# New measurements on neutron-induced activation towards an innovative approach for controlled interferences in neutron activation analysis

Valentin Blideanu, Clement Besnard Vauterin, Khalil Al Khouri, Benjamin

Rapp, Natko Skukan, Wafa Bennaceur

► To cite this version:

Valentin Blideanu, Clement Besnard Vauterin, Khalil Al Khouri, Benjamin Rapp, Natko Skukan, et al. New measurements on neutron-induced activation towards an innovative approach for controlled interferences in neutron activation analysis. Radiation Physics and Chemistry, 2025, 234, pp.112780. 10.1016/j.radphyschem.2025.112780. cea-05025998

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# New measurements on neutron-induced activation in samples, towards an innovative approach for controlled interferences in Neutron Activation Analysis

V. Blideanu¹, C. Besnard-Vauterin¹, K. Al Khouri¹, B. Rapp¹, W. Bennaceur²
N. Skukan²

¹Université Paris-Saclay, CEA, List, Laboratoire National Henri Becquerel (LNE-LNHB)
F-91129, Palaiseau, France

²Nuclear Science and Instrumentation Laboratory, IAEA, Seibersdorf, Vienna A-1400, Austria

valentin.blideanu@cea.fr

## ABSTRACT

Neutron Activation Analysis (NAA) is a widely utilized technique for precise elemental quantification across diverse fields such as geology, materials science, and archaeology. Despite its high sensitivity and specificity, NAA is often hindered by interferences arising from competing nuclear reactions in mixed thermal/fast neutron fields. While thermal neutrons predominantly produce radioactive nuclei through neutron capture (n,γ) reactions, fast neutrons can trigger alternative reactions such as (n,p) on another nuclei possibly present in the material under analysis leading to the production of the same radio-isotope as the main capture reaction and so complicating spectral analysis and increasing uncertainty of the method. This study supports the proposal of an innovative approach to accurately quantify interferences in NAA based on a system allowing irradiations in controlled neutron fields with variable thermal/fast neutron ratios. As calculations are intensively used to optimize the system based on this new approach, the capabilities of simulation tools must be tested against new data to ensure accuracy of the proposed method. A deuterium-tritium (d-T) neutron generator-based facility was used to irradiate metallic samples under tailored conditions. Key reactions investigated were $^{27}$Al(n,γ) and $^{28}$Si(n,p) both producing the $^{28}$Al radio-isotope. Post-irradiation γ spectra were analyzed using a high-purity germanium (HPGe) to determine neutron-induced radio-isotope activity in samples. Monte Carlo simulations and activation calculations accurately reproducing the irradiation conditions were performed and the results compared to the experimental values. This work highlights the potential of controlled neutron fields to resolve longstanding challenges in NAA, paving the way to a versatile and scalable solution for interference quantification and a more accurate material elemental analysis.

KEYWORDS: neutron activation, γ spectrometry, interferences, Monte-Carlo simulation

## 1. INTRODUCTION

Neutron Activation Analysis (NAA) is a powerful, non-destructive analytical technique widely used to determine the elemental composition of samples across various fields, including metallurgy, geology, archaeology, forensics, biomedicine and materials science [1,2]. By
irradiating a sample of material with thermal neutrons, capture (n,γ) reactions are induced on elements present in the material producing radio-isotopes. The subsequent γ-ray emissions from these radio-isotopes are characteristic of the elements present, enabling their identification and quantification even at trace levels. The versatility, sensitivity, and non-destructive nature of NAA make it particularly suited for analysing complex matrices and rare elements.

Despite its strengths NAA faces challenges related to interferences, related to samples being exposed in the real-life irradiation conditions to mixed neutron fields containing both thermal and fast components. When interacting with other nuclei potentially present also in the material under analysis, fast neutrons can produce by various nuclear reactions the same radio-isotope as the thermal neutron capture reaction [3,4].

