Inclusion? |
Planned: Other |