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1  V. Laskaryov Institute of Semiconductor Physics NAS of Ukraine
2  Institute for the Microelectronic and Microsystems, CNR, Lecce
Academic Editor: Francisco Falcone


Electronic nose (EN) is a technology for fast and adequate identification of complex gaseous mixtures in many vitally important areas. The idea is to use a small set of low-selective sensors with overlapping selectivity profiles instead of a huge number of specific sensors. The response of such an array of low-selective sensors is a chemical image (CI) of a gaseous mixture. The ability of an EN system to distinguish different mixtures is defined by its ability to produce unique CI. The latter is defined, first of all, by the sensors adsorption properties.

We propose an approach to increase the versatility of low-selective sensor arrays by using the virtual sensors approach. By “virtual sensor” in this case we mean a sensor able to change its adsorption properties in conditions of illumination. This allows multiple responses of the same physical sensor for an analyte to be obtained - a set of these responses for different lighting conditions is a data set for forming a unique chemical image of the analyte.

Within this scenario, we were able to successfully distinguish between homologous alcohols (methyl, ethyl, and isopropyl alcohols) using organic-inorganic nanostructured sensitive layers based on ZnO nanoparticles and phthalocyanines. It must be emphasized that this is a rather difficult analytical problem, since alcohols have both similar molecular weights and physicochemical properties.

Thus, we have demonstrated the possibility of reconfiguring multisensor arrays by controlling the adsorption properties of sensors by illuminating them in different regions of the spectrum (usually UV-VIS-IR). This is a step forward in the development of multi-purpose universal EN systems, the selectivity profile of which can be controlled by external influences without changing the composition of the base sensor array.

Keywords: Electronic nose; multisensor array; low-selective sensors; virtual sensors; ZnO nanoparticles;