Several examples of problematic interferences are reported in the analysis of geological samples, where they are produced by the main elements of the matrix. Important nuclear reactions include $ ^{28}\text{Si(n,p)}^{28}\text{Al} $, $ ^{31}\text{P(n,α)}^{28}\text{Al} $, $ ^{27}\text{Al(n,p)}^{27}\text{Mg} $, $ ^{30}\text{Si(n,α)}^{27}\text{Mg} $, $ ^{24}\text{Mg(n,p)}^{24}\text{Na} $ et $ ^{27}\text{Al(n,α)}^{24}\text{Na} $ [5, 6]. For biological samples, some of the important threshold reactions causing interferences are $ ^{24}\text{Mg(n,p)}^{24}\text{Na} $ and $ ^{54}\text{Fe(n,α)}^{51}\text{Cr} $ [3,7]. In metallurgy or archaeology, the most common interferences include the reactions $ ^{27}\text{Al(n,p)}^{27}\text{Mg} $, $ ^{28}\text{Si(n,p)}^{28}\text{Al} $, $ ^{30}\text{Si(n,α)}^{27}\text{Mg} $, $ ^{52}\text{Cr(n,p)}^{52}\text{V} $, $ ^{54}\text{Fe(n,α)}^{51}\text{Cr} $, $ ^{55}\text{Mn(n,α)}^{52}\text{V} $, $ ^{56}\text{Fe(n,p)}^{56}\text{Mn} $, $ ^{59}\text{Co(n,α)}^{56}\text{Mn} $, $ ^{60}\text{Ni(n,p)}^{60}\text{Co} $, $ ^{62}\text{Ni(n,α)}^{59}\text{Fe} $, $ ^{63}\text{Cu(n,α)}^{60}\text{Co} $, $ ^{64}\text{Zn(n,p)}^{64}\text{Cu} $ and $ ^{65}\text{Cu(n,p)}^{65}\text{Ni} $ [8-10].

Such interferences complicate spectral interpretation and compromise the accuracy of the quantitative assessment. Without a good knowledge of the contribution of fast neutrons in the total activity of the radio-isotopes being produced, no appropriate corrections related to the interferences can be applied to the analysis. This generally implies overestimated uncertainties to be adopted in the composition of the materials analysed by NAA to guarantee safety margins and by doing so the method's overall performance is degraded.

To mitigate the effect of the interferences, various strategies have been developed. Radiochemical Neutron Activation Analysis (RNAA) is one such approach, where chemical separation techniques (e.g., extraction, precipitation, or ion exchange) are employed after irradiation to isolate target elements and remove interfering isotopes [3, 7, 11]. While being rather effective, RNAA introduces additional difficulties such as increased complexity, longer analysis times, higher costs, and the potential for residual interferences. Additionally, advanced computational methods including spectrum deconvolution and machine learning techniques offer promising tools for interference correction, however, these are still under development and often cannot fully resolve issues arising from overlapping peaks or reactions involving ultra-trace elements [12, 13].

Our group at CEA (Université Paris-Saclay) recently proposed a new method [14] allowing to control interferences in NAA by irradiation of material samples under accurately established fields with variable thermal/fast neutron ratios in order to influence the contribution of different neutron-induced reactions producing the same radio-isotope. This is achieved by placing the samples at different depths in a high-density polyethylene (HDPE) moderator. The results presented in Figure 1 were obtained by simulations using the MCNP6.2 Monte-Carlo code [15] for a 14.1 MeV d-T generator-type neutron source.

The optimization of the set-up associated to this new method and namely the position of the
New measurements on neutron-induced activation in samples, towards an innovative approach for controlled interferences in Neutron Activation Analysis

samples being irradiated strongly relies on Monte-Carlo simulations coupled to activation calculations. Their accuracy in reproducing the real-life irradiation conditions is therefore crucial to guarantee the robustness of the new method proposed. The first attempt to experimentally validate the method is the main objective of the present study and focusses on a metallic element, namely aluminum, known as being prone to significant interferences during NAA as detailed in Table 1.

<table><caption>Table 1: Example of interference affected neutron activation analysis studied in this work</caption><thead><tr><td>Element under analysis</td><td>Main reaction</td><td>Interference reaction</td><td>Radio-isotope produced</td></tr></thead><tbody><tr><td><sup>27</sup>Al</td><td><sup>27</sup>Al(n,γ)</td><td><sup>28</sup>Si(n,p)</td><td><sup>28</sup>Al</td></tr></tbody></table>

<figure><img src="image_2.png" /><figcaption>Figure 1: Variation with the thickness of the HDPE moderator of the neutron spectrum from a d-T generator (on the left) and of the ratio between thermal and fast neutrons (on the right) as simulated by MCNP6.2.</figcaption></figure>

