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# Advances in dynamic and batch processing of PIXE spectra

L. Pichon, Q. Lemasson, D. Bachiller-Perea, C. Pacheco

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L. Pichon, Q. Lemasson, D. Bachiller-Perea, C. Pacheco. Advances in dynamic and batch processing of PIXE spectra. Nuclear Instruments and Methods in Physics Research Section B: Beam Interactions with Materials and Atoms, 2025, 565, pp.165734. 10.1016/j.nimb.2025.165734. hal-05066923

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Submitted on 14 May 2025

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# Advances in dynamic and batch processing of PIXE spectra

L. Pichon<sup>a,b,*</sup>, Q. Lemasson<sup>a,b</sup>, D. Bachiller-Perea<sup>a,b</sup>, C. Pacheco<sup>a,b</sup>

https://doi.org/10.1016/j.nimb.2025.165734

**Keywords:** PIXE, IBA software, dynamic PIXE processing, PIGE.

## Abstract

We present here the advances on two custom-built software programs for PIXE spectra processing, both of them based on the GUPIX package. The first one, named LivePIXE, is a standalone executable that has been implemented in the New AGLAE data acquisition system to process dynamically PIXE spectra during recording, almost in real-time. It allows to verify if the selected area of the object is relevant for the analysis and it provides a first interpretation of the PIXE results in order to orientate further analysis. The second program presented here is an updated version of the TrauPIXE software, which we had previously developed to process series of recorded PIXE spectra. As different X-ray absorbers can be installed in front of the detectors, each element of interest in the sample can be measured with different detection limits and uncertainties. This updated version selects the most precise element concentrations from all the PIXE results. It can also take into account the elemental concentrations obtained simultaneously by PIGE or/and RBS and incorporate them during the PIXE processing and into the final compositional table.

## 1. Introduction

For decades, the New AGLAE facility has been providing beamtime for Ion Beam Analysis (IBA) to the heritage science community which include researchers from various scientific backgrounds (archaeology, nuclear science, archaeometry, geology, and materials science) [1–6]. The team has continuously optimized both instruments and processing methodologies to meet and anticipate the user’s needs. To deal with a large diversity of materials and researcher problematics, the New AGLAE external beam end-station is equipped with a

<footnote><sup>a</sup> Centre de Recherche et de Restauration des Musées de France, C2RMF, 75001 Paris, France</footnote>

<footnote><sup>b</sup> Laboratoire de développement instrumental et de méthodologies innovantes pour les Biens Culturels, Lab-BC, CNRS - C2RMF - Chimie ParisTech - Univ. PSL, 75001, Paris, France</footnote>

<footnote>* Corresponding author at: Centre de Recherche et de Restauration des Musées de France, C2RMF, 75001 Paris, France.
E-mail address: laurent.pichon@culture.gouv.fr (L. Pichon).</footnote>
multi-detector system combining simultaneously Particle-Induced X-ray Emission (PIXE), Particle-Induced Gamma-ray Emission (PIGE), Ion Beam Induced Luminescence (IBIL) and Rutherford Backscattering Spectrometry (RBS) techniques. In addition, our custom acquisition software has been improved over the past few years, gaining the capability of performing elemental 2D-imaging on each IBA analysis [7,8]. Sensitivity and rapidity of the analysis has been improved by increasing the solid angle through the use of four PIXE detectors. Some other facilities have also chosen to increase the number of PIXE detectors on their external beam equipment [9–11] to take advantage of a large solid angle.

A distinctive feature of cultural heritage (CH) objects is their often highly heterogeneous surface [12–15] induced by corrosion, weathering, deposition of sediment remains and restoration products all potential sources of analytical bias. This difficulty can be circumvented by our custom-built software AGLAEMAP, which yields PIXE maps recorded. Indeed, this software permits to exclude irrelevant areas or to select specific areas of interest to record new spectra [16]. However, the thorough cleaning and verification of each map, which can only be performed during post-run data processing, can be time-consuming.

Furthermore, during acquisition, the area of interest is not always recognizable through the optical camera of the beam positioning system. This fact leads to imprecise selection of the analysis area, which may potentially result in misinterpretation in the composition of the constituent materials of the works. It is also important to emphasize that some of the accelerator users may lack familiarity with the PIXE technique. Therefore, they might face difficult challenges when making initial assessments of spectra during acquisition. In the interdisciplinary context of heritage object analysis, the implementation of such a dynamic PIXE quantification of the analysis appears to be a real advantage. It can provide a valuable instant guidance for the ongoing analysis of the object, enhancing the accessibility and user-friendliness of the experimental setup for both specialists and non-specialists. To address this challenge, we have developed an autonomous software (LivePIXE) integrated into our spectra viewer that enables dynamic processing of the PIXE spectra.

