Technologies

The dramatic global health emergency due to the SARS-CoV-2 pandemic requires new diagnostic devices capable of identifying the presence of virus particles in patient biological samples. In this direction, the development of an innovative low-cost test, which provides the result within a few minutes, which is reproducible and which can reveal the direct presence of even a few viral particles, would be of fundamental importance for the monitoring and containment of the pandemic.

The compact-GC platform is a MEMS-based analytical module for the purge&trap pre-concentration and (gas)-chromatographic separation of a sample. The two analytical MEMS (pre-concentrator and GC column) are interconnected by means of a MEMS microfluidic manifold. The microfluidic manifold interconnects the analytical MEMS, but it also acts as injector through the integrated micro-valves.

We propose an optical technique for the fast check of the presence, on the exposed surfaces of persons and objects, of explosives and their precursors, or drugs, or in general materials which are not allowed in restricted environments: airports, courts, places of worship, etc. The technique yields bi-dimensional pictures, with exposure time of < 1 sec, reporting the target substances, and their locations and quantities. The technique already provided laboratory preliminary results, to be completed, and fully validated for sensitivity and selectivity.

Detection devices for the presence of molecules of interest (analytes) enjoyed a renewed burst with the introduction of biological components (biosensors). Their high specificity is often used in various fields, from environmental monitoring and biomedicine to the protection and promotion of agri-food products. However, the high cost of production and the lack of compatibility with mass sampling (high-throughput) sometimes limit their use.

We propose a compact innovative spectroscopy system operating in the UV range. In the actual version, designed for gas, it exhibits: an aluminium tubular optical chamber (length can be adjusted; currently is 20 cm); a cheap commercial UV LED; a SiC visible blind UV detector designed and manufactured at the CNR-IMM facilities. The team developed also the electronic chain for wireless remote real time read out; while able to deal with pA current levels, it uses very cheap components and construction technology.

The proposed technology is based on the concept of Power-Over-Fibre (PoF), which involves the transmission of data and power over an optical fiber. This technology is suitable for applications where traditional copper cabling is impractical or undesirable. This is the case with pantographs, where there is a large potential difference between the catenary and the earth, and therefore any electrical contact must be avoided for safety reasons. Furthermore, pantographs operate in an environment with very high electromagnetic interference (EMI).

The platform allows the deployment of a sensor network with peripheral nodes spread on the crop fields or on the environment for the monitoring of crop parameters/environmental parameters. The network architecture integrated LoRa peripheral nodes for short-medium range communication and star-center NB-IoT based for long range communication. It includes a web server and MySQL database for data storage and visualization. The network architecture is scalable to adapt to the area to monitor.

The Q-PLL is a nonlinear circuit which can maintain a locked state when forced by two incommensurate frequencies.

The locked state is a third frequency parametrically selected among those prescribed by the theory of three-frequency resonances in dynamical systems.

In particular, the locked frequency forms a three-frequency resonance with the frequencies of the quasi- periodic input and is closely related to the pitch perception of complex sound in humans.

This form describes a programmable, autonomous and stand-alone imaging system for the acquisition and processing of images containing subjects whose size is larger than 1cm (e.g. gelatinous zooplankton, fishes, litter, manufacts), form the seafloor or along the water column, in shallow or deep waters. It is capable to recognize and classify the image content through pattern recognition algorithms that combine computer vision and artificial intelligence methodologies.

Environmental monitoring is a rapidly growing field, both in academia and industry. The use of wearables for environmental monitoring is a promising technique, as it allows data to be collected continuously and comprehensively. The main problem with using wearables for environmental monitoring is the size and weight of the system, as well as the high degree of specialization required to develop a fully functional device.