| About this Abstract |
| Meeting |
MS&T24: Materials Science & Technology
|
| Symposium
|
Additive Manufacturing Modeling, Simulation, and Machine Learning: Microstructure, Mechanics, and Process
|
| Presentation Title |
A Computational Approach to Optimize Phase Behavior in Compositionally Graded Structures |
| Author(s) |
Bernard Gaskey, Cheryl Hawk, John S. Carpenter |
| On-Site Speaker (Planned) |
Bernard Gaskey |
| Abstract Scope |
Compositionally and functionally graded structures are technologically promising because they allow one part to take advantage of properties from two or more alloy systems. Directed energy deposition is one of the primary manufacturing methods for graded parts because the material input can be varied continuously by adjusting feedstock ratio. However, development of stable material gradients can be challenging due to reactions that form undesirable intermetallic compounds. Here, we demonstrate a CALPHAD-based computational approach to predict phase compatibility in compositionally complex graded structures. We use this strategy to identify candidate interlayers for graded parts including important structural materials like titanium and nickel-base alloys. The composition gradients developed by this method minimize interface width and material waste while maximizing the phase fraction of desirable phases than insure a thermodynamically stable and mechanically robust part. LA-UR-24-24629 |