Calibration of HPGe detectors using certified reference materials of natural origin

Xhixha, Gerti; Albéri, Matteo; Baldoncini, Marica; Bode, Kozeta; Bylyku, Elida; Cfarku, Florinda; Callegari, Ivan; Hasani, Fadil; Landsberger, Sheldon; Mantovani, Fabio; Rodríguez, Eva; Shala, Ferat; Strati, Virginia; Kaçeli, M. Xhixha

doi:10.1007/s10967-015-4360-6

Cited by 23 publications

(11 citation statements)

References 23 publications

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“…The radioactive content of the collected samples was measured at the Department of Physics and Earth Sciences of the University of Ferrara, with a High Pure Germanium detector (HPGe) called MCA_Rad. Analytical details are given in Xhixha et al (). The overall relative uncertainties on the K, eU, and eTh (i.e., U and Th assumed in secular equilibrium) are of the order of 10%.…”

Section: Methodsmentioning

confidence: 99%

“…Every sample was collected from fresh outcrops, representative of the geological formation, and placed in a polyethylene bag (Figure a). Later each sample was crushed, sealed in a polycarbonate container (Figure b) and left undisturbed for at least 5 weeks with the objective of establishing radioactive equilibrium between 226 Ra and 222 Rn (see Figure of Xhixha et al, ).…”

Section: Sampling Surveymentioning

confidence: 99%

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Perceiving the Crust in 3‐D: A Model Integrating Geological, Geochemical, and Geophysical Data

Strati

Wipperfurth

Baldoncini

et al. 2017

Geochem Geophys Geosyst

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Regional characterization of the continental crust has classically been performed through either geologic mapping, geochemical sampling, or geophysical surveys. Rarely are these techniques fully integrated, due to limits of data coverage, quality, and/or incompatible data sets. We combine geologic observations, geochemical sampling, and geophysical surveys to create a coherent 3‐D geologic model of a 50 × 50 km upper crustal region surrounding the SNOLAB underground physics laboratory in Canada, which includes the Southern Province, the Superior Province, the Sudbury Structure, and the Grenville Front Tectonic Zone. Nine representative aggregate units of exposed lithologies are geologically characterized, geophysically constrained, and probed with 109 rock samples supported by compiled geochemical databases. A detailed study of the lognormal distributions of U and Th abundances and of their correlation permits a bivariate analysis for a robust treatment of the uncertainties. A downloadable 3‐D numerical model of U and Th distribution defines an average heat production of 1.5−0.7+1.4 µW/m3, and predicts a contribution of 7.7−3.0+7.7 TNU (a Terrestrial Neutrino Unit is one geoneutrino event per 1032 target protons per year) out of a crustal geoneutrino signal of 31.1−4.5+8.0 TNU. The relatively high local crust geoneutrino signal together with its large variability strongly restrict the SNO+ capability of experimentally discriminating among BSE compositional models of the mantle. Future work to constrain the crustal heat production and the geoneutrino signal at SNO+ will be inefficient without more detailed geophysical characterization of the 3‐D structure of the heterogeneous Huronian Supergroup, which contributes the largest uncertainty to the calculation.

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Section: Methodsmentioning

confidence: 99%

Section: Sampling Surveymentioning

confidence: 99%

Perceiving the Crust in 3‐D: A Model Integrating Geological, Geochemical, and Geophysical Data

Strati

Wipperfurth

Baldoncini

et al. 2017

Geochem Geophys Geosyst

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“…The MCA-Rad system is shielded with a 10 cm thickness of copper and 10 cm thickness of lead so reducing the laboratory background by approximately two orders of magnitude. The absolute peak energy efficiency of the MCA-Rad system is calibrated using certified reference materials (RGK_1, RGU_1 and RGTh_1) traceable by the International Atomic Energy Agency (IAEA) (Xhixha et al, 2015). The total uncertainty for the absolute peak energy efficiency is estimated to be less than 5%.…”

