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The effects of the SnO2 pore size and metal oxide promoters on the sensing properties of SnO2-based thick film gas sensors were investigated to improve the detection of very low H2S concentrations (<1 ppm). SnO2 sensors and SnO2-based thick-film gas sensors promoted with NiO, ZnO, MoO3, CuO or Fe2O3 were prepared, and their sensing properties were examined in a flow system. The SnO2 materials were prepared by calcining SnO2 at 600, 800, 1,000 and 1,200 °C to give materials identified as SnO2(600), SnO2(800), SnO2(1000), and SnO2(1200), respectively. The Sn(12)Mo5Ni3 sensor, which was prepared by physically mixing 5 wt% MoO3 (Mo5), 3 wt% NiO (Ni3) and SnO2(1200) with a large pore size of 312 nm, exhibited a high sensor response of approximately 75% for the detection of 1 ppm H2S at 350 °C with excellent recovery properties. Unlike the SnO2 sensors, its response was maintained during multiple cycles without deactivation. This was attributed to the promoter effect of MoO3. In particular, the Sn(12)Mo5Ni3 sensor developed in this study showed twice the response of the Sn(6)Mo5Ni3 sensor, which was prepared by SnO2(600) with the smaller pore size than SnO2(1200). The excellent sensor response and recovery properties of Sn(12)Mo5Ni3 are believed to be due to the combined promoter effects of MoO3 and NiO and the diffusion effect of H2S as a result of the large pore size of SnO2. [ABSTRACT FROM AUTHOR]

The sensing behavior of SnO2-based thick film gas sensors in a flow system in the presence of a very low concentration (ppb level) of chemical agent simulants such as acetonitrile, dipropylene glycol methyl ether (DPGME), dimethyl methylphosphonate (DMMP), and dichloromethane (DCM) was investigated. Commercial SnO2 [SnO2(C)] and nano-SnO2 prepared by the precipitation method [SnO2(P)] were used to prepare the SnO2 sensor in this study. In the case of DCM and acetonitrile, the SnO2(P) sensor showed higher sensor response as compared with the SnO2(C) sensors. In the case of DMMP and DPGME, however, the SnO2(C) sensor showed higher responses than those of the SnO2(P) sensors. In particular, the response of the SnO2(P) sensor increased as the calcination temperature increased from 400 °C to 800 °C. These results can be explained by the fact that the response of the SnO2-based gas sensor depends on the textural properties of tin oxide and the molecular size of the chemical agent simulant in the detection of the simulant gases (0.1-0.5 ppm). [ABSTRACT FROM AUTHOR]

A nanofibrous sensor for ammonia gas is fabricated by electrospinning the composite of poly(diphenylamine) (PDPA) with poly(methyl methacrylate) (PMMA) onto the patterned interdigit electrode. The composite electrospun membrane shows interconnected fibrous morphology. Functional groups in PDPA and the high active surface area of the fibrous membrane make the device detect a lower concentration of ammonia with a good reproducibility. The sensing capability of the device is studied by monitoring the changes in resistance of the membrane with different concentrations of ammonia. The changes in resistance of the membrane shows linearity with the concentration of ammonia in the limit of 10 and 300 ppm. UV-visible spectroscopy reveals the mechanism of sensing ammonia by the membrane. [ABSTRACT FROM PUBLISHER]

A micro gas sensor array, consisting of four porous tin oxide thin films added with noble metal catalysts on a micro-hotplate, was designed and fabricated. The micro-hotplate was designed to obtain a uniform thermal distribution along with a low-power consumption and fast thermal response. The sensing properties of the sensors toward certain combustible gases, i.e., propane, butane, LPG, and carbon monoxide, were evaluated. A multilayer neural network was then used to classify the gas species. The results demonstrated that the proposed micro sensor array, plus multilayer neural network employing a backpropagation learning algorithm, was very effective in recognizing specific kinds and concentration levels of combustible gas below their respective threshold limit values. [ABSTRACT FROM PUBLISHER]

A gas-sensing array with ten different SnO2 sensors was fabricated on a substrate for the purpose of recognizing various kinds and quantities of indoor combustible gas leakages, such as methane, propane, butane, LPG, and carbon monoxide, within their respective threshold limit value (TLV) and lower explosion limit (LEL) range. Nano-sized sensing materials with high surface areas were prepared by coprecipitating SnCl4 with Ca and Pt, while the sensing patterns of the SnO2-based sensors were differentiated by utilizing different additives. The sensors in the sensor array were designed to produce a uniform thermal distribution along with a high and differentiated sensitivity and reproducibility for low concentrations below 100 ppm. Using the sensing signals of the array, an electronic nose system was then applied to classify and identify simple/mixed explosive gas leakages. A gas pattern recognizer was implemented using a neuro-fuzzy network and multi-layer neural network, including an error-back-propagation learning algorithm. Simulation and experimental results confirmed that the proposed gas recognition system was effective in identifying explosive and hazardous gas leakages. The electronic nose in conjunction with a neuro-fuzzy network was also implemented using a digital signal processor (DSP). [ABSTRACT FROM PUBLISHER]

Explains that a sol-gel technique for indium oxide (In2O3) thin film has been developed and applied to produce high porous and high ozone sensitive films. Indium chloride tetrahydrate was dissolved in 40 milliliter butanol; In2O3 precursor solution for In2O3 thin film; Polyvinyl alcohol binder was added to the solution before coating to improve the adhesiveness between the In2O3 film and alumina substrate.