## 2. EXPERIMENTAL PROCEDURE

### 2.1. Irradiation set-up

The neutron fields used for the irradiations were produced by the Neutron Science Facility (NSF) of the IAEA's Nuclear Science and Instrumentation Laboratory (NSIL) in Seibersdorf, Austria [16]. The neutron source of 14.1 MeV is based on a d-T generator, which is surrounded by a moderator made of water bricks. A 70 cm long, 15 cm wide vertical opening in the water shielding has been filled with HDPE for the purpose of our experiment. Two irradiation positions were used for the samples, one in air close to the neutron generator (at 16 cm) allowing irradiations mainly with fast neutrons and the second inside the HDPE moderator at 50 cm from the generator (Figure 2). The second position corresponds to a moderator thickness of 20 cm allowing a fraction of the 14.1 MeV neutrons produced by the generator to be thermalized and, by doing so, the samples to be irradiated in a mixed thermal/fast neutron field with significant contributions from both thermal and fast components. This is illustrated by the neutron spectra given in Figure 3, obtained by the simulation of the whole set-up with the MCNP6.2 Monte-Carlo code, showing that the contribution of thermal neutrons is increased by a factor of 18.5 with a HDPE moderator thickness of 20 cm. More details on the simulation procedure will be given in subsection 3.2. The two regions in grey
shown in Figure 3 indicate the thermal and fast components of the neutron spectra, which contribute most significantly to the total neutron flux. The contribution of neutrons with energies between these two regions is several orders of magnitude lower and it has been assumed in a first approximation as being negligible. Another important aspect highlighted by the spectra shown in the figure is that thermal neutrons are distributed in a broader energy range than the fast ones, which populate only a narrow peak at 14.1 MeV corresponding to the energy of the initial neutron source produced by the d-T generator.

<figure><img src="image_3.png" /><figcaption>Figure 2: Schematical view of the irradiation set-up at the IAEA's NSF.</figcaption></figure>

<figure><img src="image_4.png" /><figcaption>Figure 3: Simulated neutron spectra with MCNP6.2 at the two irradiation positions at the IAEA's NSF.</figcaption></figure>
# New measurements on neutron-induced activation in samples, towards an innovative approach for controlled interferences in Neutron Activation Analysis

## 2.2. Sample preparation, irradiation and post-activation analysis

A total of 4 metallic samples of aluminum (Al) and silicon (Si) were prepared for neutron activation experiments, allowing the irradiation of each individual material at both irradiation positions. In addition to these samples made of a single material, 2 mixed samples were prepared by stacking two samples of individual materials of approximately the same weight in close contact to obtain the combination Al-Si. The mixed samples allowed for direct observation of interferences under identical irradiation conditions as the ones made of individual materials. The dimensions and masses of the samples were carefully measured. Their characteristics are provided in Table 2, as well as the conditions of irradiation and post-activation $\gamma$ spectrometry measurements.

<table><caption>Table 2. Samples characteristics and irradiation conditions for neutron activation and $\gamma$ spectrometry measurements.</caption><thead><tr><th>Distance (cm)</th><th>Composition</th><th>Mass (g)</th><th>Irradiation time (s)</th><th>Transfer time (s)</th><th>Measurement time (s)</th></tr></thead><tbody><tr><td>50</td><td>Al</td><td>6.672</td><td>3600</td><td>36</td><td>3733</td></tr><tr><td>50</td><td>Si</td><td>5.817</td><td>3600</td><td>47</td><td>3600</td></tr><tr><td>50</td><td>Al-Si</td><td>12.536</td><td>3600</td><td>50</td><td>3600</td></tr><tr><td>16</td><td>Al</td><td>6.675</td><td>3600</td><td>30</td><td>3600</td></tr><tr><td>16</td><td>Si</td><td>5.886</td><td>3600</td><td>44</td><td>3600</td></tr><tr><td>16</td><td>Al-Si</td><td>12.476</td><td>3600</td><td>42</td><td>3600</td></tr></tbody></table>

A motorized carbon-fiber carrier was employed for accurate positioning of the samples at the position close to the generator. At the position at 50 cm the samples were sandwiched between HDPE slabs. The intensity of the neutron source produced by the d-T generator has been measured at 1.6E+08 neutrons/s and its variation during the irradiations is estimated at less than 5%.