Concerning the advances in post-run processing of series of spectra, we have updated our custom-built software TrauPIXE, described in detail in a previous paper [17]. Its main feature is to process the PIXE matrix spectrum followed by one or several PIXE trace spectra automatically applying a normalization method named “pivot method”. Other teams using also several PIXE detectors have developed their own processing software to handle the challenge of processing both the matrix and the trace spectra [18–20].
Another data processing challenge is the study and elemental quantification of complex materials composed of elements that are undetectable by PIXE. Some elements can be quantified by other techniques, for example, fluorine and boron can be measured by PIGE, while RBS allows to detect carbon and oxygen from the binders used with mineral pigments in easel paintings [21,22]. The software improvements presented here will enable to include these "invisible" elements during the PIXE processing, thus addressing this challenge.

Other recent advances namely, a new data processing function, improved presentation of result sheets, a new custom configuration that allows other facilities to use the software easily are also described in this paper.

## 2. Multidetector quantification methodology

At New AGLAE, up to four detectors can be used simultaneously for PIXE analysis. One of them is dedicated to the low-energy (LE) X-rays particularly useful to identify light elements ($Z < 26$). No absorber is used on this detector and a flow of He gas facilitates the detection of the low-energy X-rays. Hereafter, we will refer to that detector as "LE detector" or "matrix detector", since the targets used in this works are mainly composed of light elements. The other four detectors are more suitable for trace identification, we can place different absorbers in front of them to detect high-energy (HE) X-rays emissions. In the examples shown in this work, we have used three HE detectors. Two of them are combined as they are equipped with the same absorber (20 µm Cr + 50 µm Al) to generate a unique spectrum, which will be referred to as "trace No. 1". The third HE detector, equipped with a 50 µm Al absorber, will be referred to as "trace No. 2. The physics engine of GUPIX software [23–26] is used to process the PIXE spectra obtained with the different detectors explained before [27]. The processing of the spectra requires an accurate knowledge of the experimental setup (i.e., the cumulated charge on the sample during the irradiation, the solid angle of the detectors, the absorbers equipped, the dead time, etc.). The difficulties with an external beam setup are the following: the integrated charge cannot be accurately measured and the solid angle of the detectors is often modified for each run to optimize the count-rate ratio between the trace signal and the matrix signal, depending on the type of matrix composition and absorbers. Those undetermined parameters are not a problem for the matrix spectrum processing in the case of CH samples, since the "Iterated Matrix Solution" of GUPIX can be used with an arbitrary charge and an arbitrary solid angle. This process normalizes the sum of the concentrations of the matrix elements to 100 % as we assume that we detect all matrix elements in a thick sample. For the trace spectrum
processing, a different approach is required that is why we use the fixed matrix solution of GUPIX. First, for each trace spectrum obtained from the different HE detectors, the matrix composition must be defined with the one obtained via the matrix spectrum processing and secondly, we must find a way to calculate the normalization concentration factor. To reach this goal, we use the pivot method already mentioned in previous works [7,27]. This method consists in processing the spectra of the traces with arbitrary integrated charge and solid angle. Thus, we obtain arbitrary concentrations of the traces but with the correct concentration ratios. Therefore, if the concentration of one trace element is known, it can be used as reference to scale all the other concentrations. This particular reference element must be present with high statistics in the matrix spectrum and in all the trace spectra, and will be referred to as the “pivot element”. We have to point out that the uncertainty on this pivot element is critical as it will be propagated to all the other trace elements. Note that, the uncertainties shown derive from the fit error provided by GUPIX and are all expressed as relative values. The composition of the matrix and the X-ray transmission of the absorbers installed on the detectors are also important factors to consider when selecting the pivot element. For example, lead is usually chosen in the case of leaded glass, or copper in case of bronze. In particular cases, such as metallic objects, one can obtain different matrix composition from one point to another. It may be essential to automatically select the appropriate pivot elements from a predefined list, which is a function included in TrauPIXE.

Once the concentration of the pivot element is obtained from both the matrix and trace spectra, a correction factor for the cumulated charge is obtained following Eq. 1.

$$Q' = Q \cdot \frac{\text{PivotConcTrace}}{\text{PivotConcMatrix}} \qquad (1)$$

Where *Q* is the arbitrary charge factor used in the first trace spectrum and *Q'* is the charge factor that will be used to normalized the current trace spectrum, *PivotConcMatrix* and *PivotConcTrace* are respectively the elemental concentration of the pivot element obtained from the matrix spectrum and the trace spectrum.

