In recent years, the use of techniques based on electromagnetic radiation as an investigative tool in the agri-food industry has grown considerably, and between them, the application of imaging and THz spectroscopy has gained significance in the field of food quality control. This study presents the development of an experimental setup operating in transmission mode within the frequency range of 18 to 40 GHz, which was specifically designed for assessing various quality parameters of hazelnuts. The THz measurements were conducted to distinguish between healthy and rotten hazelnut samples. Two different data analysis techniques were employed and compared: a traditional approach based on data matrix manipulation and curve fitting for parameter extrapolation, and the utilization of a Self-Organizing Map (SOM), for which we use a neural network commonly known as the Kohonen neural network, which is recognized for its efficacy in analyzing THz measurement data. The classification of hazelnuts based on their quality was performed using these techniques. The results obtained from the comparative analysis of coding efforts, analysis times, and outcomes shed light on the potential applications of each method. The findings demonstrate that THz spectroscopy is an effective technique for quality assessment in hazelnuts, and this research serves to clarify the suitability of each analysis technique.

In this paper, the study of a plasma diagnostic system based on the THz time domain spectroscopy technique is presented. Such a system could potentially probe a large part of the electromagnetic spectrum currently covered by several other diagnostics in a single measurement. This feature, keeping in mind the basic requirements for plasma diagnostics in nuclear fusion experiments, such as robustness and hard environment applicability, as well as durability and low maintenance, makes the diagnostic of great interest. A conceptual design of the THz-TDS diagnostic has been developed, starting from the well-established classical microwave and far infrared plasma diagnostics landscape. The physical constraints and required instrumental characteristics have been studied and are described in detail here, together with the solutions available for each type of plasma measurement. Specific experimental laboratory tests of the different experimental configurations have been carried out, evaluating the capacity and potential of the novel diagnostic, together with the instrumental constraint, within the diagnostic parameter space.

The study of materials for space exploration is one of the most interesting targets of international space agencies. An essential tool for realizing light junctions is epoxy adhesive (EA), which provides an elastic and robust material with a complex mesh of polymeric chains and crosslinks. In this work, a study of the structural and chemical modification of a commercial two-part flexible EA (3MTM Scotch-WeldTM EC-2216 B/A Gray), induced by 60Co gamma radiation, is presented. Combining different spectroscopic techniques, such as the spectroscopic Fourier transform infrared spectroscopy (FTIR), the THz time-domain spectroscopy (TDS), and the electron paramagnetic resonance (EPR), a characterization of the EA response in different regions of the electromagnetic spectrum is performed, providing valuable information about the structural and chemical properties of the polymers before and after irradiation. A simultaneous dissociation of polymeric chain and crosslinking formation is observed.The polymer is not subject to structural modification at an absorbed dose of 10 kGy, in which only transient free radicals are observed. Differently, between 100 and 500 kGy, a gradual chemical degradation of the samples is observed together with a broad and long-living EPR signal appearance. This study also provides a microscopic characterization of the material useful for the mechanism evaluation of system degradation.

An experimental setup operating in transmission mode in the frequency range between 18 and 40 GHz is described. This study shows how the system is able to distinguish healthy and rotten hazelnuts. In addition, a Self-Organizing Map (SOM) trained with the Kohonen algorithm was used to classify the hazelnuts according to their quality.

Since long time THz-TDS techniques have been seen as a good option for the measurements of plasma parameters [1]. This becomes a particularly interesting option for nuclear fusion experiments where Far Infrared and microwave diagnostics, in the frequency range 0.1-4000 THz, are one of the most important measurement tool [2] [3]. The application of THz-TDS techniques can potentially provide important plasma parameters, such as density, temperature and fluctuations, by using a multi-functional device with relatively small access requirements [4].

Wood is a hygroscopic material that is subject to phenomena of water exchange with the external environment. These exchanges can cause dimensional variations and cracks to appear on a macroscopic level. In recent years, the use of terahertz technologies in the field of diagnostics applied to cultural heritage has increased considerably. One of the most important characteristics of terahertz radiation is its sensitivity to water content; this polar liquid strongly absorbs and reflects this radiation. The subject of this study will be the detection of moisture in pine wood samples using a 97 GHz terahertz imaging system.