Each sample was irradiated for a pre-determined duration to allow sufficient neutron activation so that detectable yields of radio-isotopes are produced in the samples. After irradiation the samples were transferred to a low-background set-up using a high-purity germanium (HPGe) detector for $\gamma$ spectrometry analysis. The time between the end of irradiation and the start of the $\gamma$ measurement (transfer time $t_{trans}$) was minimized and carefully recorded to account for the decay of short-lived isotopes. The dead time for all $\gamma$ spectra acquisition was negligible because of the relatively low activity of the samples. Peaks at specific energies in the measured spectra subsequently allowed the identification of the radio-isotopes produced by neutron-induced reactions on the elements present in the samples and in particular $^{28}$Al, previously identified as of interest for this study being produced by both main neutron capture (n,$\gamma$) and interference reactions. The identification of the radio-isotopes from the energies of the peaks in the spectra for the activated samples has been performed based on state-of-the-art nuclear data library developed in the frame of the DDEP project (Decay Data Evaluation Project), maintained and continuously updated by the French laboratory for the metrology of ionizing radiation (LNHB) [17].
The γ spectra were further processed to determine the activity of radioactive isotopes at the time of measurement (A₀). A background spectrum was recorded over a 24-hour period and scaled to match the measurement time of each sample. The scaled background was subtracted from the sample spectra to isolate net counts (Cₙet). To calculate the activity of the radio-isotopes at the time of measurement, the following Eq. 1 was used:

$$A_0 = \frac{C_{net}}{\epsilon(E) \cdot P_{\gamma} \cdot t_{meas} \cdot DF} \cdot f_1 \cdot f_2 \qquad \text{Eq. 1}$$

Where:

* ε(E) is the detection efficiency, obtained from a polynomial calibration curve fitted to experimental efficiency data shown on Figure 4.

* Pγ is the γ emission probability (branching ratio) of the isotope, which accounts for the fraction of decays that produce the γ-ray associated with the peak.

* tmeas is the measurement time.

* DF = e⁻⁻λttrans is the decay factor accounting for decay during the transfer time (ttrans)

* f₁ is the self-attenuation correction factor.

* f₂ is the decay correction factor that take into account the decay of the radionuclide during the γ spectrometry measurement.

The efficiency of the HPGe detector, ε(E), was calibrated using a set of known γ-ray sources. The efficiency curve was fitted using the following empirical function [18]:

$$\epsilon(E) = \exp \left( a + b \cdot \ln(E) + c \cdot (\ln(E))^2 + d \cdot (\ln(E))^3 + \frac{e}{E} + \frac{f}{E^2} \right) \qquad \text{Eq. 2}$$

where E is the γ-ray energy, and a, b, c, d, e and f are the fit parameters.

For radio-isotopes with half-lives comparable to or smaller than the duration of the γ spectrometry measurement their decay during the measurement must be taken into account. This was done by multiplying the measured activity by the decay correction factor calculated according to Eq. 3 [19]:

$$f_2 = \frac{\lambda \cdot t_{meas}}{1 - e^{-\lambda t_{meas}}} \qquad \text{Eq. 3}$$

Rather than propagating the uncertainties of the individual fit parameters, which can lead to instability due to the exponential term in the function, a different approach was adopted in order to guarantee that the interpolated efficiency values and their associated uncertainties were both
New measurements on neutron-induced activation in samples, towards an innovative approach for controlled interferences in Neutron Activation Analysis

consistent with the experimental data and robust against potential instabilities in the fitting process. Therefore, a 5% relative uncertainty was assumed for each of experimentally measured efficiency points, representing the combined effects of statistical fluctuations, systematic calibration errors, and other potential sources of variation. The uncertainty on the interpolated values is considered to be 5%, equal to the uncertainty assumed on the experimental efficiency points. Figure 4 illustrates the experimental efficiency points, the fitted efficiency curve, and the interpolated uncertainty band.

<figure><img src="image_5.png" /><figcaption>Figure 4. Plot of the experimental efficiency points with fitted efficiency curve and the 5% uncertainty band.</figcaption></figure>

A comprehensive uncertainty analysis was performed to assess the reliability of the measured activity values. The total uncertainty ($\sigma_A$) affecting the measured activity was expressed as:

$$ \sigma_{A_0} = A_0 \sqrt{\left(\frac{\sigma_{C_{net}}}{C_{net}}\right)^2 + \left(\frac{\sigma_{\epsilon(E)}}{\epsilon(E)}\right)^2 + \left(\frac{\sigma_{P_Y}}{P_Y}\right)^2 + \left(\frac{\sigma_{t_{meas}}}{t_{meas}}\right)^2 + \left(\frac{\sigma_{DF}}{DF}\right)^2 + \left(\frac{\sigma_{f_1}}{f_1}\right)^2 + \left(\frac{\sigma_{f_2}}{f_2}\right)^2} $$