After replacing the arbitrary charge factor (Q) by the new calculated charge (Q') in the trace parameter file, a second trace processing is run, providing normalized trace concentrations. The two software programs presented in this paper, LivePIXE for dynamic processing and TrauPIXE for post-run processing, use this methodology. It enables us to easily process several trace spectra with any type of absorbers, charge and solid angle.
### 3. Dynamic PIXE processing software: LivePIXE

To our knowledge, no existing software utilizing the GUPIX processing engine has been designed to process PIXE spectra concurrently with acquisition. A quantitative dynamic processing capability is available in the GeoPIXE program [28–30]. This software was used at the National Accelerator Centre (NAC, now iThemba LABS, South Africa) to demonstrate the production of real-time elemental imaging thanks to the Dynamic Analysis method [31,32]. Despite being powerful, it is not an open-source software and it is only adapted to the data format produced by the Commonwealth Scientific and Industrial Research Organisation (CSIRO, Australia) imaging computer system. The Silva et al.'s team has planned to develop large data PIXE processing thanks to their Simple Spectra Processing System (SSPS) based on Artificial Neural Network [11,20]. Our approach differs from the previous ones as we are the first to use the processing engine of the widely used GUPIXWIN software to automatically process PIXE spectra in a multiple detector system calculating both matrix and trace elements contents almost in real-time [15]. The LivePIXE software has been developed in Visual Basic and is delivered as an executable. This program enables dynamic processing of the PIXE spectra under acquisition doing a new calculation every five seconds. It has been integrated into the spectral viewer of the New AGLAE data acquisition system that now displays the PIXE spectrum simultaneously with its elemental quantification.

First of all, the experimental conditions have to be specified using the graphical user interface shown in Fig. 1. The type of ion used for the PIXE analysis and its energy are two experimental parameters automatically received from the accelerator control interface, while the user can specify other experimental conditions such as the absorbers used on the detectors or the type of material being studied, in particular those of CH interest.

<figure><img src="image_2.png" /><figcaption>**Fig. 1** Part of the New AGLAE acquisition graphical interface showing the type of particle and its energy, the absorbers installed in front of the detectors, and the type of material studied.</figcaption></figure>
Once this phase has been achieved, LivePIXE generates a GUPIX parameter file containing the experimental parameters and the running PIXE spectra. Then it executes the GUPIX engine "pixwin.exe" to calculate the matrix composition from the spectrum obtained with the LE detector, it retrieves the matrix quantitative results from the output file and stores it for further trace calculation. In the case of trace spectra, it applies the pivot method considering the stored matrix composition. Finally, it refines the results to deliver only one value by element with a concentration above the limit of quantification (LOQ), defined in GUPIX as 3.3 times the limit of detection (LOD).

The quantitative concentrations obtained through this procedure are updated every five seconds and displayed under the PIXE spectrum that is being acquired (Fig. 2). The results are given in oxide or elemental form according to the choice of the user, and they are expressed in weight percentage for elements with concentrations above 1 % , and in ppm for those with concentrations below that limit (elements or oxides with light-blue background on Fig. 2).

<figure><img src="image_3.png" /><figcaption>**Fig. 2** Front panel of the spectra viewer at New AGLAE showing a PIXE spectrum being acquired (in this case with the LE detector) and a table with the calculated composition which is updated every five seconds. Trace elements are expressed in ppm and appear with a blue background.</figcaption></figure>
There is another option for executing the LivePIXE processing, instead of integrating it in a graphical interface, the user can write the instructions for processing a spectrum directly at the command prompt, so that it can be used in any customized spectrum viewer. The LivePIXE output is obtained as a text string of each element concentration in weight percentage followed by its uncertainty expressed as relative.

As it has been shown here, LivePIXE enables fast analysis of the PIXE spectra providing preliminary results. However, while these results provide a better understanding of ancient materials during measurement, and are a valuable aid to decision-making during the experiment, they are no substitute for rigorous post-run data processing to obtain high-quality quantitative results obtained with the TrauPIXE software.

## 4. New batch post-run processing capabilities of the TrauPIXE software

The New AGLAE acquisition system enables to carry out fast PIXE measurements, producing numerous spectra corresponding to trace detector channels across various combinations, thereby generating a profusion of data. Consequently, a single workday can yield hundreds of spectra requiring processing. We have recently upgraded our software TrauPIXE [7,27] that processes our series of PIXE spectra after the experimental measurements. Several new features are presented below. One of the objectives is to respond to user requests for renewing the output data formatting, in order to facilitate the visualization of the results and the interpretation of large data sets.

The formatting of the output data is indeed crucial, particularly when dealing with multiple detectors, as the concentration of certain elements may originate either from the matrix spectrum or from different trace spectra. Until now, we had to choose manually from which detector we extracted the resulting concentrations for all analyses. While this choice is straightforward for major or minor elements, it becomes less obvious for elements present in low concentrations. Factors like matrix effects or the high presence of a particular element can impact the uncertainty of the results. Manual selection may introduce errors, providing misleading information about element detection or selecting concentrations with high uncertainties.

