M.C. Horrillo

Identification of typical wine aromas by means of an electronic nose

In the field of electronic noses it is not very usual to find many applications in wine detection. Most of them are related to discrimination of wines in order to prevent their illegal adulteration and detection of off-odours but their objective is not the identification of wine aromas. In this paper, an e-nose using headspace as an extraction technique is used for the identification of typical aromatic compounds present in white and red wines. The descriptors of these compounds are: fruity, floral, herbaceous, vegetative, spicy, smoky, and microbiological and they are responsible for the usual aromas in wines; concentrations differ from 2 to 10 times the threshold concentration humans can smell. Some of the measured aromas are: pear, apple, peach, coconut, rose, geranium, cut green grass, mint, vanilla, clove, almond, toast, wood and butter. Principal component analysis (PCA) shows datasets of this group of compounds are clearly separated and radial basis neural networks (RB-NN) show a 98% rate of success in classification.

Threshold detection of aromatic compounds in wine with an electronic nose and a human sensory panel.

An electronic nose (e-nose) based on thin film semiconductor sensors has been developed in order to compare the performance in threshold detection and concentration quantification with a trained human sensory panel in order to demonstrate the use of an e-nose to assess the enologists in an early detection of some chemical compounds in order to prevent wine defects. The panel had 25 members and was trained to detect concentration thresholds of some compounds of interest present in wine. Typical red wine compounds such as whiskeylactone and white wine compounds such as 3-methyl butanol were measured at different concentrations starting from the detection threshold found in literature (in the nanograms to milligrams per liter range). Pattern recognition methods (principal component analysis (PCA) and neural networks) were used to process the data. The results showed that the performance of the e-nose for threshold detection was much better than the human panel. The compounds were detected by the e-nose at concentrations up to 10 times lower than the panel. Moreover the e-nose was able to identify correctly each concentration level therefore quantitative applications are devised for this system.

Detection of toxic gases by a tin oxide multisensor

A tin oxide multisensor with eight sensor elements has been utilized to detect different gases that are emitted from the chemical industry. The different sensors have been prepared using the RF reactive sputtering technique. Some components of this multisensor were doped with Pt and Cr by sputtering. Each sensor has been characterized by electrical measurements for detection of atmospheric pollution (nitrogen dioxide, carbon monoxide, toluene, and propanal). The detected gases are toxic and their extreme concentrations recommended in air oscillate from 1 ppm to hundreds of ppm. Detections were carried out with a single gas or a gas mixture (two gases) in dry air at 250/spl deg/C. The sensitivity and selectivity to these gases were studied. Backpropagation neural networks and their classification results were discussed.

The influence of the tin-oxide deposition technique on the sensitivity to CO

Abstract The sensor parameters for CO detection on semiconductor films are strongly dependent on the film-preparation techniques. This is observed for semiconductor films prepared by sputtering and screen-printing. The influence of sensor-film porosity on the sensitivity to CO has also been observed. The effect of catalysts on semiconductor sensors combines the catalytic activity of the metals with the surface properties of the semiconductor oxides. It is very important that the catalyst is highly dispersed on the particles of the semiconductor and that the added quantity is adequate. We have studied the effect of catalysts (Pt and Pd on films prepared by reactive sputtering and screen-printing by analysing their respective roles. Depending on whether the catalyst is Pt or Pd, the catalytic mechanism is different. Wiht Pt the effect is purely chemical, whereas with Pd the effect is electronic. Surface analysis technique (GAXRD, XPS, EDX) have been used to compare the two different preparation techniques with regard to thickness, composition and morphology.

The interaction of different oxidizing agents on doped tin oxide

Abstract The interaction of NO2, NOx and O2 and O2 on an SnO2 thin-film surface is studied. Experiments have been carried out for different tin-oxide films, undoped and doped with Pt, In and Al, prepared by reactive sputtering (r.f.) on alumina substrates. These films should allow the development of detectors for nitrogen oxides at concentrations of about a few ppm. Conductance measurements have been done in a constant flow of inert atmosphere (N2) and in synthetic air containing oxidizing agents (NO2 and NOx) to study directly adsorbed NO2 and NO and their reaction with chemisorbed oxygen. The results are discussed in terms of surface reactions.

Array of Love-wave sensors based on quartz/Novolac to detect CWA simulants.