Eq. 4

# 3. RESULTS AND DISCUSSION

## 3.1. Measurement of neutron-induced activities in the samples

Spectra measured for pure Al and Si samples for the two irradiation positions are shown in Figures 5 and 6 below. The isotopes highlighted in red are present in the spectra corresponding to both irradiation distances (16 cm and 50 cm from the neutron generator), while those marked in dark blue are exclusively observed in the spectra of samples irradiated at 16 cm from the neutron generator, being so produced mainly under the higher, fast neutron flux close to the generator. The radio-isotope $^{28}$Al of interest for the study of interferences has been identified in the measured spectra.
<figure><img src="image_6.png" /><figcaption>Figure 5. Background-subtracted $\gamma$ spectrum of the pure aluminum samples activated by irradiation at 16 cm (in black) and at 50 cm (in green) from the neutron source.</figcaption></figure>

<figure><img src="image_7.png" /><figcaption>Figure 6. Background-subtracted $\gamma$ spectrum of the pure silicon samples activated by irradiation at 16 cm (in black) and at 50 cm (in green) from the neutron source.</figcaption></figure>

The activity of $^{28}$Al in all the irradiated samples has been determined from the corresponding measured $\gamma$ spectra based on the formula given in Eq. 1. The following values for the key parameters were used, which are crucial for obtaining accurate and reliable activity measurements:

- The mean energy measured for the $\gamma$ emission of $^{28}$Al was found to be 1778.14 ± 0.05 keV.

- The branching ratio for this $\gamma$ line is 100 ± 0%.
New measurements on neutron-induced activation in samples, towards an innovative approach for controlled interferences in Neutron Activation Analysis

- The half-life of $^{28}$Al was taken to be 134.48 ± 0.07 s [17].

- The efficiency of the HPGe detector at the energy of interest was calculated at 3.3568×10⁻² ± 0.0056×10⁻².

The experimentally obtained activity values are given in Table 3, together with the activities determined based on Monte-Carlo simulation of the experimental set-up coupled with an activation calculation code as it will be discussed in the following subsection.

## 3.2. Simulation of experimental conditions and calculation of activities in the samples

The experimental set-up has been simulated using the MCNP6.2 code with a detailed geometry model taking into account all the elements strongly influencing the neutron flux and their energy. The distribution of the calculated neutron flux over the modelled geometry is presented in Figure 7. The neutron energy distributions at the two irradiation positions (Figure 3) have been calculated with MCNP6.2 using the specific CCFE scheme with 709 energy groups, allowing further activation calculations to be performed with the FISPACT-II code [20] using the option of neutron-induced reactions cross-sections from the TENDL library [21].

FISPACT-II allows us to accurately reproduce the irradiation and decay sequences as they were recorded during the experiments. Based on the neutron flux value and the energy distribution previously calculated by the simulations with the MCNP6.2 code at the sample location and considering the known irradiation duration and the intensity of the neutron source produced by the d-T generator of 1.6E+08 neutrons/s, it uses the energy-dependent cross-section values from the TENDL library to calculate the yields of radio-isotopes produced in each sample by the neutron-induced nuclear reactions on the stable nuclei present in its initial composition. Decay data libraries are further used to calculate the weight of these radio-isotopes at the time after the sample irradiation corresponding to the γ spectrometry measurements.

The calculations predictions for the activity of $^{28}$Al in the 7th column of Table 3, thus simulating as accurately as possible the real experimental conditions, can then be directly compared to the values obtained by measurements. A sufficient number of histories have been used so that the statistical uncertainties affecting the simulated values can be neglected.

<figure><img src="image_8.png" /><figcaption>Figure 7: 2D distribution of the MCNP6.2 simulated neutron flux at the IAEA's NSF and indication of the positions of the samples activated during the experiment.</figcaption></figure>
### 3.3. Discussion

The measured values of the activity given in Table 3 show that the production of $^{28}$Al in the single-material aluminum sample through $^{27}$Al(n,γ) reaction is decreased by a factor of 3.2 between the two irradiation positions, closely matching the behavior of the thermal neutron flux which decreases by a factor of 3.4 according to the calculated spectra from Figure 3. When the radio-isotope is produced by the reaction $^{28}$Si(n,p) with fast neutrons, the measured activity in the sample irradiated at 16 cm is 37 times higher compared to the irradiation at 50 cm, in disagreement by a factor of 2 with the variation of the calculated flux of fast neutrons by a factor of 74 between the two positions.