To address this issue, we have introduced a new function in TrauPIXE that intelligently selects the optimal concentration, element by element, for each analysis, saving only the one with the lowest uncertainty.
The relative uncertainties of the elements found with the trace detectors are calculated for each sample according to Eq. 2.

$$ \sigma_{\text{trace\_tot}} = \sqrt{\sigma_{\text{trace\_fit}}^2 + \sigma_{\text{pivot}}^2} \qquad (2) $$

Where $\sigma_{\text{trace\_tot}}$ is the total relative uncertainty for a trace element, $\sigma_{\text{trace\_fit}}$ is the GUPIX fit relative error value obtained for that element. As $\sigma_{\text{pivot}}$ is the relative uncertainty for the pivot element, that has been previously calculated as the quadratic sum of its GUPIX fit relative error values obtained in both matrix and trace results. Then, the concentration value with the lowest relative uncertainty among all the $\sigma_{\text{trace\_tot}}$ values and $\sigma_{\text{matrix}}$ (uncertainty in matrix) is selected for each element, and the results are summarized in a table that is exported as an Excel document by TrauPIXE. For example, in our case, three uncertainty values, $\sigma_{\text{traceN°1\_tot}}$, $\sigma_{\text{traceN°2\_tot}}$ and $\sigma_{\text{matrix}}$, were compared to find the lowest uncertainty.

As a result, the output Excel file generated by TrauPIXE contains now four new sheets that are created using this element selection, two of them display the concentration in ppm units and the two others in mass percentages. For each case, one of the two sheets contains also the uncertainty on the concentration values enabling to see at a glance the quality of the results.

As an example, four different samples were analyzed by PIXE using 3 MeV proton beam on a scanned area of 1x1 mm size. LE spectra are processed as matrix and HE spectra N°1 and N°2 as trace spectra, the Fe being used as pivot element to normalize trace concentrations. The samples correspond to geochemical reference materials provided by the Service d'Analyse des Roches et des Minéraux (Nancy, France), Dr-N stands for diorite (two points have been analyzed), Be-N stands for basalt, and Bx-N stands for bauxite. The data were processed by TrauPIXE and Fig. 3 shows an example of an Excel sheet from the output. The results for each sample are displayed in different columns and each line indicates the concentration obtained for each element or oxide with its uncertainty underneath. The cell background color indicates in which detector the concentration value has been selected: white is used for the low-energy detector (matrix constituents), light grey indicates the trace detector N°1, and dark grey is used for the trace detector N°2. Finally, the font of the figures in the table replaces the GUPIX unofficial designation of an element's presence indicator "Y/?/N". In our case, the black font indicates that the element concentration is quantified (> LOQ, "Y" in GUPIX), the red and bolt
font means that the element is above the limit of detection (LOD) but is not well quantified (< LOQ, “?” in GUPIX), and the italic and blue font indicates that an element is under the LOD (“N” in GUPIX). The letters “n.d.” are used for the uncertainties that were not determined, either because the elements are under the limit of detection or because they have been introduced manually since they are not detectable by PIXE. It can also be noticed that the user can choose the form of trace element content in oxide or elemental in those new four Excel sheets. In this case, the elements Mn, Ca and Fe have been retrieved from their oxide form (MnO, CaO and Fe₂O₃) whereas some others are retrieved in their elemental form (V, Cr, Cu, Zn, Sr, Pb).

The right table of Fig. 3 displays the certified concentrations for each standard. As can be seen when compared to the TrauPIXE concentration results, for Dr-N, the calculated concentrations of major and minor elements in the left table of Fig. 3 are close to the certified values, with less than a 5 % difference. Concerning the trace elements, most of them are also in good agreement with the certificate values (Cu, Zn, Rb, Sr). As for Be-N, the largest discrepancies are 15 % below the certified value for MgO and 15 % above for Al₂O₃, these differences could be explained by a heterogeneity on the scanned area. For Bx-N, the matrix is notably different than the precedent ones, characterized by high Al₂O₃ and Fe₂O₃ contents; both show results close to the certificate, with less than 4 % difference, but some minor elements such as SiO₂ may show higher differences. These discrepancies could be attributed to local heterogeneity of the standards. It can also be noted that under quantification of elements with low X-ray energies (<3 keV) in GUPIX is possible as highlighted in several articles [33,34]. Nevertheless, most results are close to the certified values, verifying the experimental conditions (energy, absorbers thickness, energy calibration). Ultimately, the good overall agreement of the results presented here validates the TrauPIXE data workflow.

In Fig. 3, it can also be noticed that the concentration values of V, Cr, Mn, Cu and Rb are chosen from different detectors as indicated by their background colors, which are either white, light grey or dark grey. Figure 4 provides an example (using the Cu concentration) to illustrate the automatic selection function from which the results shown on Fig. 3 have been extracted.

