Tin Oxide Sensors Research Articles

Some New Insights into the Sensing Mechanism of Palladium Promoted Tin (IV) Oxide Sensor

The combination of techniques including switching experiments, temperature programed reduction and in situ neutron scattering-conductivity are used to investigate the sensing mechanism of 1% Pd/SnO2 toward hydrogen-containing gas mixtures. In particular, the use of the in situ neutron scattering-conductivity for the first time allows the simultaneous monitoring of electrical conductivity and inelastic neutron scattering spectra of the sensor material. Direct evidence is obtained on a reversible migration of hydrogenic species from and to the metal and the underlying tin oxide surface, i.e., reversible hydrogen spillover. As a result of this spillover, a dramatic change in electrical conductivity of the Pd doped tin oxide material is observed. We confirm, in accordance with the known mechanism, that the change of conductivity is based upon the creation or destruction of negatively charged adsorbed oxygen species on the sensor surface. In addition, we report a new but important sensing mechanism, the spillo...

Multicomponent analysis of some environmentally important gases using semiconductor tin oxide sensors

Alumina sapphire based, tin oxide thick film sensors, undoped and doped with precious metals (gold, platinum and palladium) were prepared and annealed at different temperatures, before being examined for determination of carbon monoxide, nitrogen dioxide and methane as single gas or in binary mixtures. Gold-doped tin oxide sensor was found to respond to both CO and NO 2 separately more rapidly than undoped sensor, however, the simultaneous determination of both gases in their binary mixture was not possible. Therefore, in the binary mixture an amperometric sensor was used for the determination of CO while the SnO 2 sensor was used for NO 2. The multicomponent determination of CO and NO 2 was achieved using a set of two platinum-doped tin oxide sensors annealed at 600°C, one at a working temperature of 150°C selective for NO 2, and the other at 300°C selective for CO. On the other hand, the multicomponent determination of CH 4 and NO 2, was achieved using a set of two tin oxide sensors, one is doped with Pd and working at 300°C selective for methane and the other doped with Pt and working at 150°C selective for nitrogen dioxide.

Multicomponent gas mixture analysis using a single tin oxide sensor and dynamic pattern recognition

A new method, which is based on the discrete wavelet transform, is presented for extracting important features from the response transients of a micromachined, tin oxide-based gas sensor. It is shown that two components in a mixture can be simultaneously and accurately quantified by processing the response dynamics of a single sensor operated in a temperature-modulated mode. The discrete wavelet transform outperforms the fast Fourier transform (classical approach) because it is more appropriate for the non- linear frequency-time problem encountered here.

Using the classification model of an electronic nose to assign unknown malodours to environmental sources and to monitor them continuously

The paper provides some considerations resulting from measurements with electronic noses around real sources of malodour in the environment: compost facilities, printing houses, paint shops, waste water treatment plants, rendering plants, settling ponds of sugar factories. The study aims at supplying the concrete information requested by the final user in the field: either a warning signal when the malodour level exceeds some given threshold value, the identification of the source of an odour detected on site, or on-line identification and monitoring of an odour in the field. Very simple instruments are used, either in the laboratory or directly in the field, with a home-made portable e-nose, based on tin oxide sensors. Even with such simple operating conditions, the classification results with DA and PCA are fairly good. The classification functions calibrated with the statistical procedure, on the basis of the learning phase, are used to recognise and to monitor a given malodour. This odour is sometimes mixed with other odorous interferences in the field. The observations reveal some features useful in the frame of the development of a field detector.

Electronic nose: a useful tool for monitoring environmental contamination

The advances in the technology of multisensor arrays and neural computation have allowed the development of “electronic noses”, which has enabled the discrimination of compounds by their odours and consequently, has played a fundamental role in the environmental monitoring. An electronic nose MOSES II (MOdular SEnsor System) with two arrays of eight (tin oxide and quartz microblance) sensors, each one manufactured by Lennartz Electronic/MoTech, was employed in this work. The aim of this research was to discriminate the following factors by odours: (a) small concentrations (ppm) of lindane and nitrobenzene in water, (b) dry solid insecticides (synthetic pyrethroids) such as permethrin, deltamethrin and cypermethrin, (c) mixtures of different quantities of cypermethrin in an inert substance, and (d) solutions of these pyrethroids in an appropriate organic solvent. Contaminating residues of insecticides (lindane and syntethic pyrethroids) and products from the leather manufacture (phenols, nitrobenzene, anilines) are often offloaded into streams or rivers — despite the prohibition regulations — in heedless disregard of the danger they present to the health of the population and the survival of fish and flora.

