| About this Abstract |
| Meeting |
Materials in Nuclear Energy Systems (MiNES) 2021
|
| Symposium
|
Materials in Nuclear Energy Systems (MiNES) 2021
|
| Presentation Title |
Discerning the Effects of Solute Additions in FeCrAl on Dislocation Dynamics under Irradiation Using a Machine Learning Object Detection Algorithm |
| Author(s) |
Priyam Patki, Mingren Shen, Yudai Yaguchi, Jack Haley, Dane Morgan, Kevin Field |
| On-Site Speaker (Planned) |
Priyam Patki |
| Abstract Scope |
Machine learning object detection algorithms have become an increasingly popular choice in detecting, quantifying, and tracking of discrete objects in microstructures allowing the analysis of objects of interest with increased accuracy with no sacrifice in time. In this study, we use the You Only Look Once (YOLO) algorithm to detect black dots formed in FeCrAl systems with varying Cr and Al concentrations during Transmission Electron Microscope (TEM) in situ ion irradiations. The TEM in situ ion irradiation videos were analyzed for four alloys irradiated at 320°C up to 2.5 dpa using YOLO. This study will present the effects of solute additions on the size and density of the black dots formed on a per video frame basis and show a detailed analysis of individual defect dynamics including defect growth and mobility including trajectories using the established analysis framework. |
| Proceedings Inclusion? |
Undecided |