In this example, the element Cu has been detected for the four samples with the three detectors: the low-energy one without absorbers, the trace detector N°1 (absorbers: 20 µm Cr + 50 µm Al), and the trace detector N°2 (absorber: 50 µm Al). The final Cu concentration is
selected automatically choosing the result with least uncertainty: for the two Dr-N samples, it is selected from the trace N°2 (σ = 9.48 % and 7.74 %), and for the Be-N and Bx-N samples the Cu concentration is selected from the trace detector N°1 (σ = 9.10 % and σ = 16.32 %, respectively).

It clearly demonstrates that selecting manually the concentrations from only one detector for the whole dataset would thus have resulted in a loss of results precision.

Legend

<table><thead><tr><th colspan="3">Detection limit color code</th></tr><tr><th>Dark Normal (Y)</th><th>Red Bold (?)</th><th>Light Blue Italic (N)</th></tr></thead><tbody><tr><td>conc. &gt; LOQ</td><td>LOD &lt; conc. &lt; LOQ</td><td>conc. &lt; LOD</td></tr><tr><th colspan="3">Background color code for detector selection</th></tr><tr><th>Matrix</th><th>Trace N°1</th><th>Trace N°2</th></tr></tbody></table>

TrauPIXE output concentration

<table><thead><tr><th></th><th>Dr-N</th><th>Dr-N</th><th>Be-N</th><th>Bx-N</th></tr></thead><tbody><tr><td><strong>Na2O-PIGE</strong></td><td>29900</td><td>29900</td><td>31800</td><td><strong>540</strong></td></tr><tr><td>Unc%</td><td>n.d.</td><td>n.d.</td><td>n.d.</td><td>36.15</td></tr><tr><td><strong>MgO</strong></td><td>42500</td><td>44260</td><td>112500</td><td><strong>&lt; 448</strong></td></tr><tr><td>Unc%</td><td>1.04</td><td>1.04</td><td>0.6</td><td>n.d.</td></tr><tr><td><strong>Al2O3</strong></td><td>174300</td><td>170700</td><td>117200</td><td>526800</td></tr><tr><td>Unc%</td><td>0.38</td><td>0.39</td><td>0.55</td><td>0.18</td></tr><tr><td><strong>SiO2</strong></td><td>530500</td><td>530500</td><td>387400</td><td>86730</td></tr><tr><td>Unc%</td><td>0.16</td><td>0.16</td><td>0.21</td><td>0.54</td></tr><tr><td><strong>P2O5</strong></td><td>1980</td><td>2220</td><td>13130</td><td>1380</td></tr><tr><td>Unc%</td><td>10.5</td><td>9.47</td><td>2.08</td><td>10.09</td></tr><tr><td><strong>S-Certif</strong></td><td>350</td><td>350</td><td>300</td><td>10</td></tr><tr><td>Unc%</td><td>n.d.</td><td>n.d.</td><td>n.d.</td><td>n.d.</td></tr><tr><td><strong>Cl</strong></td><td>535</td><td>518</td><td>861</td><td>411</td></tr><tr><td>Unc%</td><td>8.21</td><td>8.71</td><td>5.48</td><td>9.51</td></tr><tr><td><strong>K2O</strong></td><td>17740</td><td>16880</td><td>14450</td><td>786</td></tr><tr><td>Unc%</td><td>0.68</td><td>0.7</td><td>0.75</td><td>4.85</td></tr><tr><td><strong>CaO</strong></td><td>69490</td><td>69160</td><td>136800</td><td>3390</td></tr><tr><td>Unc%</td><td>0.37</td><td