Archivio della ricerca - Fondazione Bruno Kessler
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Bi2Se3/n-Si Schottky Junctions for Near-Infrared Photodetectors
No full textBi2Se3 thin films with different thicknesses are deposited on prepatterned n-Si substrates by the vapor–solid deposition method, demonstrating photodetector performances in the visible and near-infrared range up to the telecommunication wavelength 1550 nm and showing response times as low as 126 ns. The current voltage characteristics measured in the temperature range 77–300 K indicate the formation of Schottky junctions at the interface between the two materials. The nature of the junctions is discussed considering the effect of disorder at the interface induced by the Bi2Se3 film granularity. The temperature dependence of the ideality factors and the Schottky barrier heights is consistent with a thermionic field effect mechanism governing the electron motion through the interface, which is responsible for the fast response of the photodetectors
A point-of-care test for miR-129–5p detection at sub-atto molar concentrations exploiting plasmonic pollen probes combined with complementary DNA
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Cryogenic characterization of FBK NUV-HD-Cryo 3T SiPM sensors for the DUNE photon detection system
No full textThe Deep Underground Neutrino Experiment (DUNE) is a long-baseline neutrino experiment based in the U.S.A. and composed of a Near Detector (ND) complex at Fermi National Laboratory (FNAL), and a Far Detector (FD) complex located at the Sanford Underground Research Facility (SURF) ∼ 1300 km distant. DUNE will study neutrino oscillations looking for unresolved issues of the Standard Model of particle physics (SM) such as CP violation in the leptonic sector, neutrino mass ordering and others, starting from the early 2030s. The FD, with a mass of ∼ 17 kt, that will exploit both ionization and scintillation signals to detect neutrino interactions with Argon. Scintillating photons in LAr will be detected by the photon detection system (PDS) based on light collectors coupled to Silicon Photomultipliers (SiPMs). During a test campaign, different laboratories of the collaboration performed an investigation of the best SiPM candidates that fulfill the DUNE FD requirements. We identified two models of SiPM, produced by Hamamatsu Photonics K.K. (HPK) and Fondazione Bruno Kessler (FBK), respectively. In this paper, we focus on the FBK selected model showing its main features. We will describe the characterization protocol, the results at both room and cryogenic temperatures and the photon detection efficiency measurements
Design of a micro-Raman spectroscopy chamber for operando studies on semiconductor gas sensors
No full textThis work outlines the design and validation of an ambient chamber specifically tailored for confocal micro-Raman spectroscopy investigations on semiconductor gas sensors under operando conditions. The system enables real-time analysis of gas–solid interactions providing a reproducible and versatile platform for the characterization of a wide range of gas-sensing devices. A comprehensive study was carried out, covering chamber design, 3D modeling, integration with a custom data acquisition system, residence time distribution analysis for fluid dynamics assessment, temperature and humidity monitoring. Finally, the system was validated using an indium oxide-based sensor exposed to ethanol. The proposed gas-sensing setup is designed to be easy to fabricate, operate, and maintain. It supports solid-state gas sensors with sub-millimeter active areas and can operate at temperatures up to 500 °C achieving high-resolution spectroscopic measurements. Furthermore, its modular architecture ensures seamless integration with various microscopy platforms, enhancing the quality and flexibility of spectral acquisition
A comparative benchmark study of LLM-based threat elicitation tools
No full textThreat modeling refers to the software design activity that involves the proactive identification, evaluation, and mitigation of specific potential threat scenarios. Recently, attention has been growing for the potential to automate the threat elicitation process using Large Language Models (llms), and different tools have emerged that are capable of generating threats based on system models and other descriptive system documentation. This paper presents the outcomes of an experimental evaluation study of llm-based threat elicitation tools, which we apply to two complex and contemporary application cases that involve biometric authentication. The comparative benchmark is based on a grounded approach to establish four distinct baselines which are representative of the results of human threat modelers, both novices and experts. In support of scale and reproducibility, the evaluation approach itself is maximally automated using sentence transformer models to perform threat mapping. Our study evaluates 56 distinct threat models generated by 6 llm-based threat elicitation tools. While the generated threats are somewhat similar to the threats documented by human threats modelers, relative performance is low. The evaluated llm-based threat elicitation tools prove to be particularly inefficient in eliciting the threats on the expert level. Furthermore, we show that performance differences between these tools can be attributed on a similar level to both the prompting approach (e.g., multi-shot, knowledge pre-prompting, role prompting) and the actual reasoning capabilities of the underlying llms being used
Behind the transduction mechanism of a nanostructured functional material for environmental CO2 monitoring
No full textThis work investigated an innovative CO2-sensitive nanostructured semiconductor material through a three-level approach, i.e., materials and electrical characterization, chemisorption with probe molecules analyses, and operando Diffuse Reflectance Infrared Fourier Transform (DRIFT) spectroscopy under thermoactivation. By integrating these advanced techniques, a complete scenario of the sensing mechanism can be obtained, paving the way for the development of highly sensitive and selective CO2 sensors. It emerged that doping with alkali metals, such as sodium, has proven to be an effective strategy to improve the performance of CO2 devices. This study presents a sustainable and fast synthesis of three samples with varying sodium content and characterization of each material to explore the role of sodium doping. Therefore, extensive materials characterization confirmed the nanostructured nature of the mesoporous Na-doped In2O3 materials as nanoparticles and the presence of intra-structural sodium. These material surfaces were found to possess different acid and basic sites ratio, which can be rationalized by the presence and the amount of sodium. From electrical characterization, a key feature of Na-doped In2O3 was the marginal influence of humidity, which enables such sensors to a wide range of possible real-world applications. Operando DRIFT spectroscopy clarifies which ones and under what conditions the carbonate species formed upon CO2 adsorption interact with the material as a function of the presence of acidic and basic sites, a crucial factor influencing the mechanism of transduction. This study uniquely captures the balance of active sites to motivate and explain the optimal sensing behaviour
