Technologies

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.

CNR-ISTEC develops geopolymer composites for thermostructural applications, such as: self-supporting cavities; thermal and acoustic insulation; thermal and fire barriers; high temperature coatings and damping; molds and cores for foundry; foams and refractory linings. Geopolymers are chemically bonded materials at T <300 ° C. Being inorganic polymers without water in the structure, they tolerate high temperatures: they are incombustible, do not emit gas or fumes and do not explode.

We propose a portable chemical analysis system capable of identifying chemical substances at trace concentrations (sub-ppm), even in case of a complex matrix of interfering species.

We offer integrated tools for the acquisition, analysis, modelling and optimization of visitor flows in museums characterized by frequent congestion and/or complex geometries. Our intervention is divided into 4 phases:

1) Data acquisition related to the paths followed by visitors in the museum, number of visitors in the rooms, time of permanence, ... The acquisition is performed via a specific IoT system, smartphone app or manual counting.

Optical backplane for interconnection between boards of a high-capacity ICT apparatus, data-center, server and the related automatic assembly method. The solution is based on optical connections between boards with an optimized layout on a support with mechanical constraints that involve controlled deformations of commercial optical fibers with standardized connectors. The entire interconnection circuit is divided into N independent circuits, each of which makes the connections between all the boards (Full-Mesh).

An interoperable and modular Digital Geospatial Ecosystem (DGE) is proposed, designed, implemented and tested in order to: collect in real time, manage and share geographic data; make usable tools and functionalities to support actions to prevent, monitor and mitigate impacts from extreme events as well as to prepare for and respond to emergency situations. The DGE is composed of the following modules:

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.