Academic literature on the topic 'Microbulk Micromegas detectors'

MicroMegas detectors are versatile gaseous detectors which are used for ionizing particle detection. A MicroMegas detector consists of two adjacent gas-filled volumes. One volume acts as a drift region with an electric field operating in the ionization chamber regime, the second volume is the amplification region acting as a parallel-plate avalanche counter. The use of the microbulk technique allows the production of thin, radiation resistant, and low-mass detector with a highly variable gain. Such MicroMegas detectors have been developed and used in combination with neutron time-of-flight measurements for in-beam neutron-flux monitoring, fission and light-charged particle reaction cross section measurements, and for neutron-beam imaging. An overview of MicroMegas detectors for neutron detection and neutron reaction cross section measurements and related results and developments will be presented.

Due to the so-called 3He shortage crisis, many detection techniques for thermal neutrons are currently based on alternative converters. There are several possible ways of increasing the detection efficiency for thermal neutrons using the solid neutron-to-charge converters 10B or 10B4C. Here, we present an investigation of the Micromegas technology. The micro-pattern gaseous detector Micromegas was developed in the past years at Saclay and is now used in a wide variety of neutron experiments due to its combination of high accuracy, high rate capability, excellent timing properties, and robustness. A large high-efficiency Micromegas-based neutron detector is proposed for thermal neutron detection, containing several layers of 10B4C coatings that are mounted inside the gas volume. The principle and the fabrication of a single detector unit prototype with overall dimension of ~15 × 15 cm2 and its possibility to modify the number of 10B4C neutron converter layers are described. We also report results from measurements that are verified by simulations, demonstrating that typically five 10B4C layers of 1–2 μm thickness would lead to a detection efficiency of 20% for thermal neutrons and a spatial resolution of sub-mm. The high potential of this novel technique is given by the design being easily adapted to large sizes by constructing a mosaic of several such detector units, resulting in a large area coverage and high detection efficiencies. An alternative way of achieving this is to use a multi-layered Micromegas that is equipped with two-side 10B4C-coated gas electron multiplier (GEM)-type meshes, resulting in a robust and large surface detector. Another innovative and very promising concept for cost-effective, high-efficiency, large-scale neutron detectors is by stacking 10B4C-coated microbulk Micromegas. A prototype was designed and built, and the tests so far look very encouraging.

Abstract The International AXion Observatory (IAXO) is a large scale axion helioscope that will look for axions and axion-like particles produced in the Sun with unprecedented sensitivity. BabyIAXO is an intermediate experimental stage that will be hosted at DESY (Germany) and that will test all IAXO subsystems serving as a prototype for IAXO but at the same time as a fully-fledged helioscope with potential for discovery. One of the crucial components of the project is the ultra-low background X-ray detectors that will image the X-ray photons produced by axion conversion in the experiment. The baseline detection technology for this purpose are Micromegas (Microbulk) detectors. We will show the quest and the strategy to attain the very challenging levels of background targeted for BabyIAXO that need a multi-approach strategy coming from ground measurements, screening campaigns of components of the detector, underground measurements, background models, in-situ background measurements as well as powerful rejection algorithms. First results from the commissioning of the BabyIAXO prototype will be shown.

The fission cross-section of 234U was measured at incident neutron energies between 300 and 500 keV and 4 and 5 MeV with a setup based on “microbulk” MicroMegas detectors. The standard 235,238U fission cross-sections were used as reference. The neutron beams were produced via the 7Li(p,n) and the 2H(d,n) reactions at the neutron beam facility of the 5.5 MeV Tandem accelerator laboratory at NCSR “Demokritos”. The mass of the actinide content of the targets used and of their impurities was quantitatively determined via α – spectroscopy. The developed methodology and preliminary results are presented.

A new MicroMegas detector, based on the innovative Microbulk technology, especially developed within the context of the n TOF collaboration, was used for the first time for fission cross section measurements with monoenergetic neutron beams at the Institute of Nuclear and Particle Physics of the NCSR “Demokritos”. The detector assembly was successfully used in the case of the measurement of the 237Np(n,f) cross section while the first results on the performance of the detector as far as the gain and resolution function are concerned are reported.

Abstract The TREX-DM detector, a low background chamber with microbulk Micromegas readout, was commissioned in the Canfranc Underground Laboratory (LSC) in 2018. Since then, data taking campaigns have been carried out with argon and neon mixtures, at different pressures from 1 to 4 bar. By achieving a low energy threshold of 1 keV ee and a background level of 80 counts keV-1 kg-1 day-1 in the region from 1 to 7 keV ee , the experiment demonstrates its potential to search for low-mass WIMPs. Two of the most important challenges currently faced are the reduction of both, background level and energy threshold. With respect to the energy threshold, recently a new readout plane is being developed, based on the combination of Micromegas and GEM technologies, aiming to have a pre-amplification stage that would permit very low energy thresholds, close to the single-electron ionization energy. With respect to the background reduction, apart from studies to identify and minimize contamination population, a high sensitivity alpha detector is being developed in order to allow a proper material selection for the TREX-DM detector components. Both challenges, together with the optimization of the gas mixture used as target for the WIMP detection, will take TREX-DM to explore regions of WIMP's mass below 1 GeV c -2.