Measurement of Odor Intensity by an Electronic Nose

ABSTRACT The possibility of using electronic noses (ENs) to measure odor intensity was investigated in this study. Two commercially available ENs, an Aromascan A32S with conducting polymer sensors and an Alpha M.O.S. Fox 3000 with metal oxide sensors, as well as an experimental EN made of Taguchi-type tin oxide sensors, were used in the experiments. Odor intensity measurement by sensory analysis and EN sensor response were obtained for samples of odorous compounds (n-butanol, CH3COCH3, and C2H5SH) and for binary mixtures of odorous compounds (n-butanol and CH3COCH3). Linear regression analysis and artificial neural networks (ANN) were used to establish a relationship between odor intensity and EN sensor responses. The results suggest that large differences in sensor response to samples of equivalent odor intensity exist and that sensitivity to odorous compounds varies according to the type of sensors. A linear relationship between odor intensity and averaged sensor response was found to be appropriate for the EN based on conducting polymer sensors with a correlation coefficient (r) of 0.94 between calculated and measured odor intensity. However, the linear regression approach was shown to be inadequate for both ENs, which included metal oxide-type sensors. Very strong correlation (r = 0.99) between measured odor intensity and calculated odor intensity using the ANN developed were obtained for both commercial ENs. A weaker correlation (r = 0.84) was found for the experimental instrument, suggesting an insufficient number of sensors and/or not enough diversity in sensor responses. The results demonstrated the ability of ENs to measure odor intensity associated with simple mixtures of odorous compounds and suggest that ANN are appropriate to model the relationship between odor intensity measurement and EN sensor response.

Air pollution monitoring using tin-oxide-based microreactor systems

Recent research on metal-oxide gas sensors has shown that such devices respond to environmentally relevant concentrations of O 3, NO 2, NO and CO. Such sensors, therefore, hold the potential of becoming inexpensive monitors of air pollution. In our work, tin-oxide sensors were embedded into tiny microchambers with internal volumes of 270 μl to form microreaction chambers. Enclosing samples of polluted air within such chambers, gas depletion reactions can be observed, which provide analytical information about the pollutant species enclosed. We have extended this approach to a microanalysis system containing two sensor chambers, one equipped with a thin-film and the other with a thick-film tin-oxide sensor element. Performing experiments on such a system, we were able to obtain analytical information about air pollutants in relevant concentrations for indoor as well as outdoor applications. We further show that in addition to the very gas-analysis functions, our air-monitoring system can also be equipped with calibration and self-test features.

Detection and differentiation of C 4 hydrocarbon isomers over the Pd–SnO 2 compressed powder sensor

The detection and differentiation of C 4 hydrocarbon gases, including n-butane, 1-butene, iso-butylene, cis- and trans-2-butene are investigated over a palladium-promoted tin oxide sensor using AC impedance. It is found that 1% Pd–SnO 2 gives a good linear response and good sensitivity with respect to a wide range of n-butane concentrations (0–10,000 ppm). At high operation temperatures (≥400°C), the tin oxide-based sensor offers no differentiation on different C 4 gases and is consistent with the literature that this type of sensor is rather non-selective. However, at ≤300°C, the sensor gave broadly two different types of sensitivity towards the C 4 gases of the same concentration: the sensitivities of n-butane and trans-2-butene are analogous, while 1-butene, iso-butylene and cis-2-butene all show sensitivities a factor of 20–30 higher. The sensitivity difference apparently depends on the chemical reactivity of the particular C 4 molecules, which in turn depends on the presence and position of their double bond. Hence, high sensitivity is obtained if the positions of their double bond are more susceptible for attack by surface oxygen species leading to total surface combustion of the C 4 hydrocarbons. On the other hand, if there is an absence or a surface inaccessible double bond as in the cases of n-butane and the trans-2-butene, surface attack to the hydrocarbon gases involves a kinetically more difficult hydrogen abstraction reaction, hence giving a lower sensitivity.

