JOURNAL ARTICLE
X‐ray fluorescence analysis of mercury in human hairs using a secondary target placed behind the sample.
Published In: XRS: X-ray Spectrometry, 2024, v. 53, n. 6. P. 499 1 of 3
Database: Academic Search Ultimate 2 of 3
Authored By: Inoue, Fumiyuki; Matsuyama, Tugufumi; Tsuji, Kouichi 3 of 3
Abstract
Mercury is a pollutant that poses a considerable health risk. The concentration of mercury in scalp hair can be used to estimate past mercury exposure. Methods such as atomic absorption spectrophotometry and inductively coupled plasma‐based techniques have been used to determine the concentrations of trace elements in scalp hairs; however, these analytical methods have several limitations, including the need for expensive equipment, complex sample preparation, and large samples of more than 100 hairs. Therefore, simpler and more cost‐effective methods are required. X‐ray fluorescence (XRF) spectroscopy is a simple and fast analytical method. To improve the sensitivity, we applied a secondary target method to enhance the XRF excitation and reduce the background. In conventional secondary target methods, the primary x‐rays irradiate a secondary target of a pure substance, and the sample is then irradiated with the fluorescent x‐rays from the secondary target. We placed high‐purity Y₂O₃ powder, which served as the secondary target, behind the hair samples. The XRF intensities of trace elements such as mercury and zinc in the hair were enhanced by applying the secondary target behind the hair. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:XRS: X-ray Spectrometry. 2024/11, Vol. 53, Issue 6, p499
- Document Type:Article
- Subject Area:Engineering
- Publication Date:2024
- ISSN:0049-8246
- DOI:10.1002/xrs.3406
- Accession Number:180249339
- Copyright Statement:Copyright of XRS: X-ray Spectrometry is the property of Wiley-Blackwell 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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