| About this Abstract |
| Meeting |
2025 TMS Annual Meeting & Exhibition
|
| Symposium
|
Spectroscopic Methods and Analysis for Nuclear Energy Related Materials
|
| Presentation Title |
ToF-SIMS Analysis of Irradiated U-Zr Using Spectra Cluster Analysis |
| Author(s) |
Mitchell L. Mika, Arnold Pradhan, Mario Mattos, Tanner Mauseth, Luca Capriotti, Tiankai Yao, Assel Aitkaliyeva |
| On-Site Speaker (Planned) |
Mitchell L. Mika |
| Abstract Scope |
U-Zr fuel undergoes a complex microstructural evolution during operation in a reactor, including constituent redistribution and both solid and gaseous fission product accumulation. As a result, characterizing the resulting microstructure is critical for qualifying these fuels for commercial deployment. Commonly used characterization techniques suffer from low precision (i.e., EDS), low sampling rate (i.e., TEM SAED), or are limited to the material surface (i.e., EPMA and EDS). Time of flight secondary ion mass spectrometry (ToF-SIMS) is a characterization technique that allows for sub-micron resolution elemental and isotopic mapping for both the material surface and sub-surface. One challenge with ToF-SIMS is the difficulty in analyzing the huge volume of data generated from a scan. In this work, we utilize unsupervised clustering techniques along with relational perspective mapping to quickly segment and false color compositional regions within an irradiated U-Zr fuel pin. Our work provides insights into the microstructural evolution of irradiated fuel. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Nuclear Materials, Machine Learning, Characterization |