The irradiations of the samples made of Al-Si mixtures confirm the possibility to control the interferences by varying in a customized manner the moderator's thickness and consequently the thermal/fast neutrons ratio. Indeed, the measured activity of $^{28}$Al produced by neutrons in the Al-Si samples show that the irradiation position at 50 cm (after 20 cm thick HDPE moderator), increasing in theory the ratio thermal/fast by a factor of 18.5 so that the contribution of the main $^{27}$Al(n,γ) reaction becomes dominant compared to the irradiation at 16 cm when the interference reaction $^{28}$Si(n,p) is the main contributor, results in an activity increase by a factor of 3.2. The later factor has been estimated by normalizing the measured activity in the samples irradiated at the two positions to the same total (thermal + fast) neutron flux in order to take into account exclusively the effect of neutron thermalization by the moderator and thus ignore the difference in solid angle. It must be pointed-out that one can't necessarily expect to retrieve in the induced activity values the increase by 18.5 of the thermal/fast ratio since the production of $^{28}$Al depends not only on the neutron flux, either thermal or fast, but also on the probability of the corresponding $^{27}$Al(n,γ) or $^{28}$Si(n,p) reactions to occur which may differ significantly and thus reshape the trend.

<table><caption>Table 3: Summary of the results for measured and calculated activities in the samples.</caption><thead><tr><th>Sample material</th><th>Radio-isotope</th><th>Location</th><th>Calculated φ<sub>th</sub>/φ<sub>fast</sub></th><th>Dominant reaction</th><th>A<sub>measured</sub> (Bq/g)</th><th>A<sub>calculated</sub> (Bq/g)</th><th>Ratio A<sub>calculated</sub>/A<sub>measured</sub></th></tr></thead><tbody><tr><td>Al</td><td><sup>28</sup>Al</td><td>16 cm</td><td>0.02</td><td><sup>27</sup>Al(n,γ)<sup>28</sup>Al</td><td>50.94±1.2</td><td>52.26</td><td>1.03</td></tr><tr><td>Al</td><td><sup>28</sup>Al</td><td>50 cm</td><td>0.37</td><td><sup>27</sup>Al(n,γ)<sup>28</sup>Al</td><td>15.71±0.6</td><td>13.61</td><td>0.87</td></tr><tr><td>Si</td><td><sup>28</sup>Al</td><td>16 cm</td><td>0.02</td><td><sup>28</sup>Si(n,p)<sup>28</sup>Al</td><td>224.65±3.6</td><td>114.14</td><td>0.51</td></tr><tr><td>Si</td><td><sup>28</sup>Al</td><td>50 cm</td><td>0.37</td><td><sup>28</sup>Si(n,p)<sup>28</sup>Al</td><td>6.02±0.38</td><td>4.03</td><td>0.67</td></tr><tr><td>Al-Si</td><td><sup>28</sup>Al</td><td>16 cm</td><td>0.02</td><td><sup>28</sup>Si(n,p)<sup>28</sup>Al</td><td>154.84±2.3</td><td>79.13</td><td>0.51</td></tr><tr><td>Al-Si</td><td><sup>28</sup>Al</td><td>50 cm</td><td>0.37</td><td><sup>27</sup>Al(n,γ)<sup>28</sup>Al</td><td>8.97±0.32</td><td>8.69</td><td>0.97</td></tr></tbody></table>

The comparison between measured and calculated $^{28}$Al activities allow to conclude that the calculations agree relatively well with the measurements when the production of the radio-isotope occurs mainly by the capture $^{27}$Al(n,γ) reaction, in other words when thermal neutrons are contributing the most. On the other hand, the calculated activity of this radio-isotope is underestimated by around a factor of 2 when its production is mainly due to fast neutrons through the reaction $^{28}$Si(n,p). In the general context of the induced activity calculations for various common applications related for example to radiation protection or waste management for decommissioning, this level of agreement between the calculations and the measurements is considered as satisfactory, especially since the calculated values were exclusively obtained by simulating the experimental procedure without any additional adjustment. A disagreement of a factor 2 is on the other hand not in line with the objective of this work which consists of studying the possibility to improve the precision of the NAA by a better control of the interferences. A more
New measurements on neutron-induced activation in samples, towards an
innovative approach for controlled interferences in Neutron Activation Analysis

in-depth analysis of this disagreement is therefore necessary in order to identify its origin allowing
to formulate possible solutions for improving the calculations accuracy.

The input parameters for the activity calculations with FISPACT-II code related to irradiation and
decay times cannot be a significant source of inaccuracy since the same values as the ones
rigorously recorded during the experiment and given in Table 2 were used.

