Artificial olfactive systems
A chemical sensor is a device that transforms chemical information (ranging from the concentration of a specific sample component to total composition analysis) into an analytically useful signal.
Due to their small dimension, low cost, low power consumption, on-line operation and high compatibility with microelectronic processing, conductometric semiconducting metal oxides are between the most promising devices in the field of solid state chemical sensors. The fundamental sensing mechanism of semiconductor gas sensors relies on a change in electrical conductivity due to the interaction process between the surface complexes and the gas molecules to be detected.
The most used approach to face the lack of selectivity is the use of an Artificial Olfactive System (AOS) – also called “Electronic Nose” (EN).
An EN is an instrument base on a sensor array, each sensor showing a different response spectra to gases. A pattern recognition software associates the response of the whole array (called olfactive fringerprint) to the smelled atmosphere. In this way the EN builds-up a database that is further used to selectively classify/measure the target odour/compound.
The EN is a versatile instrument that is customized (sensor selection, identification of the sampling method, pattern recognition software development) for each specific application.
Some activities carried out /in progress at SENSOR Lab are detailed in the following.
Food quality control
Modern food industry demands more effective, faster and affordable technologies to perform on-line controls of food and drinks processing operations for microbial contamination screening. Similarly, the control of drinking water quality for biological or chemical contaminants is a demanding challenge both in developed and emerging countries.
Electronic Noses (ENs) have recently emerged as valuable candidates in various areas of food and drinks quality control, including microbial contamination diagnosis. The superior sensitivity and stability of MOX-NW sensors are exploited. The EN procedure is simple and automated; the instrument, once trained, can recognize contaminated food samples without the human operator support.
EN technology has been used and is currently in use at Sensor Lab [1 ,2] for: (a) Early detection of microbial contamination in processed tomatoes; (b) Fungal contamination on green coffee beans, (c) Detection of water contaminants.
Detection of hidden people for border control application
Illegal traffic of people is a major issue in security. The need to face this crime as well as the planning of countermeasures and the identification of missing capabilities has been the subject of several security programs proposed both at a world-wide and an European level. Nowadays, dogs represent the most effective “tool” to face these traffics, but they present intrinsic drawbacks that limit their continuous and systematic use: they can’t work in a 24/7 way (24 hours per day and 7 days per week).
In this frame, CNR-INO is partner in the SNOOPY project (http://www.snoopy-project.eu/), which aims to the development of a handheld artificial sniffer system for customs/police inspection purposes, e.g. the control of freight containers. The artificial system should be able to seek hidden, living persons. The instrument consists of a vapor sampling pump unit, an enrichment unit, a desorption unit, a detection unit (sensor array) and an alarm indicator unit. Different kinds of sensors will be used together with pattern recognition software, so that each target can be detected as selective as possible. The sniffer instrument will be benchmarked towards dogs and towards ion mobility spectrometry.
The SNOOPY sniffer will be:
1) portable, thanks to the use of low-weight, small size and low-power consumption technologies;
2) suited to work in a 24/7 way;
3) able to recognize the sniffed atmospheres on its own;
4) Equipped with a small pipe to collect odors in proximity of small apertures;
5) user friendly: the user will receive a direct information and him/her will not be required to have scientific or technical competences to interpret the instrument display.
 M. Falasconi, I. Concina, E. Gobbi, V. Sberveglieri, A. Pulvirenti, and G. Sberveglieri, Electronic Nose for Microbiological Quality Control of Food Products, International Journal of Electrochemistry, vol. 2012, Article ID 715763, 12 pages, 2012.
 V. Sberveglieri et al, A Novel Electronic Nose as Adaptable Device to Judge Microbiological Quality and Safety in Foodstuff, BioMed Research International, 529519 (2014).
Electronic nose EOS835 working with olive oil samples
Personale INO dipendente:
Baratto Camilla, Ponzoni Andrea,
Faglia Guido Pietro, Soprani Matteo,