# Sorting signals recorded during EDX experiments

Sadeg Said, Jean Cauzid, Cécile Fabre, El-Hadi Djermoune

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Sadeg Said, Jean Cauzid, Cécile Fabre, El-Hadi Djermoune. Sorting signals recorded during EDX experiments. 21st Annual Conference of the International Association for Mathematical Geosciences, IAMG 2022, Aug 2022, Nancy, France. . [hal-03882758](https://hal.science/hal-03882758)

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<figure><img src="image_1.png" /></figure>

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# Sorting Signals Recorded During EDX Experiments

Sadeg Said*, Jean Cauzid*, Cecile Fabre*, El-Hadi Djermoune**

*GeoRessources, Université de Lorraine, CNRS, F-54000 Nancy, France

**CRAN, Université de Lorraine, CNRS, F-54000 Nancy, France

## Goal

The objective of this work is to separate the various signals recorded by the detectors of a Bruker Tornado M4 μXRF analyzer. That device is dedicated to the micro-imaging of the elements in solid samples. The work is conducted on a thin section from the Saint Mélany deposit in the French Massif Central. That sample hosts cassiterite and wolframite macro-crystals surrounded by quartz.

## Introduction

XRF provides the elemental composition of a sample. The EDX detector used in our setup records all X-rays emerging from the sample. XRF stricto sensu corresponds to the specific emission lines of the atoms in the sample. However, the sample can also scatter the signal from the X-ray tube itself. Three scattering signals occur: elastic and inelastic scattering of the specific emission lines of the tube material, elastic and inelastic scattering of the bremsstrahlung and coherent elastic scattering from the periodic atomic organization in crystals. The first scattering manifests as extra peaks (Compton and Rayleigh) on the recorded spectrum, the second as a baseline and the third as X-ray diffraction peaks. These spectra are superimposed with XRF stricto sensu. Each of these four signals contain useful geochemical information.

## Baseline Processing

In order to extract the baseline part from a fluorescence spectrum, we used several algorithms and selected the one providing the best fitting accuracy (Fig. 1). The algorithms we used include ASPLS [6], IRSQ [1], SNIP [5], MORMOL [2], PSALSA [4], and quantile regression [3].

## Diffraction Peaks Processing

Once the baseline signal is removed, the diffraction peaks are processed using two methods, both exploiting the signals captured by the two detectors of the XRF analyzer. Method 1 estimates the position of the peaks in the spectrum corresponding to the difference between the two measured signals. The peaks that do not appear in one of the two original spectra (using a fixed threshold) are then classified as diffraction peaks. Method 2 computes and compares all the peak positions and widths appearing in the two recorded spectra to generate the list of diffraction peaks. The second method is clearly more costly in computation time than the first.

## Conclusion

In this work we tested several methods for baseline extraction and compared the results using clustering to determine how much information was retained in the signal. We then moved on to the processing of diffraction peaks and evaluated two methods to clean up the signal: the second method was much better than the first but it is more costly. As a future work, we will focus on the Campton and Rayleigh peaks working on a half drill core.

## Contact Information

* said.sadeg@univ-lorraine.fr
* el-hadi.djermoune@univ-lorraine.fr
* jean.cauzid@univ-lorraine.fr
* cecile.fabre@univ-lorraine.fr

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[5] C. G. Ryan, E. Clayton, W. L. Griffin, S. H. Sie, and D. R. Cousens. SNIP, a statistics-sensitive background treatment for the quantitative analysis of PIXE spectra in geoscience applications. *Nuclear Instruments and Methods in Physics Research B*, 34(3):396–402, Sept. 1988. doi: 10.1016/0168-583X(88)90063-8. URL https://ui.adsabs.harvard.edu/abs/1988NIMPB..34..396R.

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<figure><img src="image_2.png" /><figcaption>Fig 1. composition of spectrum</figcaption></figure>

<figure><img src="image_3.png" /><figcaption>Fig 2. Fitted diffraction peaks found by Method 1</figcaption></figure>

<figure><img src="image_4.png" /><figcaption>Fig 3. Fitted diffraction peaks found by Method 2</figcaption></figure>

<figure><img src="image_5.png" /></figure>

<figure><img src="image_6.png" /><figcaption>(c) minerals classified from XRF sig-
nal (blue peaks on the sum spec-
trum).</figcaption></figure>

<caption>(d) proportion of each mineral in
the map</caption>

<caption>(e) map made from the inelastic scat-
tering peaks (part of the green peaks
on sum spectrum)</caption>

<caption>Fig 4. different maps showing the sample</caption>