@Article{Babiano-Suarez_etal2021,
author="Babiano-Suarez, V. et al
and Lerendegui-Marco, J.
and Balibrea-Correa, J.
and Caballero, L.
and Calvo, D.
and Ladarescu, I.
and Real, D.
and Domingo-Pardo, C.",
title="Imaging neutron capture cross sections: i-TED proof-of-concept and future prospects based on Machine-Learning techniques",
journal="European Physical Journal A",
year="2021",
volume="57",
number="6",
pages="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.",
optnote="WOS:000662881100001",
optnote="exported from refbase (https://references.ific.uv.es/refbase/show.php?record=4875), last updated on Sat, 10 Jul 2021 12:42:34 +0000",
issn="1434-6001",
doi="10.1140/epja/s10050-021-00507-7",
opturl="https://arxiv.org/abs/2012.10374",
opturl="https://doi.org/10.1140/epja/s10050-021-00507-7"
}