Technologies

The NanoMicroFab infrastructure, support companies operating in the field of micro and nanoelectronics through the supply of materials, development of processes, design, fabrication and characterization of materials and devices. NanoMicroFab makes use of existing CNR facilities of the Institute of Microelectronics and Microsystems, the Institute of Photonics and Nanotechnologies and the Institute for the Structure of Matter and provides: • a complete line of development of devices based on wide band gap semiconductors.

Celiac disease and non-celiac gluten sensitivity affect a large portion of the world population. Furthermore, the percentage of people who adopt the gluten free diet is constantly increasing because it is perceived to be healthier. We have previously developed a food grade enzymatic procedure (transamidation) for wheat flour capable of making gluten unable to induce the inflammatory response in the intestine of celiac disease patients.

The technology concerns planar optical antennas composed of thin metal films and dielectric materials for the efficient direction of the light emitted by light sources, such as fluorescent molecules and bio-markers. They consist of a reflector layer, adjacent to the substrate, and a director, semi-reflective, between which the emitter is positioned, integrated into a homogeneous dielectric layer.

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 environment as well as the food production provide a number of both natural and synthetic compounds whose effects on human being as an organism have not yet been determined nor investigated.

The prototype uses soil moisture sensors which, through a measurement of dielectric permittivity, estimate the soil moisture based on which irrigation is started through relay-controlled solenoid valve. The system was developed using Open Source technologies. Specifically, for the hardware components, a small sized board computer Raspberry PI 3B + was used together with a 4G LTE Wi-Fi router and a Modbus rs485 / USB converter.

High-Resolution Nuclear Magnetic Resonace (NMR) in solution also combined with multivariate statistical analysis to determine the quality and authenticity of saffron. Particularly the content of components (metabolites) is evaluated.

To the enterprises working in the field of nutrition/nutraceutics and drug development/repositioning, we offer the know-how and state-of-the-art instrumentation of our labs to monitor multiple relevant biological parameters at the cellular level: metabolic activity, vitality, health, but also stress and toxicity. The use of advanced imaging techniques based on fluorescent/bioluminescent probes together with the availability of time-lapse acquisitions, guarantee the cutting-edge analysis of different biological parameters over time.

Our team can develop low-cost ultra-flexible sensors integrated on plastic substrate for volatile organic compounds (VOCs) and gas detection. These devices combine scalable fabrication technologies, implementing active materials such as nanostructured metal oxides or stack of nanostructures decorated with metal nanoparticles, thus enabling a high sensitivity (in the range of hundreds of ppb). These devices can be applied to numerous industrial and commercial sectors and they can be embedded in systems that are more sophisticated.

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.