The energy distributions of neutrons calculated by simulations of the experimental set-up with MCNP6.2 and presented in Figure 3 are used directly by FISPACT-II to calculate the activity induced by the irradiation in the samples. They are therefore crucial parameters with strong influence on calculations results. The activity of radio-isotopes after irradiations is directly correlated to the total number of neutrons to which samples were exposed but also to their energies since the cross-sections for the different reactions involved are energy-dependent and their values provided by the TENDL library. Several simulation aspects such as the geometry model and the composition of materials are responsible for the accuracy of the calculated neutron spectra and despite all the precautions some errors may persist, the simulation ultimately being only an approximation of the real configuration. Therefore, the calculated neutron spectra can only be validated by comparing them to measurements, which is not possible at this stage since there are currently no measured spectra at the NSF where the experiments have been performed.

Finally, the neutron-induced activity in samples strongly depends on the probabilities of the
reactions leading to the production of $^{28}$Al by thermal and fast neutrons, through respectively
$^{27}$Al(n,γ) and $^{28}$Si(n,p) reactions. Figure 8 shows the cross-sections for these two reactions, with
the energy ranges of interest based on the calculated neutron spectra from Figure 3 highlighted in
grey.

<figure><img src="image_9.png" /><figcaption>Figure 8: Cross-sections for the neutron-induced reactions of interest for this study. Experimental values from EXFOR data library [22] are represented with symbols, evaluated cross-sections from TENDL library with continuous lines.</figcaption></figure>

For thermal neutrons the experimental cross-section values are consistent with each other and well
reproduced by the evaluated ones from the TENDL library used by the FISPACT-II code to
calculate the induced activity in samples. At 14.1 MeV the values are significantly different
between data sets and the cross-section has been evaluated in the TENDL library probably by best
fitting the different experimental values. This potentially leads to an underestimation by as much
as a factor of 2 of the $^{28}$Al production which could explain the disagreement found between the
measured and calculated activity values in Table 3. In addition, the strong variations of the ²⁸Si(n,p)
reaction cross-section may be related to resonances, effect which would be completely missed by
the evaluated cross-sections from TENDL.

4. CONCLUSIONS AND PERSPECTIVES

We report in this work measurements on neutron-induced activity dedicated to the study of a
novel method to improve accuracy of the Neutron Activation Analysis (NAA) by an increased
control of interference reactions which, as has been demonstrated by the results, can be
achieved by precise variations of the ratio between thermal and fast neutrons through
customized sample irradiations at different moderator depths.

Specific challenges posed by neutron-induced reactions and spectral interferences were
explored in depth. Calculations of induced activity were performed and compared to
experimental data in order to test the accuracy of computational tools in modelling the physics
involved, for their future use in the optimization of the new method and the associated system.

The experimental results on <sup>28</sup>Al production were consistent with expectations and with
calculations results when it occurs mostly through the main reaction used in NAA namely the
neutron capture <sup>27</sup>Al(n,γ). However, when using samples of pure Si and Al-Si mixture allowing
to study the interferences, the calculated values underestimate the measurements by around a
factor of 2, attesting inadequate accounting for fast neutron reactions by the simulation tools.
This finding highlighted on one hand the need for improved experimental characterization of
fast neutron flux allowing to validate the values obtained through Monte-Carlo simulations
and for increased accuracy of evaluated cross-section libraries, such as TENDL powering the
activation calculations with the code FISPACT-II, on the other hand. Developments in
evaluated libraries being a long process and considering that interferences in NAA refer to a
limited number of very specific reactions extensively covered for most cases in experimental
data libraries such as EXFOR, more straightforward and effective improvements in their
assessment can be achieved by the direct use of experimental cross section values instead of
evaluated ones to calculate neutron-induced activities in irradiated samples.

This work emphasizes the critical role of neutron energy distributions and reaction cross
sections in interpreting activation analysis results. The findings underline the need for refined
methods to mitigate spectral interferences and to account for varying neutron flux
contributions. The insights gained contribute to advancing the accuracy of NAA for complex
sample matrices.

ACKNOWLEDGMENTS

Authors would like to acknowledge the financial support provided by the French National Laboratory of Metrology and Testing. We also express our gratitude to the staff of the Nuclear Science and Instrumentation Laboratory at the IAEA (Seibersdorf), particularly Dr. Kalliopi Kanaki and Dr. Danas Ridikas.
# New measurements on neutron-induced activation in samples, towards an innovative approach for controlled interferences in Neutron Activation Analysis

## REFERENCES

[1] De Soete D., Gijbels R., Hoste J., « Neutron Activation Analysis », Wiley-Interscience, New York (1972).

