A reusable smart interface for gas sensor resistance measurement

The advances of the semiconductor industry enable microelectromechanical systems sensors, signal conditioning logic and network access to be integrated into a smart sensor node. In this framework, a mixed-mode interface circuit for monolithically integrated gas sensor arrays was developed with high-level design techniques. This interface system includes analog electronics for inspection of up to four sensor arrays and digital logic for smart control and data communication. Although different design methodologies were used in the conception of the complete circuit, high-level synthesis tools and methodologies were crucial in speeding up the whole design cycle, enhancing reusability for future applications and producing a flexible and robust component.

On-line event detection by recursive dynamic principal component analysis and gas sensor arrays under drift conditions

Leakage detection is an important issue in many chemical sensing applications. Leakage detection hy thresholds suffers from important drawbacks when sensors have serious drifts or they are affected by cross-sensitivities. Here we present an adaptive method based in a Dynamic Principal Component Analysis that models the relationships between the sensors in the may. In normal conditions a certain variance distribution characterizes sensor signals. However, in the presence of a new source of variance the PCA decomposition changes drastically. In order to prevent the influence of sensor drifts the model is adaptive and it is calculated in a recursive manner with minimum computational effort. The behavior of this technique is studied with synthetic signals and with real signals arising by oil vapor leakages in an air compressor. Results clearly demonstrate the efficiency of the proposed method.

Drift compensation of gas sensor array data by Orthogonal Signal Correction

Drift is an important issue that impairs the reliability of gas sensing systems. Sensor aging, memory effects and environmental disturbances produce shifts in sensor responses that make initial statistical models for gas or odor recognition useless after a relatively short period (typically few weeks). Frequent recalibrations are needed to preserve system accuracy. However, when recalibrations involve numerous samples they become expensive and laborious. An interesting and lower cost alternative is drift counteraction by signal processing techniques. Orthogonal Signal Correction (OSC) is proposed for drift compensation in chemical sensor arrays. The performance of OSC is also compared with Component Correction (CC). A simple classification algorithm has been employed for assessing the performance of the algorithms on a dataset composed by measurements of three analytes using an array of seventeen conductive polymer gas sensors over a ten month period.

Drift compensation of gas sensor array data by common principal component analysis

A new drift compensation method based on Common Principal Component Analysis (CPCA) is proposed. The drift variance in data is found as the principal components computed by CPCA. This method finds components that are common for all gasses in feature space. The method is compared in classification task with respect to the other approaches published where the drift direction is estimated through a Principal Component Analysis (PCA) of a reference gas. The proposed new method ¿ employing no specific reference gas, but information from all gases ¿has shown the same performance as the traditional approach with the best-fitted reference gas. Results are shown with data lasting 7-months including three gases at different concentrations for an array of 17 polymeric sensors.

SiC-Based MIS gas sensor for high water vapor environments

In this work we will prove that SiC-based MIS capacitors can work in environments with extremely high concentrations of water vapor and still be sensitive to hydrogen, CO and hydrocarbons, making these devices suitable for monitoring the exhaust gases of hydrogen or hydrocarbons based fuel cells. Under the harshest conditions (45% of water vapor by volume ratio to nitrogen), Pt/TaOx/SiO2/SiC MIS capacitors are able to detect the presence of 1 ppm of hydrogen, 2 ppm of CO, 100 ppm of ethane or 20 ppm of ethene, concentrations that are far below the legal permissible exposure limits.

