Tin Dioxide Gas Sensors Research Articles

On the mass action law and the power law response in tin dioxide gas sensors

On the mass action law and the power law response in tin dioxide gas sensors

A review on tin dioxide gas sensor: The role of the metal oxide doping, nanoparticles, and operating temperatures

Metal oxide gas sensors have many advantages over other solid-state gas monitoring devices, including low cost, ease of manufacture, and small design. However, the shape and structure of sensing materials have a considerable impact on the performance of such sensors, posing a significant challenge for gas sensing properties on materials or dense films to attain high-sensitivity characteristics. Various tin dioxide (SnO2) nanostructures have been devised to increase gas sensing characteristics such as sensitivity, selectivity, and response time, among other characteristics. An overview of the most well-known techniques for synthesizing gas-sensing films, as well as the influence of doping with various metal oxides, nanoparticle size, and operating temperature on the gas-sensing properties of such films, is discussed in this work. The gas sensing mechanisms and the gas detection techniques are presented in detail. The metal oxide doped SnO2 showed a strong response for SO2 and NO2 gases, whereas nanoparticle doping plays a crucial effect in increasing SnO2 sensitivity towards H2, H2S, NO2, CO, Ethanol, etc. Furthermore, the effect of operating temperature on SnO2 response is discussed in this report. SnO2 has a high sensitivity over a wide temperature range (100-350 °C).

Acetone discriminator and concentration estimator for diabetes monitoring in human breath

This study investigates the core of the development of an electronic nose envisioned for non invasive blood glucose monitoring. Tungsten trioxide (WO3), tin dioxide (SnO2) and zinc oxide (ZnO) homemade gas sensors have been exposed to various concentrations of acetone and ethanol in the presence of water vapor in order to create a dataset containing the changes in the resistance of the sensitive layer of sensors during the experiment. For the pattern recognition part of the system, this work reports the extraction of six features: two conventional steady-state features, two transient features and two features extracted from transform domain. The ReliefF algorithm is then used for the selection of the most efficient features. A classification method based on support vector machine (SVM) using a linear Kernel function is employed and to estimate the gas concentration of acetone and ethanol, the same training data in the classification step are used to create a prediction model based on least squares-SVM. A classification accuracy of 100% is achieved and the concentration of acetone and ethanol is estimated using a new method based on the combination of the best features of three sensors with a root mean square error of 0.2236 and 0.6639 respectively.

Effects of donor density on power-law response in tin dioxide gas sensors

We investigated the power-law responses in two types of tin dioxide (SnO2) films: one made from nanosized grains and another from from very large grains, both under dry air. Experimental results revealed a significant dependence between the sensitivity and the SnO2 grain size. We therefore propose, that the gas sensor sensitivity is not only determined by oxygen chemisorption, but also by changes in the density of oxygen vacancies in response to changes in the ambient gas pressure. Band bendings and adsorbate coverages for different oxygen pressures were derived resorting to the electroneutrality condition, including changes in the concentration of oxygen vacancies within the grains due to the exposure to different oxygen pressure. The consequences for the film conductivity and its power-law response were analyzed and compared with experimental results.

The Effect of Zeolite Composition and Grain Size on Gas Sensing Properties of SnO₂/Zeolite Sensor.

In order to improve the sensing properties of tin dioxide gas sensor, four kinds of different SiO2/Al2O3 ratio, different particle size of MFI type zeolites (ZSM-5) were coated on the SnO2 to prepared zeolite modified gas sensors, and the gas sensing properties were tested. The measurement results showed that the response values of ZSM-5 zeolite (SiO2/Al2O3 = 70, grain size 300 nm) coated SnO2 gas sensors to formaldehyde vapor were increased, and the response to acetone decreased compared with that of SnO2 gas sensor, indicating an improved selectivity property. The other three ZSM-5 zeolites with SiO2/Al2O3 70, 150 and 470, respectively, and grain sizes all around 1 μm coated SnO2 sensors did not show much difference with SnO2 sensor for the response properties to both formaldehyde and acetone. The sensing mechanism of ZSM-5 modified sensors was briefly analyzed.

The Method of the Sensitivity Comparison of the Tin Dioxide Gas Sensor in Periodic Steady State

The formulas for the time dependency of the electrical conductivity of the sensor in thermal periodic steady state in the clean air atmosphere were derived herein. The created model of the sensor was experimentally verified and enables to compare the sensitivity to the tested substance at the frequencies at which the tests were carried out. The experiments were carried out with the sensors MQR 1003, SP 11, and TGS813. The sensors were tested in the clean air atmosphere and subsequently in the presence of ethanol, acetone and toluene vapour in the air at three different frequencies.