[2] Greenberg R. R., Bode P., Fernandes E. A. D. N., « Neutron activation analysis: A primary method of measurement », *Spectrochim. Acta* B 66, 193 (2011).

[3] Cornelis R., Hoste J., Versieck J., « Potential interferences inherent in neutron-activation analysis of trace elements in biological materials », *Talanta* 29, 11 (1982), pp. 1029–1034.

[4] Wasim M., « Interferences in instrumental neutron activation analysis by threshold reactions and uranium fission for miniature neutron source reactor », *Radiochim. Acta* 101, 9, pp. 601–606 (2013).

[5] Wasim M., Arif M., Zaidi J. H., Fatima I., « Quantitative analysis of ancient Chinese ceramic using k0-instrumental neutron activation analysis », *Radiochim. Acta* 96, 863 (2008).

[6] Millard H. T., « Neutron activation determination of iridium, gold, platinum, and silver in geologic samples », *J. Radioanal. Nucl. Chem.* 113, 125–132 (1987).

[7] Chajduk E., Polkowska-Motrenko H., « Neutron Activation Analysis: Application in Bioanalytical Sciences », in Buszewski B., Baranowska I. (eds), *Handbook of Bioanalytical Sciences*, Springer, Cham (2022).

[8] Wasim M., Ahmad S., Arif M., Daud M., Nawaz H., « Comparative performance of semi- absolute k0-instrumental neutron activation analysis and inductively coupled plasma optical emission spectrometry (ICP-OES) for compositional decoding of aluminum base alloys », *Radiochim. Acta* 99, 187 (2011).

[9] Moreira E. G., Vasconcellos M. B. A., Saiki M., « Instrumental neutron activation analysis applied to the determination of the chemical composition of metallic materials with study of interferences », *J. Radioanal. Nucl. Chem.* 264, 45 (2005).

[10] García-Heras M., Fernández-Ruiz R., Tornero J. D., « Analysis of Archaeological Ceramics by TXRF and contrasted with NAA », *J. Archaeol. Sci.* 24, 11 (1997), pp. 1003–1014.

[11] Smodiš B., Benedik L., Jaćimović R., « Analytical radiochemistry of neutron activated samples », *J. Radioanal. Nucl. Chem.* 318, pp. 1641–1647 (2018).

[12] Huseyin S., Xin L., « γ spectral analysis by artificial neural network coupled with Monte Carlo simulations », *Nucl. Instrum. Methods Phys. Res. A* 953, 163062 (2020).

[13] Nunes W. V., da Silva A. X., Crispim V. R., Schirru R., « Explosives detection using prompt-γ neutron activation and neural networks », *Appl. Radiat. Isot.* 56, 6, pp. 937–943 (2002).

[14] Patent number FR2406712

[15] Werner C. J., « MCNP Users Manual - code version 6.2 », LA-UR-17-29981.

[16] Gan P. et al., « Progress in commissioning a neutron/X-ray radiography and tomography systems at IAEA NSIL », *JINST* 17, T11001 (2022).

[17] Dulieu C., Kellett M., Mougeot X., « Dissemination and visualisation of reference decay data from Decay Data Evaluation Project (DDEP) », *EPJ Web Conf.* 146 (2017), p. 07004.

[18] Sánchez-Reyes A. F., Febrián M. I., Baró J., Tejada J., « Absolute efficiency calibration function for the energy range 63–3054 keV for a coaxial Ge(Li) detector », *Nucl. Instrum. Methods Phys. Res. B* 28, 1 (1987), pp. 123–127.

[19] Fitzgerald R. « Corrections for the combined effects of decay and dead time in live-timed counting of short-lived radionuclides », *Appl Radiat Isot.*, vol. 109, pp. 335–340 (2016).

[20] Sublet J.-Ch., et al., « FISPACT-II: An Advanced Simulation System for Activation,
Transmutation and Material Modelling », Nucl. Data Sheets, vol. 139, pp. 77-137, (2017).

[21] Koning A.J., et al., « TENDL: Complete Nuclear Data Library for Innovative Nuclear Science and Technology », Nucl. Data Sheets, vol. 155, pp. 1-55 (2019).

[22] Otuka N., et al., « Towards a More Complete and Accurate Experimental Nuclear Reaction Data Library (EXFOR): International Collaboration Between Nuclear Reaction Data Centres (NRDC) », Nucl. Data Sheets, vol. 120 272 (2014).