| About this Abstract |
| Meeting |
2025 TMS Annual Meeting & Exhibition
|
| Symposium
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Spectroscopic Methods and Analysis for Nuclear Energy Related Materials
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| Presentation Title |
ToF-SIMS Characterization of Irradiated U-Zr FCCI Region Using Spectra Clustering |
| 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 |
The FCCI region of U-Zr fuels is a complex region where significant interdiffusion occurs between the fuel, cladding, and fission product elements. This leads to fuel performance concerns, primarily eutectic and intermetallic phase formation. 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 high resolution elemental and isotopic mapping for the material surface and sub-surface (when combined with FIB milling). One challenge with ToF-SIMS is the difficulty in analyzing the large volume of data generated from a scan. In this work, we utilize unsupervised clustering techniques along with relational perspective mapping to segment and color compositional regions within an irradiated U-Zr fuel pin in the FCCI region, enabling subsequent elemental and isotopic distributions in the FCCI region. |
| Proceedings Inclusion? |
Planned: |
| Keywords |
Nuclear Materials, Machine Learning, Characterization |