La recherche de la désintégration double bêta sans neutrino (0νββ) est cruciale pour faire progresser notre compréhension de la physique et explorer la physique au-delà du modèle standard. Cependant, cette recherche est incroyablement difficile en raison de l'extrême rareté de la désintégration, qui nécessite une interprétation approfondie et une dépendance aux contraintes expérimentales et aux modèles nucléaires théoriques. L'expérience PandaX-III est dédiée à la recherche de 0νββ dans 136-Xe. Il s'agit d'une chambre de projection temporelle (TPC) gazeuse à haute pression équipée de détecteurs Micromegas. Ce choix a été fait pour maximiser la capacité de détection des traces de particules et minimiser les fluctuations statistiques dans la résolution énergétique. L'un des principaux défis de la recherche d'événements 0νββ est la discrimination entre le signal et les événements de bruit de fond, qui contaminent la région d'intérêt (ROI). Le système de lecture par pistes des détecteurs Micromegas (une combinaison de 52 détecteurs forme un plan de lecture) permet la reconstruction 2D précise des trajectoires d'ionisation avec les informations de charge et de temps. Cela permet d'étudier l'énergie et la topologie des trajectoires d'électrons et, en conséquence, de distinguer le signal du bruit de fond. Pour supprimer la scintillation et ne se baser que sur le signal d'ionisation, le 136-Xe gazeux enrichi à 90% est mélangé avec 1% de triméthylamine (TMA) qui joue le rôle de "quencher". La résolution énergétique actuelle de l'expérience PandaX-III est de 3% pour l'énergie de 2457 keV de la désintégration de 136-Xe 0νββ, et devrait être améliorée à 1%. Cependant, plusieurs facteurs peuvent dégrader la résolution en énergie, tels que la présence de canaux morts, les inhomogénéités de gain dans les détecteurs Micromegas ou l'attachement des électrons dans la TPC. Ce travail de doctorat présente une étude de l'impact des canaux manquants sur les reconstructions d'énergie et de topologie dans l'expérience PandaX-III. Les résultats de la détermination de la charge du blob n'offrent pas la possibilité souhaitée de reconstituer la partie de son énergie qui aurait été perdue en raison des canaux manquants dans XZ à partir des projections YZ des traces d'événements reconstruites et vice versa. Cependant, l'étude a montré qu'il est possible d'utiliser des algorithmes d'apprentissage automatique pour atténuer l'impact des canaux manquants sur ls reconstruction de l'énergie et de la topologie. Un modèle de réseau neuronal convolutif (CNN) a été développé pour prédire l'énergie réelle des électrons à partir des données simulées collectées par les Micromegas avec des canaux manquants. Les résultats finaux montrent que le modèle CNN prédit l'énergie réelle des événements enregistrés par les Micromegas avec des canaux manquants avec une grande efficacité. Nous observons une amélioration de l'efficacité de détection du signal de Monte Carlo dans la ROI, qui passe de 69% à 89% après l'application du modèle CNN, par rapport à l'approche directe consistant à additionner les amplitudes des signaux provenant des Micromegas dont les canaux sont manquants. Un autre modèle CNN a également été utilisé pour classer les événements à deux électrons des événements à un seul électron dans les données de Monte Carlo affectées par des canaux manquants. Le modèle est capable de rejeter 99% des événements de bruit de fond tout en conservant une efficacité de 26% pour les signaux 0νββ dans la ROI. Les résultats de ce travail sont prometteurs et ouvrent la voie à d'autres études visant à améliorer la résolution en énergie et le rejet du bruit de fond dans l'expérience PandaX-III
The search for neutrinoless double-beta decay (0νββ) is crucial for advancing our understanding of physics and exploring physics beyond the Standard Model. However, this pursuit is incredibly challenging due to the decay's extreme rarity, requiring profound interpretation and reliance on experimental constraints and theoretical nuclear models. The PandaX-III experiment is dedicated to the search for 0νββ in 136-Xe. It is a high-pressure gaseous Time Projection Chamber (TPC) with Micromegas detectors. This design choice is made to maximize the particle track detection and discrimination 0νββ signal vs. gamma background capabilities. One of the main challenges of the 0νββ search is the discrimination between the signal and background events, which contaminate the region of interest (ROI). The strip readout system of the Micromegas detectors (a combination of 52 of them form a readout plane) allows for the precise 2D reconstruction of the ionization tracks together with the charge and time information. This allows for studying the electron tracks' energy and topology and ultimately discriminating the signal from the background. To suppress the scintillation light and rely only on the ionization signal, a 90% enriched 136-Xe is mixed with a 1% trimethylamine (TMA) quencher. The current energy resolution of the PandaX-III experiment is 3% for the 2457 keV energy of the 136-Xe 0νββ decay, envisioned to be improved to 1%. However, several factors can degrade the energy resolution, such as the presence of dead channels, gain inhomogeneities in the Micromegas detectors, or electron attachment in the TPC. This Ph.D work presents a study on the impact of missing channels on the energy and topology reconstructions in the PandaX-III experiment. The results of the Blob charge determination do not provide the desired possibility of reconstituting the part of the blob energy that would have been lost due to missing channels in XZ from YZ projections of reconstructed event tracks and vice versa. However, the study gave insight into employing machine learning (ML) algorithms to mitigate the impact of missing channels on energy and topology reconstructions. A Convolutional Neural Network (CNN) model was developed to predict the true energy of the electrons from the simulated data collected by the Micromegas with missing channels. The final results show that the CNN model predicts the true energy of the events recorded by the Micromegas with missing channels with a good energy resolution. We observe an improvement in the detection efficiency of the Monte Carlo 0νββ signal in the ROI from 69% to 89% after applying the CNN model, in comparison to the direct approach of directly summing amplitudes of the signals from the Micromegas with missing channels. Another CNN model was also used to classify the two-electron events from the single-electron events in the Monte Carlo data affected by missing channels. The model is capable of rejecting 99% of the background events while maintaining a 26% efficiency for the 0νββ signal in the ROI. The results of this work are promising and pave the way for further studies to improve the energy resolution and background rejection in the PandaX-III experiment