Use of CdZnTe detectors to analyze gamma emission of safeguards samples in the field

Czock, K.H.; Arlt, R.

doi:10.1016/s0168-9002(00)00861-5

Cited by 10 publications

(5 citation statements)

References 1 publication

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“…Owing to its large average atomic number, wide band gap, high resistivity, and good electron transport properties, Cadmium Zinc Telluride(CdZnTe) has become one of the most exploited materials for x-ray and gamma-ray radiation detection at room temperature, which has broad prospects in medicine, space science, airport, port security, nuclear waste monitoring and other applications of nuclear technology [1][2][3] .…”

Section: Introduction Introduction Introduction Introductionmentioning

confidence: 99%

Study on Cd vacancy in CdZnTe Crystal by Positron Annihilation Technology

Liu

Min

Liang

et al. 2013

J. Phys.: Conf. Ser.

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Section: Introduction Introduction Introduction Introductionmentioning

confidence: 99%

Study on Cd vacancy in CdZnTe Crystal by Positron Annihilation Technology

Liu

Min

Liang

et al. 2013

J. Phys.: Conf. Ser.

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“…Room temperature medium resolution detectors of CdZnTe (CZT) type are becoming attractive for many radiation measurement applications where compact size, absence of cryogenics and good energy resolution makes them advantageous over traditional spectrometers based on HPGe or NaI devices. Indeed, CZT detectors were proposed as promising candidates for homeland security, safeguards, medical and industrial applications [1][2][3][4][5][6]. Energy resolution of CZT detectors is between that of HPGe and NaI detectors, yielding spectroscopic performance with a more detailed spectral information on the measured X-and gamma-ray signatures, compared to traditional room temperature devices.…”

Section: Introductionmentioning

confidence: 99%

A novel asymmetrical peak broadening feature for a CdZnTe detector response function modeling using PHITS particle and heavy ion transport simulation code

Meleshenkovskii

Ogawa

Pauly

et al. 2020

Nuclear Instruments and Methods in Physics Research Section B:

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In this paper we present the results of a detector response function modeling using a new version of PHITS Particle and Heavy Ion Transport Code with an advanced feature for asymmetrical peak broadening. Tests are performed on a room temperature medium resolution 500 mm 3 CdZnTe detector of a quasi-hemispherical design with validation on a set of point source gamma-ray spectra with a range of energies from 59 keV up to 1332 keV. Performance assessment is conducted with respect to built-in spectra broadening capabilities using as default Gaussian as well as an asymmetrical peak shape models. Results of our study indicate that up to 200 keV energy range where peak asymmetry is not severe a default Gaussian peak shape broadening can be used. Beyond 200 keV the degree of CZT photopeak asymmetry becomes significant and requires an asymmetrical peak shape broadening. This asymmetry affects the low-energy side of the photopeaks and has a non-linear behavior with energy. We find that with a built-in feature of a tailed peak shape model introduced in the new version of PHITS code (ver. 3.10) asymmetrical peak shapes of CZT detectors can be approximated. The analysis routines and mathematical formalism are described in detail and results are presented.

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“…The field of radiation detection is itself a very rich subject, in which in the past decades there has been progress with room temperature medium resolution detectors, such as CdZnTe (CZT) and LaBr 3 (Ce) [6,7]. Compared to traditional low-resolution detectors, such as NaI, their attractive features open new possibilities for X-and gamma-ray assay of uranium and plutonium bearing materials, portable systems, for medical applications and imaging [8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Making isotopic composition artificially intelligent: Conceptual design and performance assessment of pattern recognition algorithms for uranium enrichment determination tasks using CZT and LaBr3(Ce) detectors

2019

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There is currently a huge interest in the use of artificial intelligence (AI) technologies for various data analysis applications. Among these applications are radiation detection and spectra analysis tasks aiming at qualitative and quantitative information extraction on the assaying radioisotopes. AI tools are foreseen as promising techniques to deal with complex spectra analysis cases, where the traditional statistical tools are subject to deficiencies, due to high degree of noise, peak overlapping and statistical uncertainties because of the room temperature operation of detectors such as CdZnTe and LaBr 3(Ce). However, over the years there has been no comprehensive assessment of possible conceptual designs of such AI-based algorithms for spectra analysis purposes applied to uranium enrichment determination tasks. This paper analyzes different AI-based methodologies for the qualitative and quantitative analyses of uranium spectra and presents the AI-based Cluster Analysis via Machine Intelligence and Learning Algorithms (CAMILA) code for uranium enrichment determination. The performance assessment of multivariate and pattern recognition methodologies limits and possibilities is conducted in view of different physical conditions of the measurement system, such as the degree of attenuation and sample-to-detector distance, as well as impact of the neural network (NN) design on the algorithm performance. Tests are conducted on uranium spectra of CBNM certified standards with enrichment degrees from 0.31% up to 4.46% of 235 U atomic abundance measured with different statistical quality, as well as on simulated uranium spectra with a broad range of enrichment degrees. Implemented unfolding and analysis routines of the algorithms are described in detail and results are presented.

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Use of CdZnTe detectors to analyze gamma emission of safeguards samples in the field

Cited by 10 publications

References 1 publication

Study on Cd vacancy in CdZnTe Crystal by Positron Annihilation Technology

Study on Cd vacancy in CdZnTe Crystal by Positron Annihilation Technology

A novel asymmetrical peak broadening feature for a CdZnTe detector response function modeling using PHITS particle and heavy ion transport simulation code

Making isotopic composition artificially intelligent: Conceptual design and performance assessment of pattern recognition algorithms for uranium enrichment determination tasks using CZT and LaBr3(Ce) detectors

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