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Quantitative analysis of total reflection X-ray fluorescence from finely layered structures using XeRay
Total reflection x-ray fluorescence (TXRF) is a widely applicable experimental technique for studying chemical element distributions across finely layered structures at extremely high sensitivity. To promote and facilitate scientific discovery using TXRF, we developed a MATLAB-based software package...
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Published in: | Review of scientific instruments 2017-03, Vol.88 (3), p.033112-033112 |
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Main Authors: | , , , , , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites Items that cite this one |
Online Access: | Get full text |
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Summary: | Total reflection x-ray fluorescence (TXRF) is a widely applicable experimental technique for studying chemical element distributions across finely layered structures at extremely high sensitivity. To promote and facilitate scientific discovery using TXRF, we developed a MATLAB-based software package with a graphical user interface, named XeRay, for quick, accurate, and intuitive data analysis. XeRay lets the user model any layered system, each layer with its independent chemical composition and thickness, and enables fine-tuned data fitting. The accuracy of XeRay has been tested in the analysis of TXRF data from both air/liquid interface and liquid/liquid interfacial studies and has been compared to literature results. In an air/liquid interface study, Ca2+ sequestration was measured at a Langmuir monolayer of 1-stearoyl-2-oleoyl-sn-glycero-3-phosphatidic acid (SOPA) on a buffer solution of 1 mM CaCl2 at pH 7.5. Data analysis with XeRay reveals that each 1 nm2 of interfacial area contains 2.38 ± 0.06 Ca2+ ions, which corresponds to a 1:1 ratio between SOPA headgroups and Ca2+ ions, consistent with several earlier reports. For the liquid/liquid interface study of Sr2+ enrichment at the dodecane/surfactant/water interface, analysis using XeRay gives a surface enrichment of Sr2+ at
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Å2 per ion, consistent with the result published for the same dataset. |
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ISSN: | 0034-6748 1089-7623 |
DOI: | 10.1063/1.4978654 |