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Updated: May 5, 2026

Quantifying X-Ray Fluorescence Data Using MAPS
Published on: February 17, 2018
Biomedical applications of photon-induced X-ray fluorescence
1Centro per l'Ingegneria Biomedica, Università di Roma La Sapienza, Corso Vittorio Emanuele II, 244, 00186, Roma, Italy.
This study presents an optimized X-ray fluorescence (XRF) method for trace element analysis in biological samples. The enhanced technique achieves high sensitivity for elements like chromium and zirconium using preconcentration and quasimonoenergetic radiation.
Area of Science:
- Analytical Chemistry
- Atomic Spectroscopy
- Materials Science
Background:
- Accurate in vitro analysis of trace elements is crucial for various scientific disciplines.
- Traditional X-ray fluorescence (XRF) methods can face limitations in sensitivity and spectral interference.
Purpose of the Study:
- To develop and optimize an X-ray fluorescence (XRF) method for enhanced in vitro trace element analysis.
- To improve sensitivity and reduce spectral background noise for accurate quantification.
Main Methods:
- Utilized an X-ray tube with secondary targets to generate quasimonoenergetic radiation.
- Employed "infinitely thin" specimens and optimized secondary target purity and collimator design.
- Minimized scattered photon contributions from the sample, support, and air.
- Incorporated preconcentration techniques, specifically ashing biological samples.
Main Results:
- Achieved typical sensitivities of 1-5 ng/cm² for elements with atomic numbers 24 (chromium) to 40 (zirconium).
- Demonstrated the effectiveness of optimized XRF parameters and preconcentration for trace element detection.
- Quantification was performed within a counting time of 10³ seconds.
Conclusions:
- The presented XRF method offers a highly sensitive approach for in vitro trace element analysis.
- Optimization strategies, including quasimonoenergetic sources and preconcentration, significantly enhance detection limits.
- This method is suitable for the precise determination of trace elements in biological matrices.
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