Application of radiometric temperature determination methods to semiconductor gas sensors

A radiometric method for the determination of the operating surface temperature of very small objects to within ±5 K has been applied to commercial semiconductor gas sensors operated in a static atmosphere. The method involves the collection of the infrared (IR) emission spectrum of the sensor at regular intervals over the operating heater voltage range, followed by the fitting of ambient-corrected Planck functions to determine the temperature at each voltage. At least one independent calibrating temperature measurement (to eliminate the effects of sensor emissivity and spectrometer response) is obtained using the known melting point of an inorganic salt. The operating voltage–temperature relationships for two popular Figaro tin oxide sensors were found to be pseudo-linear and are reported as T=103 V+214±3 K for the Figaro TGS813 sensor with its base removed, T=101 V+224±5 K for the TGS813 with its base attached, and T=106 V+238±5 K for the Figaro TGS2611 sensor. (The temperature of the sensors does not rise appreciably above ambient when they are operated below 0.5 V.) These results indicate that sensor temperatures are significantly higher than most previously reported estimates, particularly those made using infrared thermometers (IRTs). A heat loss model for the sensors is discussed, and the calibration of the heater resistance–temperature relationship is achieved for the TGS2611.

Aggregation of sensory input for robust performance in chemical sensing microsystems

This paper demonstrates the usefulness of aggregating information generated from arrays of chemical sensors for improving the ability to discriminate among target chemicals and their potential interferents. Two types of aggregation methods are evaluated; the first set do not compress the data, but incorporate effects from neighboring sensors into the output of each sensor in an array. The second method does result in compression of data and aggregates multiple sensor outputs into a single, more robust signal. Methods for processing data and aggregating and smoothing outputs from arrays of tin-oxide sensors are comparatively analyzed. Processing parameters studied include those related to simple averaging, linear-weighted averaging, and exponential smoothing across operating temperature and across type of sensing film in the dimensionality of the array. Aggregation techniques are evaluated during various stages of both the transient and steady-state response of the array to quantify the early decision-making capability of the array over that of a single or small number of unprocessed sensors. Aggregation strategies are studied in combination, and results are extracted by quantitatively measuring the goodness of clustering for each case. Cluster analysis, including principal component analysis (PCA), is used to determine which of these processing techniques are most effective. It is shown that aggregation methods, whether they reduce transmission bandwidth or not, improve the performance of a 30-element, tin-oxide heterogeneous sensor array in discriminating among common breath alcohol components (ethanols), their interferents (acetone, formaldehyde, isopropyl), and a contrast substance (ammonia). Aggregation generates a best-case 42% improvement in separability of clusters and 6.25% improvement in the tightness of clusters. Results are shown that clearly demonstrate the usefulness of aggregation in heterogeneous arrays among sensors whose outputs possess an appreciably degree of correlation (overlapping specificity).

Relationship between ethanol gas sensitivity and surface catalytic property of tin oxide sensors modified with acidic or basic oxides

A semiconductor gas sensor using SnO 2 was loaded with acidic or basic oxides (5 wt.%) to investigate ethanol-gas sensing properties and related catalytic properties. The sensitivity to ethanol gas at 300°C increased tremendously with an addition of a basic oxide (e.g., La 2O 3), while it hardly changed with that of an acidic oxide (WO 3). It turned out that the addition of the basic metal oxide to SnO 2 brought about enhancement of catalytic activity not only for the dehydrogenation of ethanol gas to CH 3CHO but also for the consecutive oxidation of CH 3CHO to CO 2. On the other hand, the acidic metal oxide enhanced only the dehydration reaction, showing even an adverse effect on the consecutive oxidation. Based on these results, it was concluded that the enhancement of the catalytic oxidation activity to an appropriate level could be a reason for the high sensitivity to ethanol gas for the sensors loaded with basic oxides, particularly one loaded with La 2O 3.