Classification via an Embedded Approach

This paper presents the results of an automated volatile organic compound (VOC) classification process implemented by embedding a machine learning algorithm into an Arduino Uno board. An electronic nose prototype is constructed to detect VOCs from three different fruits. The electronic nose is constructed using an array of five tin dioxide (SnO2) gas sensors, an Arduino Uno board used as a data acquisition section, as well as an intelligent classification module by embedding an approach function which receives data signals from the electronic nose. For the intelligent classification module, a training algorithm is also implemented to create the base of a portable, automated, fast-response, and economical electronic nose device. This solution proposes a portable system to identify and classify VOCs without using a personal computer (PC). Results show an acceptable precision for the embedded approach in comparison with the performance of a toolbox used in a PC. This constitutes an embedded solution able to recognize VOCs in a reliable way to create application products for a wide variety of industries, which are able to classify data acquired by an electronic nose, as VOCs. With this proposed and implemented algorithm, a precision of 99% for classification was achieved into the embedded solution.

Antimony-Doped Tin Dioxide Gas Sensors Exhibiting High Stability in the Sensitivity to Humidity Changes

The type and amounts of oxygen adsorption species at various atmospheric humidity levels are important factors in improving the sensitivity to combustible gases and stability to humidity changes of SnO2-based resistive-type gas sensors. We investigated the effect of antimony (Sb) doping of SnO2 nanoparticles on the stability of the sensitivity to humidity changes and oxygen adsorption species under humid atmosphere. No significant degradation of the sensitivity to hydrogen of Sb-SnO2 sensors was observed between 16 and 96 RH%, while an undoped SnO2 sensor showed gradually decreasing responses with increasing humidity. An evaluation of oxygen adsorption species under humid atmosphere showed a transition from O2– to O– with increasing humidity from 16 to 96 RH%. However, the O2– adsorption sites were maintained on the surfaces of the Sb-SnO2, even as the humidity increased. Moreover, the extent of oxygen adsorption on the Sb-SnO2 was not obviously changed with increasing humidity. These results indicate tha...

A fuzzy inference system for the identification

Odor identification is an important area in a wide range of industries like cosmetics, food, beverages and medical diagnosis among others. Odor detection could be done through an array of gas sensors conformed as an electronic nose where a data acquisition module converts sensor signals to a standard output to be analyzed. To facilitate odors detection a system is required for the identification. This paper presents the results of an automated odor identification process implemented by a fuzzy system and an electronic nose. First, an electronic nose prototype is manufactured to detect organic compounds vapor using an array of five tin dioxide gas sensors, an arduino uno board is used as a data acquisition section. Second, an intelligent module with a fuzzy system is considered for the identification of the signals received by the electronic nose. This solution proposes a system to identify odors by using a personal computer. Results show an acceptable precision.

The Derivation of the Electrical Conductance/Temperature Dependency for Tin Dioxide Gas Sensor

The dependency between the electrical conductivity and the temperature of the tin dioxide layer at the constant concentration of the detected gas is derived here. The derived equation is modified as a function of two variables describing the dependence of the electrical conductivity of the sensor on both the temperature and the concentration. The derived formulas were verified by approximation of the measured data. These formulas can be useful in practical applications.

The Test of Organic Solvents Vapours Based on Commercial Tin Dioxide Gas Sensors

This article describes the experiments carried out with the system of three tin dioxide gas sensors MQR 1003, TGS 822 and TGS 813, as well as the achieved results. Vapours of five industrial organic solvents were tested. The measurement values were processed by a cluster analysis. The programmes STATGRAPHIC 5.0 Plus and MATLAB 7.11 were used for data processing. The achieved results show, that the used commercial sensors are able to successfuly distinguish chosen industrial solvents and the results can be used for discrimination of organic solvents vapours in air.

Gas Sensors Based on Tin Dioxide for Exhaust Gas Application, Modeling of Response for Pure Gases and for Mixtures

Abstract This paper concerns tin dioxide gas sensors for automotive exhaust gas application. It consists in elaborating robust sensors on alumina substrate by screen-printing technology. Sensors have been tested on a synthetic gas bench which is able to generate high gas velocity and gases at high temperatures close to real exhaust gas conditions. The responses of the sensors to three gases were modeled, and the classical model of electrical conductivity with one reducing or oxidizing pollutant gas was extended to mixtures. Comparisons between models and experiments are presented with good agreements.

Effect of micro-electrode geometry on NO 2 gas-sensing characteristics of one-dimensional tin dioxide nanostructure microsensors

Electrodes with micro-gaps are fabricated by using dc-sputtering and FIB techniques. SnO 2 nanowires are deposited on the micro-gap (1–30 μm) by suspension dropping method to fabricate a micro-gas sensor. The sensing ability of various SnO 2 micro-gap sensors is measured. A comparison between sensors reveals that the short-gap electrode has numerous advantages in terms of reliability, high sensitivity and detection of low concentrations of NO 2, while the large-gap electrode is relatively sensitive for high concentrations. Conductance measurements are carried out at different surface temperatures and NO 2 concentrations in order to investigate the effects that the gap size has on the overall sensor conductance. The results suggest that the interface between the electrode and sensitive layer has a very important role for the sensing mechanism of tin dioxide gas sensors.

