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Caballero, L., Albiol, F., Corbi Bellot, A., Domingo-Pardo, C., Leganes Nieto, J. L., Agramunt Ros, J., et al. (2018). Gamma-ray imaging system for real-time measurements in nuclear waste characterisation. J. Instrum., 13, P03016–23pp.
Abstract: Acompact, portable and large field-of-viewgamma camera that is able to identify, locate and quantify gamma-ray emitting radioisotopes in real-time has been developed. The device delivers spectroscopic and imaging capabilities that enable its use it in a variety of nuclear waste characterisation scenarios, such as radioactivity monitoring in nuclear power plants and more specifically for the decommissioning of nuclear facilities. The technical development of this apparatus and some examples of its application in field measurements are reported in this article. The performance of the presented gamma-camera is also benchmarked against other conventional techniques.
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Olleros, P., Caballero, L., Domingo-Pardo, C., Babiano, V., Ladarescu, I., Calvo, D., et al. (2018). On the performance of large monolithic LaCl3(Ce) crystals coupled to pixelated silicon photosensors. J. Instrum., 13, P03014–17pp.
Abstract: We investigate the performance of large area radiation detectors, with high energy-and spatial-resolution, intended for the development of a Total Energy Detector with gamma-ray imaging capability, so-called i-TED. This new development aims for an enhancement in detection sensitivity in time-of-flight neutron capture measurements, versus the commonly used C6D6 liquid scintillation total-energy detectors. In this work, we study in detail the impact of the readout photosensor on the energy response of large area (50 x 50 mm(2)) monolithic LaCl3(Ce) crystals, in particular when replacing a conventional mono-cathode photomultiplier tube by an 8 x 8 pixelated silicon photomultiplier. Using the largest commercially available monolithic SiPM array (25 cm(2)), with a pixel size of 6 x 6 mm(2), we have measured an average energy resolution of 3.92% FWHM at 662 keV for crystal thick-nesses of 10, 20 and 30 mm. The results are confronted with detailed Monte Carlo (MC) calculations, where optical processes and properties have been included for the reliable tracking of the scintillation photons. After the experimental validation of the MC model, we use our MC code to explore the impact of a smaller photosensor segmentation on the energy resolution. Our optical MC simulations predict only a marginal deterioration of the spectroscopic performance for pixels of 3 x 3 mm(2).
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Algora, A. et al, Jordan, D., Tain, J. L., Rubio, B., Agramunt, J., Perez-Cerdan, A. B., et al. (2011). Improvements on Decay Heat Summation Calculations by Means of Total Absorption Gamma-ray Spectroscopy Measurements. J. Korean Phys. Soc., 59(2), 1479–1482.
Abstract: The decay heat of fission products plays an important role in predictions of the heat released by nuclear fuel in reactors. In this contribution we present results of the analysis of the measurement of the beta decay of some refractory isotopes that were considered possible important contributors to the decay heat in reactors. The measurements presented here were performed at the IGISOL facility of the University of Jyvaskyla, Finland. In our measurements we have combined for the first time a Penning trap (JYFLTRAP), which was used as a high resolution isobaric separator, with a total absorption spectrometer. The results of the measurements as well as their consequences for decay heat summation calculations are discussed.
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Labiche, M. et al, Caballero, L., & Rubio, B. (2010). TIARA: A large solid angle silicon array for direct reaction studies with radioactive beams. Nucl. Instrum. Methods Phys. Res. A, 614(3), 439–448.
Abstract: A compact, quasi-4 pi position sensitive silicon array. TIARA, designed to study direct reactions induced by radioactive beams in inverse kinematics is described here. The Transfer and Inelastic All-angle Reaction Array (TIARA) consists of 8 resistive charge division detectors forming an octagonal barrel around the target and a set of double-sided silicon-strip annular detectors positioned at each end of the barrel. The detector was coupled to the gamma-ray array EXOGAM and the spectrometer VAMOS at the GANIL Laboratory to demonstrate the potential of such an apparatus with radioactive beams. The N-14(d,p)N-15 reaction, well known in direct kinematics, has been carried out in inverse kinematics for that purpose. The observation of the N-15 ground state and excited states at 7.16 and 7.86 MeV is presented here as well as the comparison of the measured proton angular distributions with DWBA calculations. Transferred l-values are in very good agreement with both theoretical calculations and previous experimental results obtained in direct kinematics.
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Babiano-Suarez, V. et al, Lerendegui-Marco, J., Balibrea-Correa, J., Caballero, L., Calvo, D., Ladarescu, I., et al. (2021). Imaging neutron capture cross sections: i-TED proof-of-concept and future prospects based on Machine-Learning techniques. Eur. Phys. J. A, 57(6), 197–17pp.
Abstract: i-TED is an innovative detection system which exploits Compton imaging techniques to achieve a superior signal-to-background ratio in (n, gamma) cross-section measurements using time-of-flight technique. This work presents the first experimental validation of the i-TED apparatus for high-resolution time-of-flight experiments and demonstrates for the first time the concept proposed for background rejection. To this aim, the Au-197(n, gamma) and Fe-56(n, gamma) reactions were studied at CERN n_TOF using an i-TED demonstrator based on three position-sensitive detectors. Two C6D6 detectors were also used to benchmark the performance of i-TED. The i-TED prototype built for this study shows a factor of similar to 3 higher detection sensitivity than state-of-the-art C6D6 detectors in the 10 keV neutron-energy region of astrophysical interest. This paper explores also the perspectives of further enhancement in performance attainable with the final i-TED array consisting of twenty position-sensitive detectors and newanalysis methodologies based on Machine-Learning techniques.
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