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.

Celik, Necati; Altin, Duygu; Cevik, Ugur

A new method was presented for the purpose of volumetric water content determination in any soil sample by gamma-ray transmission. Monte Carlo (MC) simulation technique was used to determine the functional behavior of the linear attenuation coefficient of soil samples having different water contents for three soil samples. Using this functional behavior, the linear attenuation coefficients of dry soil and water were obtained from the intercept and the slope, respectively. It was experimentally shown that the mass attenuation coefficients of soil samples were not sensitive to the chemical composition but only to the physical density. This independence was exploited in this study to obtain the linear attenuation coefficient of a completely dry soil which was found to be 0.1409, 0.1274, and 0.1657 cm−1 for Gumushane, Ardahan, and Trabzon soil, respectively. The linear attenuation coefficient of water was determined to be 0.09 cm−1. Then, the volumetric water contents were obtained by measuring the gamma-ray intensities passed through three wet soil samples. The results were found to be 0.186, 0.182, and 0.214 cm3 cm−3 for Gumushane, Ardahan, and Trabzon soil, respectively. The results obtained by the method introduced were compared with the results obtained using gravimetric method. A very good agreement was observed.

Celik, Necati; Altin, Duygu; Cevik, Ugur

In the presented study, a code was created for the purpose of true coincidence summing (TCS) correction factors for 134Cs. The created code was implemented in EGS4 Monte Carlo simulation package. TCS factors were determined for nine different energies for different detector-source geometries. The calculated results were successfully validated by an empirical method using a point 134Cs radioactive source and a p-type HPGe detector having 55% relative efficiency. Although the code created gives TCS factors only for 134Cs, the technique presented can be used to obtain the factors for any radionuclide used in gamma-ray spectrometry.

Koz, Bahadir; Cevik, Ugur; Bulut, Volkan Numan; Kaya, Selim; Gundogdu, Ali; Celik, Necati

The heavy metal analysis of mosses in the Black Sea region of Turkey was determined using atomic absorption spectrometry method. The procedure was also validated by analysis of standard reference material (IAEA-336 Lichen). A qualitative analysis showed that the samples contained chromium, manganese, cobalt, nickel, copper, zinc, and lead. While the mean concentration values of Cr, Mn, Co, Ni, Cu, Zn, and Pb in the moss samples collected from city centers are 60.6, 820, 12.2, 18.8, 293, 181 and 39.8 mg.kg-1, the mean concentration values in the moss samples collected from the city intervals are 43.8, 761, 11.0, 15.6, 242, 170 and 38.4 mg.kg-1, respectively. Since this study was a heavy metal analysis along the highway, evaluation of these elements with their potential hazards for ecology and human was briefly discussed. A strong relationship was observed between Pb concentration and the traffic density.

Koz, Bahadir; Cevik, Ugur; Celik, Necati

This study was performed in one of the most important parks of Turkey, the Hatila national park, where a gold mining activity is planned to be conducted. For this purpose, 40 moss samples were collected for heavy metal and radioactivity measurements. A radioisotope excited Xray fluorescence analysis using the method of multiple standard additions was applied for the elemental analysis of mosses collected in Hatila valley national park in the Eastern Black Sea region of Turkey. An annular 50 mCi 241Am radioactive source and annular 50 mCi 55Fe radioactive sources were used for excitation of characteristic K-X rays. An Si(Li) detector which had a 147eV full width at half maximum for 5.9 keV photons was used for intensity measurements. A qualitative analysis of spectral peaks showed that the samples contained potassium, calcium, titanium, iron, tin and barium with average concentrations of 230, 5340, 450, 70, 4 and 33 mg.kg -1, respectively. 137Cs and 40K using gamma-ray spectroscopy were determined in 40 moss species collected from the Hatila valley national park. Average activity concentrations of 40K and 137Cs were found to be 103 and 272 Bq.kg -1, respectively. As the region was shown to be heavily contaminated by the Chernobyl accident, the high concentration of 137Cs could be due to this accident. The results are compared with those obtained in different parts of the world where gold mining activities are being conducted. The possible consequences of these results are briefly discussed from the point of potential hazards to ecology and human health.