Resistive and surface ionisation response of SnO 2 gas sensing layers

Gas detection experiments have been performed with tin dioxide (SnO 2) gas sensors specifically configured to observe surface ion emission (SI) in addition to the more familiar resistive (R) response. We show that both kinds of gas response can be observed on one and the same kind of metal oxide material, however, within largely different surface temperature ranges. Whereas the R response shows the widely observed broad-range sensitivity towards different analyte gases, the SI response is largely restricted towards hydrocarbons with low ionisation energy and a concomitantly large proton affinity. Operating the SnO 2 sensor in a range of temperatures where both a R and SI response can be observed, highly odorous and toxic amines could be safely distinguished from less reactive but combustible gases such as H 2, C 2H 4, and CO. Reasons for the much higher selectivity of the SI gas response are discussed.

Odour classification system for continuous monitoring applications

In this paper, we investigate the classification performance of an electronic nose system, based on tin dioxide gas sensors. In contrast to previous studies, the electronic nose is mounted on a mobile platform and samples are analyzed using only transient information in the signals. The motivation behind this work is to explore the feasibility of using electronic nose devices for odour classification in a number of future application domains which require fast and possibly real-time odour identification. To perform transient based analysis of the signals, a comparative study of different methods for feature extraction was performed. Additionally, the application of a relevance vector machine classifier is explored to further analyze the classification performance based on quality of the obtained samples. The results presented in this study can be used for the development of electronic nose devices particularly suitable for environmental monitoring applications.

Effects of electron beam irradiation on tin dioxide gas sensors

In this paper, the effects of electron beam irradiation on the gas sensing performance of tin dioxide thin films toward H2 are studied. The tin dioxide thin films were prepared by ultrasonic spray pyrolysis. The results show that the sensitivity increased after electron beam irradiation. The electron beam irradiation effects on tin dioxide thin films were simulated and the mechanism was discussed.

Micromachined sol–gel carbon nanotube/SnO2 nanocomposite hydrogen sensor

A novel micromachined single wall carbon nanotube (SWCNT) reinforced nanocrystalline tin dioxide gas sensor has been developed. The presence of SWCNT in SnO 2 matrix was realized by a spin-on sol–gel process. The SWCNT/SnO 2 sensor's sensitivity for hydrogen detection has greatly increased by a factor of three, in comparison to that of pure SnO 2 sensor. The novel sensor also lowers the working temperature, response time and recovery time. The greatly improved performances are mainly attributed to the effective gas accessing nano passes through SWCNT plus the smaller distance between adjacent gas accessing boundaries formed by the distribution of tiny SWCNTs. Therefore, both the spatial requirement ( D ≤ 2 L , D is the distance between adjacent gas accessing boundaries and L is the space charge layer thickness) and surficial requirement (adequate gas activation area) are met and the maximum inherent sensitivity of SnO 2 is achieved.

Formation of orthorhombic tin dioxide from mechanically milled monoxide powders

X-ray scattering measurements are used to show that the metastable orthorhombic phase of tin dioxide is produced by the oxidation of mechanically milled litharge-phase tin monoxide. After milling to a grain size of approximately 20nm, followed by heating to 575°C, the fraction of the orthorhombic phase is approximately 80%. The orthorhombic phase was originally observed in high-pressure experiments, but more recently, it has been produced in a wide variety of thin-film and nanoparticle samples. The data presented here demonstrate the importance of small-grain-size tin monoxide as a precursor in the ambient-pressure synthesis of the orthorhombic phase. This result has practical importance in the production of tin dioxide gas sensors. A more fundamental observation is that the particle size of a precursor phase can have a marked effect on subsequent phases produced during oxidation. Lastly, a formula for determining the orthorhombic fraction in two-phase tin dioxide samples is developed using the method of standard additions.

New approach for the detection of organophosphorus pesticide in cabbage using SPME/SnO 2 gas sensor: principle and preliminary experiment

A new approach for fast detection of organophosphorus pesticide like dichlorvos in cabbage using solid phase microextraction (SPME) coupled with tin dioxide gas sensor was investigated. In comparison the experiments of guide sample of dichlorvos, this method which employed only one SnO 2 gas sensor rather than an array of sensors in a rectangular temperature mode could perform the qualitative analysis. The quantitative analysis was performed using polar plots and peak area.

New approach for the detection of organophosphorus pesticide in cabbage using SPME/SnO2 gas sensor: principle and preliminary experiment

A new approach for fast detection of organophosphorus pesticide like dichlorvos in cabbage using solid phase microextraction (SPME) coupled with tin dioxide gas sensor was investigated. In comparison the experiments of guide sample of dichlorvos, this method which employed only one SnO2 gas sensor rather than an array of sensors in a rectangular temperature mode could perform the qualitative analysis. The quantitative analysis was performed using polar plots and peak area.