Development of a Thin, Double-Sided Alpha/Beta Detector for Surface-Contamination Measurement

Ifergan, Y.; Dadon, S.; Ocherashvili, A.; Israelashvili, I.; Yehuda-Zada, Y.; Smadja, D.; Carmel, L.; Knafo, Yaron; Ginzburg, Dimitry; Osovizky, A.; Atias, R.; Kadmon, Y.; Cohen, Yehuda; Mazor, T.

doi:10.1109/tns.2016.2514269

Cited by 10 publications

(6 citation statements)

References 4 publications

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“…High-Z (atomic number) elements are suitable for X/γ-ray absorption, whereas light elements are better used as β-ray scintillators [42,43]. Various nuclides are used for generating β-rays such as 3.…”

Section: High-energy Radiation Sources (α- β- γ- and X-rays) And Thei...mentioning

confidence: 99%

Perovskite: Scintillators, direct detectors, and X-ray imagers

et al. 2022

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Section: High-energy Radiation Sources (α- β- γ- and X-rays) And Thei...mentioning

confidence: 99%

Perovskite: Scintillators, direct detectors, and X-ray imagers

et al. 2022

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“…The data set used in this study comprises recordings of four distinct radiation isotopes: 60 Co, 57 Co, 137 Cs, and 241 Am. Each radiation isotope was recorded for 60 seconds using a directional detector consisting of seven cylindrical detectors made of NaI(Tl) scintillators [17]. The detector arrangement included one central detector positioned higher than the surrounding six detectors, arranged in a non-symmetrical configuration.…”

Section: A Data-setmentioning

confidence: 99%

Radioactive Direction of Arrival Estimation Using Neural Networks Approach

Salomon,

Vax,

Osowizky

et al. 2023

EPJ Web Conf.

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In this paper, we present a comprehensive investigation into improving Direction of Arrival (DOA) estimation for gamma-emitting isotopes using deep neural networks. The direction of arrival estimation is most valuable for Home Land Security (HLS) applications or increased safety in Decontamination and Decommissioning (D&D). Traditional methods, such as beamforming (BF), have limitations in accuracy and sensitivity to noise and background variations. In recent years, data-driven approaches utilizing deep neural networks, including Convolutional Neural Network (CNN) and Gated Recurrent Unit (GRU) models, have shown promise in enhancing DOA estimation. By considering the full energy spectrum and augmenting recorded data, our neural network models outperform traditional BF methods and exhibit greater resilience in diverse background scenarios. The 2-layer CNN model, in particular, achieves up to 40% improvement in estimation accuracy. Our research provides a reliable and data-driven approach for precise DOA estimation with potential applications in nuclear security and safety in D&D.

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“…In 2017 [5], our group introduced a concept of raising the central detector resembling a sun-dial (Fig. 1b).…”

Section: A Previous Work Based On Mutual-shieldingmentioning

confidence: 99%

“…Using a gradient descent of a loss function combining the sensitivity and accuracy, we improved the configuration from angular MSE of 3.73° to 2.84° and ~6% in the sensitivity. [1]; (b) added elevation capability for half a sphere (2π) using the 'sun-dial' array [5]; with whole 4π directionality using 2x4 cuboid scintillators array coupled to SiPMs [6]; (c) prototype of 90 small cubic scintillators randomly placed [8] for high accuracy.…”

Section: A Previous Work Based On Mutual-shieldingmentioning

confidence: 99%

Methodical Optimization of Mutual-Shielding Directional Gamma Detector

Eran,

Nadav,

Yossi

et al. 2023

EPJ Web Conf.

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Mutual-Shielding Directional Gamma Detector excels at sensitivity and can achieve good angular accuracy and a large field of view. In this paper, we present, in detail, a method to optimize a mutual shielding directional detector array regarding the scintillators positioning for a given number and size of detection units. The optimization goals are improvement of accuracy and sensitivity. The optimization uses two types of fast, non-Monte-Carlo simulations since the simulation needs to generate measurements from all directions for each array formation tested. Both these simulations are explained and demonstrated. The presented method uses the ambiguity function to assess the accuracy and identify directions that may generate errors due to similar responses from other directions. Then, addressing these problematic directions can be fixed by changing the scintillators’ positions or adding a partial shield to change the response at one of the similar directions.

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Development of a Thin, Double-Sided Alpha/Beta Detector for Surface-Contamination Measurement

Cited by 10 publications

References 4 publications

Perovskite: Scintillators, direct detectors, and X-ray imagers

Perovskite: Scintillators, direct detectors, and X-ray imagers

Radioactive Direction of Arrival Estimation Using Neural Networks Approach

Methodical Optimization of Mutual-Shielding Directional Gamma Detector

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