>0.37</td><td>0.25</td><td>1.63</td></tr><tr><td><strong>TiO2</strong></td><td>9970</td><td>10390</td><td>25180</td><td>22570</td></tr><tr><td>Unc%</td><td>1.06</td><td>1.03</td><td>0.67</td><td>0.58</td></tr><tr><td><strong>V</strong></td><td>245</td><td><strong>203</strong></td><td><strong>221</strong></td><td>458</td></tr><tr><td>Unc%</td><td>13.2</td><td>16.23</td><td>24.45</td><td>9.83</td></tr><tr><td><strong>Cr</strong></td><td><strong>28</strong></td><td><strong>40</strong></td><td>317</td><td>215</td></tr><tr><td>Unc%</td><td>55.97</td><td>39.94</td><td>9</td><td>11.4</td></tr><tr><td><strong>MnO</strong></td><td>2070</td><td>2150</td><td>1940</td><td>340</td></tr><tr><td>Unc%</td><td>2.62</td><td>1.94</td><td>2.69</td><td>6.98</td></tr><tr><td><strong>Fe2O3</strong></td><td>95650</td><td>97780</td><td>123000</td><td>231000</td></tr><tr><td>Unc%</td><td>0.29</td><td>0.28</td><td>0.26</td><td>0.17</td></tr><tr><td><strong>NiO</strong></td><td><strong>12</strong></td><td><strong>420</strong></td><td>230</td><td>170</td></tr><tr><td>Unc%</td><td>68.74</td><td>n.d.</td><td>7.16</td><td>8.64</td></tr><tr><td><strong>Cu</strong></td><td>55</td><td>66</td><td>65</td><td>30</td></tr><tr><td>Unc%</td><td>9.48</td><td>7.74</td><td>9.1</td><td>16.32</td></tr><tr><td><strong>Zn</strong></td><td>140</td><td>141</td><td>124</td><td>95</td></tr><tr><td>Unc%</td><td>5.46</td><td>4.88</td><td>5.64</td><td>6.64</td></tr><tr><td><strong>As</strong></td><td><strong>7</strong></td><td><strong>14</strong></td><td><strong>21</strong></td><td>86</td></tr><tr><td>Unc%</td><td>33.46</td><td>n.d.</td><td>n.d.</td><td>6.23</td></tr><tr><td><strong>Rb</strong></td><td>66</td><td>68</td><td>57</td><td><strong>93</strong></td></tr><tr><td>Unc%</td><td>7.33</td><td>7.11</td><td>8.4</td><td>31.14</td></tr><tr><td><strong>Sr</strong></td><td>451</td><td>450</td><td>1620</td><td>132</td></tr><tr><td>Unc%</td><td>3.41</td><td>3.31</td><td>1.92</td><td>4.75</td></tr><tr><td><strong>Y</strong></td><td><strong>32</strong></td><td><strong>33</strong></td><td><strong>30</strong></td><td>127</td></tr><tr><td>Unc%</td><td>16.29</td><td>16.2</td><td>20.42</td><td>5.73</td></tr><tr><td><strong>Pb</strong></td><td>44</td><td>185</td><td>352</td><td>154</td></tr><tr><td>Unc%</td><td>16.75</td><td>6.94</td><td>4.75</td><td>7.19</td></tr><tr><td><strong>H2O-Certif</strong></td><td>24000</td><td>24000</td><td>25000</td><td>120000</td></tr><tr><td>Unc%</td><td>n.d.</td><td>n.d.</td><td>n.d.</td><td>n.d.</td></tr><tr><td><strong>CO2-Certif</strong></td><td>0</td><td>0</td><td>7400</td><td>5000</td></tr><tr><td>Unc%</td><td>n.d.</td><td>n.d.</td><td>n.d.</td><td>n.d.</td></tr><tr><td>Sum</td><td>1000065</td><td>999994</td><td>999977</td><td>1000517</td></tr></tbody></table>

