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- MakaleYalnız künye2025Scopus SJRQ3Interpretable 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.
AtıfScopus4WoS3OpenAlex3İncele - MakaleYalnız künye2022Scopus SJRQ1Effect 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.
AtıfScopus31WoS27OpenAlex36İncele