Section: Methodsmentioning

confidence: 99%

Uranium distribution in the Variscan Basement of Northeastern Sardinia

Xhixha¹,

Albéri

Baldoncini

et al. 2015

Journal of Maps

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We present a detailed map of uranium distribution and its uncertainties in the Variscan Basement of Northeastern Sardinia (VBNS) at a scale of 1:100,000. An area of 2100 km 2 was investigated by means of 535 data points obtained from laboratory and in situ gamma-ray spectrometry measurements. These data volume corresponds to the highest sampling density of the European Variscides, aimed at studying the genetic processes of the upper crust potentially triggered by an enrichment of radiogenic heat-producing elements. For the first time, the Kriging with Variance of Measurement Error method was used to assign weights to the input data which are based on the degree of confidence associated with the measurements obtained using different gamma-ray spectrometry techniques. A detailed tuning of the model parameters for the adopted Experimental Semi-Variogram led to the identification of a maximum distance of spatial variability coherent to the observed tendency of the experimental data. We demonstrate that the obtained uranium distribution in the VBNS, characterized by several calc-alkaline plutons emplaced within migmatitic massifs and amphibolite-facies metamorphic rocks, is an excellent benchmark for the study of 'hot' collisional chains. The uranium map of VBNS, and in particular the Arzachena minor pluton, confirms the emplacement model based on the recognition of the different petrological associations characterizing the Variscan magmatic processes in the Late Paleozoic. Furthermore, the presented model of the uranium content of the geological bedrock is a potential baseline for future mapping of radon-prone areas.ARTICLE HISTORY

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“…These are the corresponding to the gamma lines of 242.0, 609.3, 1120.3 and 1238.1 keV emitted by 238 U progeny and 338.3, 583.2, 727.3, 860.0 and 911.0 keV emitted by 232 Th progeny. In such cases, the CSCF have been determined using the equations proposed by Xhixha et al [35], except in the emission of 727.3 keV, for which the corresponding equation proposed by Tomarchio and Rizzo [36] has been used. In both works, the correction factors are calculated as function of the FEPEs and total efficiencies for the energies corresponding to the X-ray and -ray emissions which are likely to coincide with the main gamma emission, causing the coincidence-summing effect.…”

Section: Characmentioning

confidence: 99%

Automatic modeling using PENELOPE of two HPGe detectors used for measurement of environmental samples byγ-spectrometry from a few sets of experimental efficiencies

Guerra

Rubiano

Winter

et al. 2018

Nuclear Instruments and Methods in Physics Research Section A:

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a b s t r a c tThe aim of this paper is to characterize two HPGe gamma-ray detectors used in two different laboratories for environmental radioactivity measurements, so as to perform efficiency calibrations by means of Monte Carlo Simulation. To achieve such an aim, methodologies developed in previous papers have been applied, based on the automatic optimization of the model of detector, so that the differences between computational and reference FEPEs are minimized. In this work, such reference FEPEs have been obtained experimentally from several measurements of the IAEA RGU-1 reference material for specific source-detector arrangements. The models of both detectors built through these methodologies have been validated by comparing with experimental results for several reference materials and different measurement geometries, showing deviations below 10% in most cases. (J.G. Guerra). work [16,17], in which automatic computational methodologies for the characterization of HPGe detectors have been developed.In the first paper [16], a simple methodology of characterization is proposed, consisting in an implementation of a mono-objective optimization evolutionary algorithm, called Differential Evolution or DE [18], together with the Monte Carlo Simulation code PENE-LOPE [19], so that a computational model of the detector would be built automatically, with the only requirements of an accurate set of reference FEPEs for a specific sample-detector arrangement and material of the sample, but restricted to those beakers with a diameter lower than the crystal diameter of the detector. In the second [17], the methodology proposed in the first work was upgraded, eliminating such restriction by both improving the detector model and implementing a multi-objective Differential Evolution algorithm or DEMO [20] instead of its monoobjective precursor DE. In both cases, the methodologies proved to obtain successfully a detector model which generated FEPEs equivalent to the ones taken as reference, which were calculated, for a given

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Calibration of HPGe detectors using certified reference materials of natural origin

Cited by 23 publications

References 23 publications

Perceiving the Crust in 3‐D: A Model Integrating Geological, Geochemical, and Geophysical Data

Perceiving the Crust in 3‐D: A Model Integrating Geological, Geochemical, and Geophysical Data

Uranium distribution in the Variscan Basement of Northeastern Sardinia

Automatic modeling using PENELOPE of two HPGe detectors used for measurement of environmental samples byγ-spectrometry from a few sets of experimental efficiencies

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