Microdosimetric techniques are a valuable tool for beam quality monitoring in BNCT, due to their capability to distinguish different contributions to the total dose and provide physics-based quantities related to biological effectiveness of this composite radiation field. To this aim, measurements are generally performed with gas detectors simulating a tissue-equivalent site size between 0.5 and 2 μm. This work presents instead measurements for site sizes up to 10 μm, performed in the thermal neutron field produced by the accelerator-based MUNES source available at INFN-LNL. An avalanche-confinement TEPC with boron doping in the cathode walls was used. Photon and neutron dose fractions were discriminated in the measured dose-weighted distributions based on their different lineal energy range. In the neutron component two separate peaks could be distinguished for site sizes of 5 μm and greater, the origin of which was tentatively related to contributions due to protons and alpha particles. These results allow to assess the impact of increasing site diameter on the measured relative dose contributions and provide valuable reference data for biological modelling and for comparison with solid-state microdosimeters.
This contribution describes the development of a set of numerical methods based on Machine Learning algorithms to generate an automated classification of experimental Thermoluminescence (TL) Glow Curves obtained routinely by Dosimetry Services. This classification will use experimental data historically recorded by Thermoluminescence Dosimeter (TLD) devices and will be based on the search for possible anomalies in the curves. The classifier tool will ease the labelling of experimental data and the detection of anomalies without previous supervision, implying an improvement in the control evaluations in Quality Guarantee Systems often implemented by Dosimetry Services. Furthermore, this study shows that each curve provides information about the status of each dosimeter, and can be used to perform unsupervised classifications of the measurements.
In this paper, Lu2.97Al5–xGaxO12:Ce0.03 (x = 0, 1, 2, 3) nanophosphors were synthesized using sol-gel method and calcined at 1100 °C for 3 h. The effect of Ga content on the structural, photoluminescence (PL), and notably thermoluminescence (TL) glow curve, dose response, repeatability and fading properties were investigated. X-ray diffraction (XRD) results indicated that all synthesized samples were crystallized in a pure garnet phase. The PL emission spectra exhibited a broad emission band corresponding to the 5 d → 4f (2F5/2, 2F7/2) transition of Ce3+ ions in the garnet lattice. Furthermore, a significant decrease in emission intensity was observed upon increasing Ga content. The TL characteristics of nanopowders irradiated with β-rays revealed a significant effect of Ga content on the peak position, shape and intensities of TL Glow curves, which can be explained by the reduction of the energy gap and the distribution of trap levels. The dose response linearity in the range of 0.125–100 Gy was examined for different Ga content, revealing a good linear behavior for x = 0 and 1 Ga. Additionally, samples prepared with x = 0, 1, and 2 Ga exhibited a high level of repeatability across a batch of 10 samples. Also, fading studies were performed for 128 h and revealed strong fading in samples synthesized with x = 0 and 1 Ga. These results suggest potential applications of Lu3Al5O12:Ce and Lu3Al4Ga1O12:Ce in ionizing radiation dosimetry.