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Yayınlar
- MakaleAçık Erişim2026Enhancing precision of low-cost detectors via machine learning for accurate mass attenuation coefficient estimation
Düzgün, İ.; Küçük, M.A.; Kaya, S.; Çelik, N.
Low-cost NaI(Tl) detectors are practical for gamma-ray spectrometry but their limited energy resolution can introduce systematic errors in mass attenuation coefficient measurements when scattered photons are included in the peak region. This study proposes a machine-learning correction framework that maps NaI(Tl)-derived attenuation coefficients to XCOM-based HPGe-equivalent reference values through a dimensionless correction factor. An EGS4/XCOM dataset of 756 model-development configurations, covering 18 atomic numbers, six monoenergetic photon energies, and seven collimator radii, was used to train twelve regression models and evaluate them over 60 randomized train–validation–test cycles. Sodium and Bismuth were withheld for external material-wise validation. Gaussian Process Regression with a Matérn 5/2 kernel provided the best overall testing performance. For the withheld materials, the correction reduced the mean deviation from XCOM references from 3.07% to 0.83%, supporting its use as a practical correction layer for low-cost attenuation measurements.
- MakaleAçık Erişim2026A combined Monte Carlo, analytical, and experimental study of true coincidence summing correction factors for 152Eu
Çelik, Necati; Ali, Ahmed H.; Apaydin, Gokhan; Çevik, Ugur; Açikel, Selami
The radionuclide 152Eu presents a significant challenge in gamma-ray spectrometry due to its complex decay scheme and significant true coincidence summing (TCS) effects, especially in close-measurement geometries. This study presents a comprehensive investigation into TCS correction factors for the principal gamma-ray lines of 152Eu using tripartite methodology: a custom Monte Carlo (MC) simulation based on the EGS4 system, an established analytical method, and direct experimental measurements. The MC simulation explicitly models the complete decay process, including branching ratios, gamma emissions, internal conversion, and subsequent X-ray emissions for both decay branches (beta-minus to 152Gd and EC to 152Sm). Experimentally, correction factors were derived using a well-characterized point source measured at multiple distances with a coaxial HPGe detector. The analytical, method based on probabilistic analysis of the decay scheme, served as an examination. Results demonstrate that the analytical method underestimated the TCS correction factors, particularly for low-energy lines such as 121.78 keV, where it predicted a mere 0.78 % correction compared to 25.5 and 23.5 % from MC and experiment, respectively. This discrepancy is attributed to the analytical method's neglect of gamma-X ray coincidences and the internal conversion effects. In contrast, the MC simulation showed remarkable agreement with experimental results across all energies, validating its capability to accurately model the full complexity of TCS effects. The study concludes that while analytical methods offer rapid estimates, MC simulations, especially when experimentally validated, are essential for achieving metrological accuracy in the gamma-ray spectrometric analysis of complex radionuclides like 152Eu.
- MakaleYalnız künye2025Interpretable machine learning for rapid prediction and calibration of HPGe detector efficiency: a physics-informed approach and online platform
Yesilkanat, Cafer Mert; Celik, Necati; Celik, Ahmet; Cevik, Ugur
This study introduces a novel, physics-informed, and calibration-friendly hybrid machine learning framework for the rapid and accurate prediction of the Full Energy Peak (FEP) efficiency in High-Purity Germanium (HPGe) detectors. To overcome the limitations of conventional “black-box” models, our two-stage approach first represents the FEP efficiency curve using a physically interpretable logarithmic polynomial. Subsequently, machine learning models were trained to predict the polynomial coefficients directly from the detector geometric parameters using a comprehensive dataset generated via Monte Carlo simulations. Among the various algorithms tested, the Generalized Linear Model yielded superior performance, achieving R2 values of 0.975–0.992 for the coefficients. While raw model predictions showed expected variability, a key feature of our framework (a single-point calibration protocol using one known efficiency value) dramatically improved accuracy, reducing the mean absolute percentage error by an average of 80% on the independent test data. The calibrated model was further validated using an experimental detector. The entire framework was deployed as a user-friendly online platform, enabling researchers to instantly generate and calibrate efficiency curves. Our work successfully harmonizes interpretability, speed, and accuracy, offering a powerful tool for the design, optimization, and routine calibration of HPGe detectors.
- MakaleYalnız künye2023Effect of detector crystal size on Compton suppression factors
Kaya, Selim; Çelik, Necati; Gök, Abdulkadir; Çevik, Uğur
The geometrical parameters which affect the suppression factor for an HPGe (High Purity Germanium)-NaI Compton suppression spectrometer were studied by a Monte Carlo simulation with the EGS4 system. The spectrums were crated for 5 energy values ranging from 200 keV to 2 MeV. Compton suppression factors (CSFs), the parameters characterizing the system performance, were calculated for different HPGe crystal parameters. It was observed that to obtain better Compton suppressed factors, a laboratory must choose as small HPGe crystal as possible for energy values up to 400 keV. However, for higher energies up to 2 MeV, larger HPGe crystals provide better Compton suppression systems. These findings suggest that the choice of HPGe crystal size can significantly impact the performance of a Compton suppression spectrometer and should be carefully considered in its design and optimization.
- MakaleYalnız künye2022Effect of front, lateral and back dead layer thicknesses of a HPGe detector on full energy peak efficiency
Kaya, Selim; Çeli̇k, Necati; Bayram, Tuncay
As well known, High Purity Germanium (HPGe) detectors have a wide range of applications in every area where radiation detection and measurements are involved. One of the most important parameters in this respect is the determination of the full energy peak (FEP) efficiency. There are certain parameters affecting the so-called FEP efficiency. Perhaps the most important one is the thickness of dead layers of the crystal itself. In the current study, we investigated the effects of the thickness of front, lateral and back dead layer thicknesses of the detector crystal on the FEP efficiencies for the energy range 30 keV–5 MeV using EGS4 Monte Carlo simulation package. It was shown that the change in the thickness of the front dead layer has significant effect on the efficiency values for the energy interval 30–400 keV. The change in the thickness of the lateral and back dead layer was shown to have significant effects on the efficiencies for the energy intervals 2–3 MeV and 3–5 MeV, respectively. The results were checked using GEANT4 and a good agreement was observed.