Rank extraction in tin-oxide sensor arrays

It is shown that data pre-processing by rank-order filtering can significantly improve the odor discrimination capability of an array of chemical sensors, while simultaneously reducing the amount of data to be processed. This work is a first example in feature extraction from tin-oxide sensors that both reduces the size of the data set and simultaneously improves the discrimination performance of the array. This work is aimed toward the design of remote sensor modules where bandwidth reduction and improved accuracy are both essential to system performance. The effectiveness of extracting rank from a 30-element array of tin-oxide sensors is presented. Results are extrapolated to other arrays of chemical sensors whose specificities and response characteristics overlap. Methods for processing data and extracting rank-related features from arrays of tin-oxide sensors are comparatively analyzed. Processing parameters studied include those related to temporal filtering and window-averaging, pre-scaling (to remove baseline), sample acquisition time, and the number of ranks used in rank-order filtering of the data during the transient and steady state response. Cluster analysis, including principal component analysis (PCA) and a novel method described herein, is used to determine which of these processing techniques are most effective. Artificial neural networks, specifically multi-layer perceptrons and radial basis function networks, are used to further investigate the ability to discriminate odors on the basis of the extracted features. The analysis is performed for an array of 30 tin-oxide sensors applied to detecting a sampling of breath alcohol mixtures (beer, wine, vodka) and common interferents (acetone, formaldehyde, isopropyl). Ammonia is included as a contrast substance. For the set of seven odorants studied, it is found that using rank-order filtering with 10 or more ranks improves odor recognition rate by a multi-layer perceptron neural network from 92% to 95%. If one odor (vodka) is removed from the study set, the recognition rate for the remaining odors improves from 95% (with no rank-order filtering) to 99%. Simultaneously, the dimensions of the data set for each odor are reduced from 30 sensors×18,000 time steps (12 bit samples) to N integer values, where N is the number of ranks used in the rank-order filtering.

Use of a simple tin oxide sensor array to identify five malodours collected in the field

A laboratory-made malodour sensing system including 12 commercial tin oxide gas sensors (Figaro Engineering) is used to identify five typical sources of olfactive annoyance: printing houses, paint shop in a coachbuilding, wastewater treatment plant, urban waste composting facilities and rendering plant. In this work, all the samples are collected in the field from real malodours in uncontrollable conditions. The ability of the system to predict the origin of unknowns odoriferous samples is investigated. The test of various pre-processing data algorithms shows that the best classification results are obtained with a parameter free of the sensor base-line. The differences in sensor responses among the five odours are shown by icon plots and confirmed by principal component analysis, which highlights four representative clusters. Classification models calibrated by discriminant analysis and artificial neural network are validated on unknowns samples. Chemical relationships between the sensors and the classification results proves that the recognition is not fortuitous. In spite of the influence of environmental parameters, results demonstrate the ability of a simple system to detect and identify typical olfactive annoyances.

Discrimination of individual gas/odor using responses of integrated thick film tin oxide sensor array and fuzzy-neuro concept

A new neural network classifier for an Intelligent Gas Sensor (IGS) application is presented. The classifier is trained on fuzzyfied training set. Its superior classification and learning performance is demonstrated for discrimination of alcohols and alcoholic beverages using published data of thick film tin oxide sensor array fabricated and characterized at our laboratory. The new model proposed in this article not only gives a steep and monotone learning curve, but also exhibits lower sensitivity to learning parameter choices.

Sol–gel derived pure and palladium activated tin oxide films for gas-sensing applications

Pure and Pd activated SnO 2 films on Corning 7059 substrates were prepared by the sol–gel dip coating method and used as active material in gas-sensing devices. SnCl 4 and Pd(CH 3COO) 2 were used for tin and palladium sources. The SnO 2 sol was prepared from 1:3:9:4 molar ratios of SnCl 4:H 2O:C 3 n H 7OH:C 4 i H 9OH. The 5 equivalent wt% PdO-95% SnO 2 sol was prepared by mixing the required amount of Pd acetate to the pure SnO 2 sol. The dried (110°C/0.5 h) films were heat-treated in air at 600°C for 1 h. Pure SnO 2 films showed ethanol gas sensing characteristics similar to most of the commercially available tin oxide sensors. An improvement in the sensitivity towards ethanol gas at relatively low temperature was observed in case of Pd activated SnO 2 films. The improvement of sensing properties of Pd activated films was due to high surface roughness/surface area, oxygen vacancies and presence of PdO microcrystallites.