Gas identification with tin oxide sensor array and self-organizing maps: adaptive correction of sensor drifts

Low-cost tin oxide gas sensors are inherently nonspecific. In addition, they have several undesirable characteristics such as slow response, nonlinearities, and long-term drifts. This paper shows that the combination of a gas-sensor array together with self-organizing maps (SOM's) permit success in gas classification problems. The system is able to determine the gas present in an atmosphere with error rates lower than 3%. Correction of the sensor's drift with an adaptive SOM has also been investigated

Nanosized Nb-TiO2 gas sensors derived from alkoxides hydrolization

Nanocrystalline TiO2 modified with Nb has been produced through the sol-gel technique. Nanopowders have been obtained by means of the hydrolysis of pure alkoxides with deionized water and peptization of the resulting hydrolysate with diluted acid nitric at 100 C. The addition of Nb stabilizes the anatase phase to higher temperatures. XRD spectra of the undoped and the Nb-doped samples show that the undoped sample has been almost totally converted to rutile at 600 C, meanwhile the doped samples present still a low percentage of rutile phase. Nanocrystalline powders stabilized at 600 C with grain sizes of about 17 nm have successfully been synthesized by the addition of Nb with a concentration of 2% at., which appears to be an adequate additive concentration to improve the gas sensor performances, such as it is suggested by the catalytic conversion efficiency experiments performed from FTIR measurements. FTIR absorbance spectra show that catalytic conversion of CO occurs at lower temperatures when niobium is introduced. The electrical response of the films to different concentrations of CO and ethanol has been monitored in dry and wet environments in order to test the influence of humidity in the sensor response. The addition of Nb decreases the working temperature and increases the stability of the layers. Also, large enhancement of the response time is obtained even with lower working temperatures. Moreover, humidity effects on the gas sensor response toward CO and ethanol are less important in Nb-doped samples than in the undoped ones.

Nanosized Nb-TiO2 gas sensors derived from alkoxides hydrolization

Nanocrystalline TiO2 modified with Nb has been produced through the sol-gel technique. Nanopowders have been obtained by means of the hydrolysis of pure alkoxides with deionized water and peptization of the resulting hydrolysate with diluted acid nitric at 100 C. The addition of Nb stabilizes the anatase phase to higher temperatures. XRD spectra of the undoped and the Nb-doped samples show that the undoped sample has been almost totally converted to rutile at 600 C, meanwhile the doped samples present still a low percentage of rutile phase. Nanocrystalline powders stabilized at 600 C with grain sizes of about 17 nm have successfully been synthesized by the addition of Nb with a concentration of 2% at., which appears to be an adequate additive concentration to improve the gas sensor performances, such as it is suggested by the catalytic conversion efficiency experiments performed from FTIR measurements. FTIR absorbance spectra show that catalytic conversion of CO occurs at lower temperatures when niobium is introduced. The electrical response of the films to different concentrations of CO and ethanol has been monitored in dry and wet environments in order to test the influence of humidity in the sensor response. The addition of Nb decreases the working temperature and increases the stability of the layers. Also, large enhancement of the response time is obtained even with lower working temperatures. Moreover, humidity effects on the gas sensor response toward CO and ethanol are less important in Nb-doped samples than in the undoped ones.

Gas sensing properties of catalytically modified WO3 with copper and vanadium for NH3 detection

Ammonia gas detection by pure and catalytically modified WO3 based gas sensor was analysed. The sensor response of pure WO3 to NH3 was not only rather low but also presented an abnormal behaviour, probably due to the unselective oxidation of ammonia to NOx. Copper and vanadium were introduced in different concentrations and the resulting material was annealed at different temperatures in order to improve the sensing properties for NH3 detection. The introduction of copper and vanadium as catalytic additives improved the response to NH3 and also eliminated the abnormal behaviour. Possible mechanisms of NH3 reaction over these materials are discussed. Sensor responses to other gases like NO2 or CO and the interference of humidity on ammonia detection were also analysed so as to choose the best sensing element.

Nanocrystalline SnO2 by liquid pyrolisis

Liquid pyrolysis is presented as a new production method of SnO2 nanocrystalline powders suitable for gas sensor devices. The method is based on a pyrolytic reaction of high tensioned stressed drops of an organic solution of SnCl4·5(H2O). The main advantages of the method are its capability to produce SnO2 nanopowders with high stability, its accurate control over the grain size and other structural characteristics, its high level of repeatability and its low industrialization implementation cost. The characterization of samples of SnO2 nanoparticles obtained by liquid pyrolysis in the range between 200ºC and 900ºC processing temperature is carried out by X-ray diffraction, transmission electron microscopy, Raman and X-ray photoelectron spectroscopy. Results are analyzed and discussed so as to validate the advantages of the liquid pyrolysis method.