Certified concentration

<table><thead><tr><th>Dr-N</th><th>Be-N</th><th>Bx-N</th><th></th></tr></thead><tbody><tr><td>29900</td><td>31800</td><td>400</td><td><strong>Na2O</strong></td></tr><tr><td>0.19</td><td>0.23</td><td>0.06</td><td>Unc%</td></tr><tr><td>44000</td><td>131500</td><td>1100</td><td><strong>MgO</strong></td></tr><tr><td>0.27</td><td>0.44</td><td>0.08</td><td>Unc%</td></tr><tr><td>175200</td><td>100700</td><td>542100</td><td><strong>Al2O3</strong></td></tr><tr><td>0.55</td><td>0.41</td><td>1.16</td><td>Unc%</td></tr><tr><td>528500</td><td>382000</td><td>74000</td><td><strong>SiO2</strong></td></tr><tr><td>0.73</td><td>0.62</td><td>0.46</td><td>Unc%</td></tr><tr><td>2500</td><td>10500</td><td>1300</td><td><strong>P2O5</strong></td></tr><tr><td>0.05</td><td>0.13</td><td>0.06</td><td>Unc%</td></tr><tr><td>350</td><td>300</td><td>n.d.</td><td><strong>SO3</strong></td></tr><tr><td>68</td><td>149.7</td><td>n.d.</td><td>Unc%</td></tr><tr><td>400</td><td>200</td><td>n.d.</td><td><strong>Cl</strong></td></tr><tr><td>85</td><td>87.9</td><td>n.d.</td><td>Unc%</td></tr><tr><td>17000</td><td>13900</td><td>500</td><td><strong>K2O</strong></td></tr><tr><td>0.1</td><td>0.11</td><td>0.03</td><td>Unc%</td></tr><tr><td>70500</td><td>138700</td><td>1700</td><td><strong>CaO</strong></td></tr><tr><td>0.24</td><td>0.37</td><td>0.14</td><td>Unc%</td></tr><tr><td>10900</td><td>26100</td><td>23700</td><td><strong>TiO2</strong></td></tr><tr><td>0.08</td><td>0.14</td><td>0.23</td><td>Unc%</td></tr><tr><td>220</td><td>235</td><td>350</td><td><strong>V</strong></td></tr><tr><td>34.4</td><td>33.4</td><td>77.1</td><td>Unc%</td></tr><tr><td>40</td><td>360</td><td>280</td><td><strong>Cr</strong></td></tr><tr><td>10.3</td><td>48.9</td><td>74.9</td><td>Unc%</td></tr><tr><td>2200</td><td>2000</td><td>500</td><td><strong>MnO</strong></td></tr><tr><td>0.02</td><td>0.02</td><td>0.02</td><td>Unc%</td></tr><tr><td>97000</td><td>128400</td><td>228800</td><td><strong>Fe2O3</strong></td></tr><tr><td>0.3</td><td>0.35</td><td>1.0</td><td>Unc%</td></tr><tr><td>15</td><td>267</td><td>180</td><td><strong>NiO</strong></td></tr><tr><td>11.05</td><td>26.5</td><td>36.8</td><td>Unc%</td></tr><tr><td>50</td><td>72</td><td>18</td><td><strong>Cu</strong></td></tr><tr><td>7.18</td><td>10.9</td><td>4.22</td><td>Unc%</td></tr><tr><td>145</td><td>120</td><td>80</td><td><strong>Zn</strong></td></tr><tr><td>16.38</td><td>49.7</td><td>38.84</td><td>Unc%</td></tr><tr><td>3</td><td>1.8</td><td>115</td><td><strong>As</strong></td></tr><tr><td>0.64</td><td>0.6</td><td>8.9</td><td>Unc%</td></tr><tr><td>73</td><td>47</td><td>3.6</td><td><strong>Rb</strong></td></tr><tr><td>7.62</td><td>8.8</td><td>11.1</td><td>Unc%</td></tr><tr><td>440</td><td>1370</td><td>110</td><td><strong>Sr</strong></td></tr><tr><td>49.6</td><td>100.0</td><td>18.7</td><td>Unc%</td></tr><tr><td>23</td><td>30</td><td>114</td><td><strong>Y</strong></td></tr><tr><td>6.96</td><td>5.0</td><td>40.2</td><td>Unc%</td></tr><tr><td>55</td><td>4</td><td>135</td><td><strong>Pb</strong></td></tr><tr><td>11.4</td><td>5.38</td><td>76.5</td><td>Unc%</td></tr><tr><td>24000</td><td>25000</td><td>120000</td><td><strong>H2O</strong></td></tr><tr><td>0.28</td><td>0.4</td><td>0.26</td><td>Unc%</td></tr><tr><td>0</td><td>7400</td><td>5000</td><td><strong>CO2</strong></td></tr><tr><td>n.d.</td><td>0.23</td><td>0.23</td><td>Unc%</td></tr><tr><td>1003514</td><td>1001005</td><td>1000482</td><td>Sum</td></tr></tbody></table>

**Fig. 3** Top: legend to understand the meaning of the fonts and backgrounds on the bottom tables. Left: example of a table obtained in an Excel results sheet generated by TrauPIXE. Color font and style of the values represent the “Y/N/?” GUPIX indicator, cell background color indicates the detector origin of the concentration. The label “n.d.” is used for the uncertainties that were not determined. Right: table containing the certified concentrations for Dr-N, Be-N and Bx-N Standard.
<figure><img src="image_4.png" /><figcaption>**Fig. 4** Example of the Cu concentration (ppm) selected and the corresponding lowest relative uncertainty (%) for the four analyses. On the bottom: relative uncertainty (%) obtained for the Cu concentration with all detectors.</figcaption></figure>

The second major TrauPIXE update is the integration of element concentrations measured by other companion techniques, such as RBS or PIGE, during the PIXE processing. This can be a very interesting option for elements such as B, F, Na, Be, Li, C, N that are invisible or hardly detectable by PIXE (for example, in the case of Na, it can be detected by PIXE but inaccurately). The most common cases in archaeometry deal with analyses of altered soda-lime glasses where the Na concentration is always determined by PIGE due to the loss of alkaline element in the first micron of the surface [35–41], for ivory objects where fluorine is also obtained from PIGE results [42,43], and for glazes containing boron [44] or lithium [45]. With the earlier version of TrauPIXE, we used to incorporate the concentrations obtained by PIGE into the tables of results replacing manually the corresponding inaccurate PIXE concentrations or adding new lines for the elements not correctly measured or non-detectable with this technique. The results are then manually normalized to 100 %. This process has been improved by automatically introducing the PIGE derived concentrations during the PIXE spectrum processing. Thus, elemental concentrations obtained by others techniques can be simply given thanks a comma-separated value file named ‘external-conc.csv’. Their concentration will be replaced in the matrix composition if they are present in PIXE results (e.g., Na₂O) or will be added if they are not detected by PIXE (H, B, F, C, Li, Be). This TrauPIXE feature provides a more realistic matrix definition during the trace spectrum processing, improving the matrix absorption calculation and obtaining a more accurate trace composition.