Response of oxygen plasma-treated thick film tin oxide sensor array for LPG, CCl 4, CO and C 3H 7OH

In the present paper, studies have been made to analyze the effect of oxygen plasma and dopants on the room temperature sensitivity of tin oxide, thick film gas sensors for various gases. To achieve this, an array of sensors was fabricated by thick film technology using tin oxide paste doped with Pd, Pt, CuO, ZnO, Cd and SnO 2. Subsequently, the fabricated array was annealed in oxygen plasma for 15 min. The response of the array has been studied for different concentrations of CO, LPG, CCl 4 and C 3H 7OH. The response–recovery time analysis of the fabricated array has also been carried out. These studies reveal that the sensitivity of oxygen plasma-treated array is much higher at room temperature compared with the untreated array. Moreover, addition of different dopants enhance the sensitivity and selectivity of the sensor to various gases/odours. The Pt-doped sensor has been found to be more sensitive to CO and LPG, whereas the Pd-doped sensor shows a good response towards CCl 4 and C 3H 7OH, and the Cd-doped sensor was found to show a fairly good response to all four gases.

Comparative studies of doped and surface modified tin oxide towards hydrogen sensing: Synergistic effects of Pd and Ru

A surface functionalised gas sensing material capable of giving better sensitivity and selectivity to hydrogen is demonstrated by grafting few Ru–O and Pd–O linkages in the surface of tin oxide. A systematic evaluation of the surface coverage, morphology and thermal stability using different techniques like EDAX, Cyclic voltammetry, SEM and TGA indicates the importance of an optimum distribution of Ru/Pd ratio (1.28) in dictating both sensitivity and selectivity. A comparison of the optimum performance of conventionally doped (225) and surface modified (1350) tin oxide to 1000 ppm hydrogen at 250°C illustrates the clear advantages offered by surface modified tin oxide in enhancing the sensitivity. Moreover, the synergistic effect by surface functionalisation with both Ru and Pd species is emphasised in comparison to individually modified tin oxide sensors.

Steady‐State and Transient Behavior of Thick‐Film Tin Oxide Sensors in the Presence of Gas Mixtures

In this paper, a new nonlinear diffusion‐adsorption model for the steady‐state and transient response of thick‐film tin oxide gas sensors in the presence of multicomponent gas mixtures is discussed in detail. The model, which takes into account gas interaction during the adsorption process, accurately accounts for the sensor behavior for a wide range of gas concentrations. The model predictions were validated by measuring binary mixtures of ethanol, toluene, and ethylbenzene with commercially available thick‐film tin oxide gas sensors. New parameters that may be useful for identifying components in a gas mixture were obtained by adjusting experimental and theoretical transients.

Transient response of thick-film tin oxide gas-sensors to multicomponent gas mixtures

Abstract In this study we analyse the conductance transient of thick-film tin oxide sensors under a step change in a multicomponent gas mixture concentration. We discuss a new nonlinear diffusion model which accurately depicts experimental sensor behaviour in the low-medium gas concentration range. This model allows a set of n concentration-independent parameters ( τ ′ 1 , τ ′ 2 , ..., τ ′ n ) to be estimated. Each parameter is characteristic of a species present in the n -component mixture and varies from one sensor to another. By adjusting conductance transient measurements of binary mixtures (ethanol, toluene and ethylbenzene) to theoretical transients, we obtained τ ′ i values. This new set of constants may give useful information for identifying the components of gas mixtures.

Electrical characterization of a thin film tin oxide sensor array for VOCs detection

A tin oxide sensor array has been fabricated using the r.f. reactive sputtering technique. Some elements of the array have been doped with Pt, Pd and Al by sputtering. Sensors have been characterized by DC electrical measurements for different volatile organic compounds (VOCs) such as benzene, toluene, chloroform, propanal, methyl–ethyl–ketone (MEK) and octane, in a concentration range from 50 to 500 ppm in dry air at 300°C. The best response has been obtained by Pt and Pd doped sensors for the oxygenated compounds, but for all gases good sensitivities are shown. The impedance spectra were obtained by AC variable-frequency measurements for all the sensors in air, in benzene and in propanal atmospheres at 300°C. The VOCs peak frequencies changed with regard to air peak frequencies for all the sensors. The roles of dopants and doping level are discussed.