An array of Love-wave sensors based on quartz and Novolac has been developed to detect chemical warfare agents (CWAs). These weapons are a risk for human health due to their efficiency and high lethality; therefore an early and clear detection is of enormous importance for the people safety. Love-wave devices realized on quartz as piezoelectric substrate and Novolac as guiding layer have been used to make up an array of six sensors, which have been coated with specific polymers by spin coating. The CWAs are very dangerous and for safety reasons their well known simulants have been used: dimethylmethyl phosphonate (DMMP), dipropyleneglycol methyl ether (DPGME), dimethylmethyl acetamide (DMA), dichloroethane (DCE), dichloromethane (DCM) and dichloropentane (DCP). The array has been exposed to these CWA simulants detecting very low concentrations, such as 25 ppb of DMMP, a simulant of nerve agent sarin. Finally, principal component analysis (PCA) as data pre-processing and discrimination technique, and probabilistic neural networks (PNN) as patterns classification technique have been applied. The performance of the sensor array has shown stability, accuracy, high sensitivity and good selectivity to these simulants.

Edible and non-edible olive oils discrimination by the application of a sensory olfactory system based on tin dioxide sensors

An array of semiconductor sensors has been developed to discriminate virgin olive oil samples based on their organoleptic characteristics. The multisensor, developed at laboratory, is composed by 14 sensing elements of tin dioxide thin layers (doped with Cr and In, and undoped) deposited by the reactive sputtering technique. The sensors are stable and show good repeatability. Off-flavors and extra-virgin olive oil samples, taken at the outlet of the vertical centrifuge of a small experimental olive oil mill and sensory evaluated, have been used. A good discrimination of edible (extra-virgin and virgin) from non-edible (lampante) olive oils has been obtained through the statistical method of principal component analysis (PCA).

Characterization of an array of Love-wave gas sensors developed using electrospinning technique to deposit nanofibers as sensitive layers.

The electrospinning technique has allowed that very different materials are deposited as sensitive layers on Love-wave devices forming a low cost and successful sensor array. Their excellent sensitivity, good linearity and short response time are reported in this paper. Several materials have been used to produce the nanofibers: polymers as Polyvinyl alcohol (PVA), Polyvinylpyrrolidone (PVP) and Polystirene (PS); composites with polymers as PVA+SnCl4; combined polymers as PS+Poly(styrene-alt-maleic anhydride) (PS+PSMA) and metal oxides (SnO2). In order to test the array, well-known chemical warfare agent simulants (CWAs) have been chosen among the volatile organic compounds due to their importance in the security field. Very low concentrations of these compounds have been detected by the array, such as 0.2 ppm of DMMP, a simulant of sarin nerve gas, and 1 ppm of DPGME, a simulant of nitrogen mustard. Additionally, the CWA simulants used in the experiment have been discriminated and classified using pattern recognition techniques, such as principal component analysis and artificial neural networks.

A potentially selective methane sensor based on the differential conductivity responses of Pd- and Pt-doped tin oxide thick layers

Abstract Derived from a concept suggested by E. M. Logothetis et al., Proc. 2nd Int. Meet. Chemical Sensors, Bordeaux, France, 1986, p. 175, two differential sensing devices, based on the different catalytic properties of palladium and platinum, are proposed. The first one consists in covering two screen-printed layers of pure tin dioxide by Pd and Pt-doped filters. No major difference is observed between these sensors, probably because of the lack of thickness of the screen-printed filters. In the second device, tin dioxide is directly doped with palladium for one sensor and with platinum for the other. The difference in the response to methane is now sufficient to consider the feasibility of a differential device. However, such sensors have no long-term stability which can only be achieved by covering the layers with inert filters. These filtered SnO2:Pd and SnO2:Pt sensors, now satisfactory as far as differential sensitivity and long-term stability are concerned, also exhibit an important differential response to ethanol, but fortunately reverse to that to methane. The latter result enables a sensing device to be constructed which is selective to methane with respect to ethanol, and insensitive to changes in relative humidity and/or gas flow.

Hall coefficient measurements for SnO2 doped sensors, as a function of temperature and atmosphere

Abstract The Hall coefficient has been measured for thin (300 nm) r.f. sputtered Al, In-doped SnO 2 and undoped SnO 2 films. Two experiments have been carried out: (i) Hall measurements in a temperature range of 20 to 300 °C in inert (Ar), reductor (H 2 0.2%) and oxidant (O 2 2%) atmospheres. Aged films were also tested in Ar. (ii) Hall measurements as a function of H 2 (0–2%) and O 2 (0–20%) concentrations at fixed temperature. Conduction mechanisms were discussed adjusting temperature dependent results to a grain boundary carried-trapping model. A grain size dependent sensitivity model has been used to explain H 2 and O 2 sensitivities. Combining results from both models, we are able to establish the best conditions for detection of reductor and oxidant gases.