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M. Taani

Publications and source records attributed to M. Taani.

4 recordsLinked to original sources

Water-based Quantum Dots Liquid Scintillator for Particle Physics

Liquid scintillators are typically composed from organic compounds dissolved in organic solvents. However, usage of such material is often restricted due to fire safety and environmental reasons. Because of this, R\&D of water-based liquid scintillators is of extreme relevance; yet, no such scintillators have been made commercially available as yet. Here, we investigate an alternative, water-based quantum dots liquid scintillator. Pre-determined and controllable optical properties of the quantum dots, as well as the existence of large libraries of established protocols for their dispersion in aqueous solutions, make them an attractive option for nuclear and particle physics applications. We characterize the optical properties of water-based quantum dots liquid scintillator and find that most of its optical properties are preserved upon quantum dots' phase transfer into water, through the addition of an oleic acid hydrophilic layer. Using the developed scintillator, the time and charge responses from atmospheric muons are measured, highlighting the practical viability of water-based quantum dots liquid scintillators for nuclear and particle physics, special interest on neutrino physics.

physics.ins-det

Application of machine learning techniques to lepton energy reconstruction in water Cherenkov detectors

The application of machine learning techniques to the reconstruction of lepton energies in water Cherenkov detectors is discussed and illustrated for TITUS, a proposed intermediate detector for the Hyper-Kamiokande experiment. It is found that applying these techniques leads to an improvement of more than 50% in the energy resolution for all lepton energies compared to an approach based upon lookup tables. Machine learning techniques can be easily applied to different detector configurations and the results are comparable to likelihood-function based techniques that are currently used.

physics.ins-det

Sea state monitoring using coastal GNSS-R

We report on a coastal experiment to study GPS L1 reflections. The campaign was carried out at the Barcelona Port breaker and dedicated to the development of sea-state retrieval algorithms. An experimental system built for this purpose collected and processed GPS data to automatically generate a times series of the interferometric complex field (ICF). The ICF was analyzed off line and compared to a simple developed model that relates ICF coherence time to the ratio of significant wave height (SWH) and mean wave period (MWP). The analysis using this model showed good consistency between the ICF coherence time and nearby oceanographic buoy data. Based on this result, preliminary conclusions are drawn on the potential of coastal GNSS-R for sea state monitoring using semi-empirical modeling to relate GNSS-R ICF coherence time to SWH.

physics.ao-ph

GNSS-R: Operational Applications

This paper provides an overview of operational applications of GNSS-R, and describes Oceanpal, an inexpensive, all-weather, passive instrument for remote sensing of the ocean and other water surfaces. This instrument is based on the use of reflected signals emitted from GNSS, and it holds great potential for future applications thanks to the growing, long term GNSS infrastructure. The instrument exploits the fact that, at any given moment, several GNSS emitters are simultaneously in view, providing separated multiple scattering points with different geometries. Reflected signals are affected by surface roughness and motion (i.e., sea state, orbital motion, and currents), mean surface height and dielectric properties (i.e., salinity and pollution). Oceanpal is envisioned as an accurate, "dry" tide gauge and surface roughness monitoring system, and as an important element of a future distributed ocean remote sensing network concept. We also report some results from the Starlab Coastpal campaign, focusing on ground GNSS-R applications.

physics.ao-ph