About this Abstract |
Meeting |
MS&T21: Materials Science & Technology
|
Symposium
|
High Entropy Materials: Concentrated Solid Solutions, Intermetallics, Ceramics, Functional Materials and Beyond II
|
Presentation Title |
Enabling High-strength and Oxidation-resistant Refractory Complex, Concentrated Alloys via Multi-fidelity Experiments and Simulations |
Author(s) |
Michael S. Titus, Austin Hernandez, Sharmila Karumuri, Kenneth Sandhage, Ilias Bilionis, Alejandro Strachan |
On-Site Speaker (Planned) |
Michael S. Titus |
Abstract Scope |
Refractory complex, concentrated alloys (RCCAs) can be defined as refractory-based alloys that comprise four or more elements with near equimolar compositions. Some of these alloys have recently been shown to exhibit remarkable high temperature strength, exceeding that of Ni-based alloys and Mo- and Nb-based silicides. Furthermore, the alloys exhibit superior oxidation resistance compared to traditional refractory-based alloys, but current strategies have not enabled the formation of a protective α-Al2O3 scale above 1300 °C. In this work, we will present a new machine learning for accelerated materials discovery (ML-AMD) framework that utilizes multi-fidelity and multi-cost experiments and physics-based modeling. New semi-high-throughput methods for characterizing oxidation resistance will be presented, and methods for implementing high-throughput simulations into the ML-AMD framework will be expounded. Promising alloys will be identified, and strategies from improving the oxidation resistance of RCCAs will be discussed. |