Potential and pitfalls of XRF-CS analysis of ion-exchange resins in environmental studies

Detecting clandestine, intermittent release of heavy metal pollution into natural and man-made water ways is challenging. Conventional chemical methods are both labor intensive and expensive. A recent approach combining ion-exchange resins with the capabilities of X-ray fluorescence core scanners (XRF-CS) therefore is of great interest. In short, ion-exchange resin is deployed in the water using small sachets, the resin is then collected, dried, filled into sample holders and scanned using XRF-CS. Ion-exchange resins take up heavy metals in proportion to the concentration in the ambient water, with a correlation coefficient (R2) between concentration and XRF-CS counts better than 0.96 for most elements. However, a number of parameters influence the measurements. Different drying methods introduce differences in the XRF counts because of lattice bound water, resin shrinkage, and disaggregation of the resin particles. Furthermore, the newly developed sample carrier, which was constructed using 3D printed polymers, contains trace amounts of elements that may influence the sample measurements through edge effects and secondary fluorescence. In the tested sample carrier materials, substantial levels of Cr, Fe, Co, and Zn were detected, while Ca, Ti, Ni, Cu, Ga showed variable levels. Ba, Tl and Bi show very low levels, and Pb is only of importance in the PLA carrier. It is therefore necessary to streamline the analysis-process to ensure that the variations in sample treatment and drying and filling methods are minimized. It is also recommended that only spectra from the center of the compartments are used for the evaluation to avoid edge effects caused by secondary fluorescence of metals in the compartment walls. Although the technique of using ion-exchange resin sachets and XRF-CS analysis is only semi-quantitative, it is a cost effective and fast way to monitor large areas for environmental pollution, and the new sample carrier greatly contributes to make the process faster and less error prone.

Secondary Fluorescence of 3D Heterogeneous Materials Using a Hybrid Model

In electron probe microanalysis or scanning electron microscopy, the Monte Carlo method is widely used for modeling electron transport within specimens and calculating X-ray spectra. For an accurate simulation, the calculation of secondary fluorescence (SF) is necessary, especially for samples with complex geometries. In this study, we developed a program, using a hybrid model that combines the Monte Carlo simulation with an analytical model, to perform SF correction for three-dimensional (3D) heterogeneous materials. The Monte Carlo simulation is performed using MC X-ray, a Monte Carlo program, to obtain the 3D primary X-ray distribution, which becomes the input of the analytical model. The voxel-based calculation of MC X-ray enables the model to be applicable to arbitrary samples. We demonstrate the derivation of the analytical model in detail and present the 3D X-ray distributions for both primary and secondary fluorescence to illustrate the capability of our program. Examples for non-diffusion couples and spherical inclusions inside matrices are shown. The results of our program are compared with experimental data from references and with results from other Monte Carlo codes. They are found to be in good agreement.

Validation of secondary fluorescence excitation in quantitative X-ray fluorescence analysis of thin alloy films

Reference-free X-ray fluorescence analysis of multilayered, alloyed thin films in the μm regime with significant secondary fluorescence contributions.

Secondary Fluorescence Correction for Characteristic and Bremsstrahlung X-Rays Using Monte Carlo X-ray Depth Distributions Applied to Bulk and Multilayer Materials

Secondary fluorescence effects are important sources of characteristic X-ray emissions, especially for materials with complicated geometries. Currently, three approaches are used to calculate fluorescence X-ray intensities. One is using Monte Carlo simulations, which are accurate but have drawbacks such as long computation times. The second one is to use analytical models, which are computationally efficient, but limited to specific geometries. The last approach is a hybrid model, which combines Monte Carlo simulations and analytical calculations. In this article, a program is developed by combining Monte Carlo simulations for X-ray depth distributions and an analytical model to calculate the secondary fluorescence. The X-ray depth distribution curves of both the characteristic and bremsstrahlung X-rays obtained from Monte Carlo program MC X-ray allow us to quickly calculate the total fluorescence X-ray intensities. The fluorescence correction program can be applied to both bulk and multilayer materials. Examples for both cases are shown. Simulated results of our program are compared with both experimental data from the literature and simulation data from PENEPMA and DTSA-II. The practical application of the hybrid model is presented by comparing with the complete Monte Carlo program.

Secondary Fluorescence in WDS: The Role of Spectrometer Positioning

Secondary fluorescence (SF), typically a minor error in routine electron probe microanalysis (EPMA), may not be negligible when performing high precision trace element analyses in multiphase samples. Other factors, notably wavelength dispersive spectrometer defocusing, may introduce analytical artifacts. To explore these issues, we measured EPMA transects across two material couples chosen for their high fluorescence yield. We measured transects away from the fluorescent phase, and at various orientations with respect to the spectrometer focal line. Compared to calculations using both the Monte Carlo simulation code PENEPMA and the semi-analytical model FANAL, both codes estimate the magnitude of SF, but accurate correction requires knowledge of the position of the spectrometer with respect to the couple interface. Positioned over the fluorescent phase or otherwise results in a factor of 1.2–1.8 of apparent change in SF yield. SF and spectrometer defocusing may introduce systematic errors into trace element analyses, both may be adequately accounted for by modeling. Of the two, however, SF is the dominant error, resulting in 0.1 wt% Zn apparently present in Al at 100 μm away from the Zn boundary in an Al/Zn couple. Of this, around 200 ppm Zn can be attributed to spectrometer defocusing.