A comparative study of machine learning and conventional methods for determining the dead layer thickness of an HPGe detector
N.D. Thong, N.H.K. Vi, L.N.D. Uyen, N.V. Thiem, T.T. Thanh, V.T. Minh, P.L. Ho, C.T. Tai, C.V. Tao
Radiation Physics and Chemistry 249(2026)114162
Abstract:
The dead layer of p-type HPGe detectors grows progressively due to lithium diffusion, degrading detection efficiency at low gamma-ray energies. This study compares four regression approaches for dead layer estimation— conventional G4-scan interpolation, single-source Linear Regression (LR), single-source Random Forest (RF), multi-source LR and multi-source RF combining 241Am and 109Cd — applied to an ORTEC GEM50P4-83 detector at two epochs separated by eight years. A single Geant4 simulation campaign (N = 107 events/run, 1301 points) trained all models, with GUM-compliant uncertainties throughout. All four ML predictions agree with the G4-scan reference (1.323 ± 0.019 mm) within 0.006 mm for the 2018 dataset. When Beer–Lambert linearity is confirmed (R2 > 0.998) and features are restricted to 𝑙𝑛(𝜖), Linear Regression achieves a crossvalidated MAE of 0.009 mm, outperforming all tree-based benchmarks (MAE = 0.010 mm), consistent with the Gauss–Markov theorem. A quantitative threshold analysis shows that multi-source LR reduces total uncertainty by 27% when 𝛿𝜖Cd ∕𝜖Cd < 2.04% — a condition satisfied by the present measurements. Dead layer growth rates of 0.208 mm/year (2015–2018) and 0.009 mm/year (2018–2026) are consistent with nonlinear lithium diffusion deceleration.
More detail: https://doi.org/10.1016/j.radphyschem.2026.114162
A benchmark for Monte Carlo simulations in gamma-ray spectrometry Part II: True coincidence summing correction factors
M.-C. Lépy, C. Thiam, M. Anagnostakis, C. Cosar, A. de Blas, H. Dikmen, M.A. Duch, R. Galea, M.L. Ganea, S. Hurtado, K. Karfopoulos, A. Luca, G. Lutter, I. Mitsios, H. Persson, C. Potiriadis, S. Röttger, N. Salpadimos, M.I. Savva, O. Sima, T.T. Thanh, R.W. Townson, A. Vargas, T. Vasilopoulou, L. Verheyen, T. Vidmar
Applied Radiation and Isotopes, 2023
Abstract:
The goal of this study is to provide a benchmark for the use of Monte Carlo simulation when applied to coincidence summing corrections. The examples are based on simple geometries: two types of germanium detectors and four kinds of sources, to mimic eight typical measurement conditions. The coincidence corrective factors are computed for four radionuclides. The exercise input files and calculation results with practical recommendations are made available for new users on a dedicated webpage.
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A benchmark for Monte Carlo simulation in gamma-ray spectrometry
M.C. Lépy, C. Thiam, M. Anagnostakis, R. Galea, D. Gurau, S. Hurtado, K. Karfopoulos, J. Liang, H. Liu, A. Luca, I. Mitsios, C. Potiriadis, M.I. Savva, T.T. Thanh, V. Thomas, R.W. Townson, T. Vasilopoulou, M. Zhang
Abstract:
Monte Carlo (MC) simulation is widely used in gamma-ray spectrometry, however, its implementation is not always easy and can provide erroneous results. The present action provides a benchmark for several MC software for selected cases. The examples are based on simple geometries, two types of germanium detectors and four kinds of sources, to mimic eight typical measurement conditions. The action outputs (input files and efficiency calculation results, including practical recommendations for new users) are made available on a dedicated webpage.
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210Po in Paddy Soils and Rice Grains in Chau Doc, An Giang, Vietnam: Activity Concentration, Soil-to-Rice Transfer, and Health Hazard
Van Thang Nguyen, Nguyen Phong Thu Huynh, Cong Hao Le
Science & Technology Development Journal, 24(4):1-10
Abstract:
Introduction: Soil-to-rice transfer factors (TF) are widely used to predict radionuclides' activity concentrations in rice plants. Since rice (Oryza sativa L.) is one of the most popular crops in Vietnam, the radiological risks due to 210Po contaminating rice grains and the TF must be concerned.
Methods: Alpha spectrometry measured the activity concentration of 210Po in rice and soil samples collected in Chau Doc, An Giang province. TF for the uptake of 210Po from soil to rice plant has been calculated the ratio of the dry weight concentration in the plants to the dry weight concentration in the specified soil layer. Assessment of radiological risks due to ingestion of rice grains was based on estimation of the effective dose.
Results: The activity concentrations of 210Po were in the ranges of 63.77 – 117.75 Bq kgdry weight-1 and 7.38 – 14.16 Bq kgdry weight-1 in soils and rice grains, respectively. Based on the radiation dose assessment, the accumulation of 210Po in rice grains was not considered for public health. The average TF values of 210Po were 0.12, 0.11, and 0.37 for grains, straws, and roots, respectively. Our TF values for rice were higher than the corresponding values found by other studies and the IAEA TRS-472 report.
Conclusion: The analytical method for 210Po determination using alpha spectrometry can be applied for further studies in the field of environmental radioactivity. The measured TF values can be used to predict the radioactivity level of 210Po in rice plants cultivated in other fields in the Mekong Delta region.
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Bằng chứng thực nghiệm trực tiếp chứng minh tính hai-lần số “Magic” của 78Ni đã được công bố trên tạp chí Nature ngày 2/5/2019...
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Dù đóng vai trò quan trọng trong giải quyết những vấn đề toàn cầu như cung cấp năng lượng sạch, giảm phát thải, hướng tới phát triển xanh và bền vững nhưng trong thực tế, năng lượng nguyên tử lại phải hứng chịu nhiều hiểu nhầm với thông tin bị thổi phồng hoặc bóp méo. Đây chính là thông điệp mà nhà vận động môi trường Mỹ Michael Shellenberger chia sẻ trong phần diễn thuyết kết thúc Diễn đàn ATOMEXPO tại Sochi, Nga, từ ngày 15-16/04/2019.
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