Nonlinear inverse dynamic models of gas sensing systems based on chemical sensor arrays for quantitative measurements

Gas sensing systems based on low-cost chemical sensor arrays are gaining interest for the analysis of multicomponent gas mixtures. These sensors show different problems, e.g., nonlinearities and slow time-response, which can be partially solved by digital signal processing. Our approach is based on building a nonlinear inverse dynamic system. Results for different identification techniques, including artificial neural networks and Wiener series, are compared in terms of measurement accuracy.

Structural and gas-sensing properties of WO3 nanocrystalline powders obtained by a sol-gel method from tungstic acid

WO3 nanocrystalline powders were obtained from tungstic acid following a sol-gel process. Evolution of structural properties with annealing temperature was studied by X-ray diffraction and Raman spectroscopy. These structural properties were compared with those of WO3 nanopowders obtained by the most common process of pyrolysis of ammonium paratungstate, usually used in gas sensors applications. Sol-gel WO3 showed a high sensor response to NO2 and low response to CO and CH4. The response of these sensor devices was compared with that of WO3 obtained from pyrolysis, showing the latter a worse sensor response to NO2. Influence of operating temperature, humidity, and film thickness on NO2 detection was studied in order to improve the sensing conditions to this gas.

Gas-sensing properties of sprayed films of (CdO)x(ZnO)1-x mixed oxide

A novel NO2 sensor based on (CdO)x(ZnO)1-x mixed-oxide thin films deposited by the spray pyrolysis technique is developed. The sensor response to 3-ppm NO2 is studied in the range 50°C-350°C for three different film compositions. The device is also tested for other harmful gases, such as CO (300 ppm) and CH4 (3000 ppm). The sensor response to these reducing gases is different at different temperatures varying from the response typical for the p-type semiconductor to that typical for the n-type semiconductor. Satisfactory response to NO2 and dynamic behavior at 230°C, as well as low resistivity, are observed for the mixed-oxide film with 30% Cd. The response to interfering gas is poor at working temperature (230°C). On the basis of this study, a possible sensing mechanism is proposed.

Composition of Greenhouse Gas Emissions in Spain: an Input-Output Analysis

Extending the traditional input-output model to account for the environmental impacts of production processes reveals the channels by which environmental burdens are transmitted throughout the economy. In particular, the environmental input-output approach is a useful technique for quantifying the changes in the levels of greenhouse emissions caused by changes in the final demand for production activities. The inputoutput model can also be used to determine the changes in the relative composition of greenhouse gas emissions due to exogenous inflows. In this paper we describe a method for evaluating how the exogenous changes in sectorial demand, such as changes in private consumption, public consumption, investment and exports, affect the relative contribution of the six major greenhouse gases regulated by the Kyoto Protocol to total greenhouse emissions. The empirical application is for Spain, and the economic and environmental data are for the year 2000. Our results show that there are significant differences in the effects of different sectors on the composition of greenhouse emissions. Therefore, the final impact on the relative contribution of pollutants will basically depend on the activity that receives the exogenous shock in final demand, because there are considerable differences in the way, and the extent to which, individual activities affect the relative composition of greenhouse gas emissions. Keywords: Greenhouse emissions, composition of emissions, sectorial demand, exogenous shock.

Trade of permits for greenhouse gas emissions; bilateral trade need not be the answer

The Kyoto Protocol sets national quotas on CO2 emissions and allows international trade of these quotas. We argue that this trade is characterized by asymmetric, identity-dependent externalities, and show that bilateral trade may not be sufficient for an efficient allocation of emissions. We derive conditions under which bilateral trade does improve the allocation of permits. The conditions are strong. In this sense, we argue that, for emissions permits, market design matters.