n_TOF Collaboration(Balibrea-Correa, J. et al), Domingo-Pardo, C., Giubrone, G., Tain, J. L., & Tarifeño-Saldivia, A. (2020). Measurement of the alpha ratio and (n, gamma) cross section of U-235 from 0.2 to 200 eV at n_TOF. Phys. Rev. C, 102(4), 044615–18pp.
Abstract: We measured the neutron capture-to-fission cross-section ratio (alpha ratio) and the capture cross section of U-235 between 0.2 and 200 eV at the nTOF facility at CERN. The simultaneous measurement of neutron-induced capture and fission rates was performed by means of the nTOF BaF2 Total Absorption Calorimeter (TAC), used for detection of gamma rays, in combination with a set of micromegas detectors used as fission tagging detectors. The energy dependence of the capture cross section was obtained with help of the Li-6(n, t) standard reaction determining the n_TOF neutron fluence; the well-known integral of the U-235(n, f) cross section between 7.8 and 11 eV was then used for its absolute normalization. The alpha ratio, obtained with slightly higher statistical fluctuations, was determined directly, without need for any reference cross section. To perform the analysis of this measurement we developed a new methodology to correct the experimentally observed effect that the probabilities of detecting a fission reaction in the TAC and the micromegas detectors are not independent. The results of this work have been used in a new evaluation of U-235 performed within the scope of the Collaborative International Evaluated Library Organisation (CIELO) Project, and are consistent with the ENDF/B-VIII.0 and JEFF-3.3 capture cross sections below 4 eV and above 100 eV. However, the measured capture cross section is on average 10% larger between 4 and 100 eV.
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Balibrea-Correa, J., Lerendegui-Marco, J., Calvo, D., Caballero, L., Babiano, V., Ladarescu, I., et al. (2021). A first prototype of C6D6 total-energy detector with SiPM readout for neutron capture time-of-flight experiments. Nucl. Instrum. Methods Phys. Res. A, 985, 164709–8pp.
Abstract: Low efficiency total-energy detectors (TEDs) are one of the main tools for neutron capture cross section measurements utilizing the time-of-flight (TOF) technique. State-of-the-art TEDs are based on a C6D6 liquid-scintillation cell optically coupled to a fast photomultiplier tube. The large photomultiplier tube represents yet a significant contribution to the so-called neutron sensitivity background, which is one of the most conspicuous sources of uncertainty in this type of experiments. Here we report on the development of a first prototype of a TED based on a silicon-photomultiplier (SiPM) readout, thus resulting in a lightweight and much more compact detector. Apart from the envisaged improvement in neutron sensitivity, the new system uses low voltage (+28 V) and low current supply (-50 mA), which is more practical than the-kV supply required by conventional photomultipliers. One important difficulty hindering the earlier implementation of SiPM readout for this type of detector was the large capacitance for the output signal when all pixels of a SiPM array are summed together. The latter leads to long pulse rise and decay times, which are not suitable for time-of-flight experiments. In this work we demonstrate the feasibility of a Schottky-diode multiplexing readout approach, that allows one to preserve the excellent timing properties of SiPMs, hereby paving the way for their implementation in future neutron TOF experiments.
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Balibrea-Correa, J., Lerendegui-Marco, J., Babiano-Suarez, V., Caballero, L., Calvo, D., Ladarescu, I., et al. (2021). Machine Learning aided 3D-position reconstruction in large LaCl3 crystals. Nucl. Instrum. Methods Phys. Res. A, 1001, 165249–17pp.
Abstract: We investigate five different models to reconstruct the 3D gamma-ray hit coordinates in five large LaCl3(Ce) monolithic crystals optically coupled to pixelated silicon photomultipliers. These scintillators have a base surface of 50 x 50 mm(2) and five different thicknesses, from 10 mm to 30 mm. Four of these models are analytical prescriptions and one is based on a Convolutional Neural Network. Average resolutions close to 1-2 mm fwhm are obtained in the transverse crystal plane for crystal thicknesses between 10 mm and 20 mm using analytical models. For thicker crystals average resolutions of about 3-5 mm fwhm are obtained. Depth of interaction resolutions between 1 mm and 4 mm are achieved depending on the distance of the interaction point to the photosensor surface. We propose a Machine Learning algorithm to correct for linearity distortions and pin-cushion effects. The latter allows one to keep a large field of view of about 70%-80% of the crystal surface, regardless of crystal thickness. This work is aimed at optimizing the performance of the so-called Total Energy Detector with Compton imaging capability (i-TED) for time-of-flight neutron capture cross-section measurements.
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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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Lerendegui-Marco, J., Balibrea-Correa, J., Babiano-Suarez, V., Ladarescu, I., & Domingo-Pardo, C. (2022). Towards machine learning aided real-time range imaging in proton therapy. Sci Rep, 12(1), 2735–17pp.
Abstract: Compton imaging represents a promising technique for range verification in proton therapy treatments. In this work, we report on the advantageous aspects of the i-TED detector for proton-range monitoring, based on the results of the first Monte Carlo study of its applicability to this field. i-TED is an array of Compton cameras, that have been specifically designed for neutron-capture nuclear physics experiments, which are characterized by gamma-ray energies spanning up to 5-6 MeV, rather low gamma-ray emission yields and very intense neutron induced gamma-ray backgrounds. Our developments to cope with these three aspects are concomitant with those required in the field of hadron therapy, especially in terms of high efficiency for real-time monitoring, low sensitivity to neutron backgrounds and reliable performance at the high gamma-ray energies. We find that signal-to-background ratios can be appreciably improved with i-TED thanks to its light-weight design and the low neutron-capture cross sections of its LaCl3 crystals, when compared to other similar systems based on LYSO, CdZnTe or LaBr3. Its high time-resolution (CRT similar to 500 ps) represents an additional advantage for background suppression when operated in pulsed HT mode. Each i-TED Compton module features two detection planes of very large LaCl3 monolithic crystals, thereby achieving a high efficiency in coincidence of 0.2% for a point-like 1 MeV gamma-ray source at 5 cm distance. This leads to sufficient statistics for reliable image reconstruction with an array of four i-TED detectors assuming clinical intensities of 10(8) protons per treatment point. The use of a two-plane design instead of three-planes has been preferred owing to the higher attainable efficiency for double time-coincidences than for threefold events. The loss of full-energy events for high energy gamma-rays is compensated by means of machine-learning based algorithms, which allow one to enhance the signal-to-total ratio up to a factor of 2.
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