| About this Abstract |
| Meeting |
MS&T22: Materials Science & Technology
|
| Symposium
|
Advanced Characterization of Materials for Nuclear, Radiation, and Extreme Environments III
|
| Presentation Title |
Microstructural Evolution of Alloy 718 under High Temperature In-situ Ion Irradiation with Machine Learning |
| Author(s) |
Stephen Taller, Timothy Lach, Kai Sun |
| On-Site Speaker (Planned) |
Stephen Taller |
| Abstract Scope |
Ni-based superalloys are a candidate alloy class for advanced reactor applications because of their intrinsic resistance to creep and high strength primarily from intermetallic phases δ, γʹ or γʹʹ. Two heats of Inconel 718 with large pre-existing precipitate densities were evaluated using the in-situ dual ion irradiation TEM at the University of Michigan. Irradiations were conducted up to 10 dpa using Kr ions with ~400 appm He/dpa co-injected at temperatures from 500-700°C. STEM HAADF images were continuously collected to capture the time-dependence of the microstructure. A dynamic segmentation convolutional neural network classified features in each frame of in-situ video with several computer vision algorithms to track the size of each feature. Pre-existing precipitates dissolved early (< 1 dpa) for all conditions. Cavities nucleated shortly after with phases with similar contrast to γ″ and δ emerging at higher fluences. With increasing temperature, both cavity nucleation and precipitate dissolution and re-emergence accelerated. |