English

u-RANIA: a neutron detector based on \mu -RWELL technology

Instrumentation and Detectors 2020-08-18 v5

Abstract

In the framework of the ATTRACT-uRANIA project, funded by the European Community, we are developing an innovative neutron imaging detector based on micro-Resistive WELL (μ\mu -RWELL) technology. The μ\mu -RWELL, based on the resistive detector concept, ensuring an efficient spark quenching mechanism, is a highly reliable device. It is composed by two main elements: a readout-PCB and a cathode. The amplification stage for this device is embedded in the readout board through a resistive layer realized by means of an industrial process with DLC (Diamond-Like Carbon). A thin layer of B4_4C on the copper surface of the cathode allows the thermal neutrons detection through the release of 7^7Li and α\alpha particles in the active volume. This technology has been developed to be an efficient and convenient alternative to the 3^3He shortage. The goal of the project is to prove the feasibility of such a novel neutron detector by developing and testing small planar prototypes with readout boards suitably segmented with strip or pad read out, equipped with existing electronics or readout in current mode. Preliminary results from the test with different prototypes, showing a good agreement with the simulation, will be presented together with construction details of the prototypes and the future steps of the project.

Keywords

Cite

@article{arxiv.2005.06260,
  title  = {u-RANIA: a neutron detector based on \mu -RWELL technology},
  author = {I. Balossino and G. Bencivenni and P. Bielowka and G. Cibinetto and R. Farinelli and G. Felici and I. Garzia and M. Gatta and P. Giacomelli and M. Giovannetti and R. Hall Wilton and C. -C. Lai and L. Lavezzi and F. Messi and G. Mezzadri and G. Morello and M. Pinamonti and M. Poli Lener and L. Robinson and M. Scodeggio and P. -O. Svensson},
  journal= {arXiv preprint arXiv:2005.06260},
  year   = {2020}
}

Comments

Prepared for the INSTR20 Conference Proceeding for JINST

R2 v1 2026-06-23T15:30:45.075Z