The response to relative humidity (RH) and alcohol vapors of resistive-type sensors based on nanobeads of conjugated polymers, namely polyphenylacetylene (PPA) and copolymer poly[phenylacetylene-(co-2-hydroxyethyl methacrylate)] (P(PA/HEMA)), were investigated. Sensors based on ordered arrays of these nanostructured polymeric materials showed stable and reproducible current intensity variations in the range 10-90% of relative humidity at room temperature. Both polymers also showed sensitivity to aliphatic chain primary alcohols, and a fine tuning of the sensor response was obtained by varying the chain length of the alcohol in relation to the polarity. The nanostructured feature of polymeric-based membranes seems to have an effect on the sensing response and an enhancement of the sensitivity was observed for the response to water and alcohol vapor variations with respect to previous studies based on amorphous polyphenylacetylene. High stability of the polymeric nanostructured membranes was detected with no aging after two weeks in continuum stressing measurement conditions.
Phenanthrene is a hydrophobic organic pollutant, composed of three--fused benzene rings belonging to polycyclic aromatic hydrocarbons (PAHs). PAHs are produced by incomplete combustion of organic matter due to natural events, i.e. fires, and anthropogenic actions, i.e. C--containing fuels combustion. The presence of PAHs in contaminated soils is usually detected by classical extraction techniques, such as solvent extractions through Soxhlet extractor. In this work two recently developed techniques (solid phase microextraction-SPME and electronic nose-EN) able to analyse the headspace of solid or liquid samples were used to monitor the possible degradation of phenanthrene in an artificially contaminated soil. The analysis by SPME showed a drastic decrease of phenanthrene content after 30 days of incubation (−92%) and different treatments with nutrient solutions and/or surfactant improve this rate up to 97%. Differently, the analysis of soil headspaces by EN, processed by principal component analysis (PCA), showed that contaminated and uncontaminated soil samples (controls) might be distinguished on a temporal scale. Furthermore, PCA showed that phenanthrene--contaminated soil samples produced chemical images, which were delayed relative to controls at the same period of incubation. The application of partial least square--discriminant analysis (PLS DA) to chromatograms obtained by SPME pointed out the presence, in the headspace of phenanthrene--treated soils, of a series of possible indicators involved in phenanthrene degradation, which were completely absent in relative unpolluted controls. Results suggest that the two techniques do not necessarily represent mutually exclusive alternatives, but giving different information, they may be considered as complementary.
The aim of the present study is to combine a bio-inspired nanofibrous artificial epithelium to the electronic nose (e-nose) principles. The sensing device set up was an electronic nose consisting of an array of 9 micro-chemoresistors (Cr-Au, 3×3) coated with electrospun nanofibrous structures. These were comprised of doped polyemeraldine base blended with 3 different polymers: polyethylene oxide, polyvinilpyrrolidone and polystyrene, which acted as carriers for the conducting polymer and were the major responsible of the features of each fibrous overlay (electrical parameters, selectivity and sensitivity ranges). The two sensing strategies here adopted and compared consisted in the use of 2 different textural coatings: a single- and a double-overlay, where the double-overlay resulting from overdeposition of 2 different polymer blends. Such e-nose included a plurality of nanofibres whose electrical parameters were at the same time depending on each polymer exposure to analytes (NO(2), NH(3)) and on the spatial distribution of the interlacing fibres. The morphology of the coating arrangements of this novel e-nose was investigated by scanning electron microscopy (SEM) and its sensor responses were processed by multicomponent data analyses (PCA and PLS) reporting encouraging results for detection and recognition of analytes at ppb levels.
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