JOURNAL ARTICLE
Construction and evaluation of a system for in-air PIXE analysis for the determination of Cs in trace amounts in mortar.
Published In: International Journal of PIXE, 2024, v. 32, n. 1-4. P. 1 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Kamata, R.; Hagura, N.; Sato, I.; Kawarabayashi, J. 3 of 3
Abstract
This study compares experiments using particle-induced X-ray emission (PIXE) with calculations using PHITS to develop a system for in-air PIXE analyses. X-ray fluorescence (XRF) and in-air PIXE analyses were performed to evaluate the detection limits of Cs in mortar. In the decommissioning of the Fukushima Daiichi Nuclear Power Plant (1F), 1 3 7 Cs is an important nuclide for decommissioning work because of its relatively long half-life, chemical activity, and complex behavior compared with 1 3 3 Xe, which has the most significant amount released into the environment. Therefore, qualitative and quantitative evaluation methods for low concentrations of Cs need to be established to evaluate the contamination mechanism of concrete waste, which constitutes most reactor building materials, to approximate the actual conditions. This study showed that the system used in-air PIXE analysis was more capable of detecting X-rays when the detector was placed behind rather than perpendicular to the sample. At the detection limit of Cs in the mortar, 100 ppm could be measured using XRF analysis, and 50 ppm using in-air PIXE analysis. Therefore, in-air PIXE analysis systematically constructed in this study was confirmed to be one of the most important analytical methods for detecting low concentrations of Cs. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:International Journal of PIXE. 2024/12, Vol. 32, Issue 1-4, p1
- Document Type:Article
- Subject Area:Geology
- Publication Date:2024
- ISSN:0129-0835
- DOI:10.1142/S0129083524500013
- Accession Number:185105958
- Copyright Statement:Copyright of International Journal of PIXE is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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