For example, thanks to the external concentrations given through the CSV file, it can be seen on Fig. 3, that H₂O and CO₂ concentrations have been correctly added to the table. As original PIXE sulfur concentration have been replace by the certificate concentration (350 ppm), since during the preliminary processing we had obtained an unexplained too high concentration (1.6
%), probably due to some contamination. As for Na₂O, its concentrations obtained by PIXE for Dr-N and Be-N have been replaced by certificate values to simulate a PIGE correction.

Note that, here we have used the certificate values because we did not use any complementary technique. The objective is to demonstrate and to validate the correct replacement or addition of concentrations provided via the CSV file, followed by normalization to 100%. In the case of a real sample analysis (unknown composition), we would use the values from the experimental measurements.

As an example to illustrate the effect of this matrix correction procedure, the Na₂O concentration on altered soda-lime glasses can differ of 1-10 % between the PIXE and the PIGE results, inducing differences when using the above matrix correction during the trace spectra processing. Figure 5 illustrates the difference of the theoretical yield calculated by GUPIX for these two processes, one without any correction on the matrix composition, i.e., 13 % Na₂O and no B₂O₃, and the second one with a corrected matrix composition, i.e., 17 % of Na₂O and 4 % of B₂O₃. As can be seen in Fig. 5, the inclusion of those low-Z element concentrations in the trace processing shows differences up to 4.5 % in the theoretical yield of low-Z emissions, and between -1 % to 1 % for emissions above the Fe Kα line (6.405 keV), typically corresponding to trace elements. This difference on the calculation is particularly relevant for the elements between Ca and Fe, which are the usual pivot elements, affecting even more the results since its difference is propagated to all the traces. This new feature needs to be applied to other types of materials or other PIXE-invisible elements or constituents to demonstrate greater differences on the theoretical yield.
<figure><img src="image_5.png" /><figcaption>**Fig. 5** PIXE Trace yield difference between GUPIX simulated results obtained on a glass matrix composition with 13 % Na₂O and 0 % of B₂O₃, and the same glass corrected with 17 % of Na₂O and 4 % of B₂O₃.</figcaption></figure>

The inclusion of elements non-detectable or inaccurately detected during the PIXE spectrum processing will not only improve the accuracy of the results, but also simplify the multi-technique data processing. The resulting Excel file displays all the concentrations, the ones with the best precision for PIXE and concentrations obtained by others IBA techniques, normalized to 100 % for the hundreds of analyses recorded during a run.

In addition to these new processing features, we have also introduced a configuration file for TrauPIXE to be able to understand various file extensions or naming. In the case of New AGLAE, we use different file extensions for detector differentiation (X0, X1, X2, X3, X4...).
Now, it is feasible to configure up to eight PIXE spectra using either alternative file extensions or by specifying a keyword present in the filename (e.g., big, small, det1, det2...). This customization in the TrauPIXE interface enhances its adaptability, making it more accessible for its use in other facilities.
**5. Conclusion**

The two software programs developed at New AGLAE facility constitute a step forward in PIXE data analysis. The newly developed LivePIXE software enables dynamic PIXE spectra processing, very helpful to users during experiments. Indeed, it provides the composition of the area under analysis almost in real-time and offers a guidance for the ongoing analysis of the object. Future enhancements to the spectra viewer will be on the dynamic processing of chemical elements measured by PIGE, in particular for sodium (Na), which, coupled with PIXE quantification, will provide immediate information on the state of conservation of the area being analyzed for glass objects. Concerning the post-run processing performed with the TrauPIXE software, several improvements have been done, for example, a modular user interface ensuring adaptability to diverse setups has been provided, and new output results are included in the Excel file, facilitating streamlined data interpretation and analysis. With this update, TrauPIXE also incorporates now a result-selection algorithm that identifies the quantification values with the lowest uncertainties, serving as an important processing step on complex raw PIXE data.
Since this algorithm is now validated for different types of materials, the use of a weighted average could be incorporated into the selection process to provide a unique average concentration for each element with reduced uncertainty.

It is worth noting that the feedback from the New AGLAE users and researchers interrogations have been highly helpful, and that the latest innovations are being effectively utilized on real case studies. enabling a continuous improvement of these new features and the development of additional ones.

**Acknowledgements**

The authors are grateful to Dr. Thomas Calligaro and Jean-Paul Berthet for the scientific discussions, to Dr. Jean-claude Dran for the advice on improving the English in the text and to Dr. Ina Reiche, director of the Lab-BC - UAR3506, for the financial and scientific support.

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