• Journal of Sensor Science and Technology
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• v.22 no.2
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• pp.162-173
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• 2013

The purpose of this paper is to classify VOC gases by emulating the characteristics found in biological olfaction. For this purpose, we propose new signal processing method based a polymeric chemical sensor array consisting of 4096 sensors which is created by NEUROCHEM project. To remove unstable sensors generated in the manufacturing process of very large scaled chemical sensor array, we used discrete wavelet transformation and cosine similarity. And, to remove the supernumerary redundancy, we proposed the method of selecting candidates of representative sensor representing sensors with similar features by Fuzzy c-means algorithm. In addition, we proposed an improved algorithm for selecting representative sensors among candidates of representative sensors to better enhance classification ability. However, Classification for very large scaled sensor array has a great deal of time in process of learning because many sensors are used for learning though a redundancy is removed. Throughout experimental trials for classification, we confirmed the proposed method have an outstanding classification ability, at transient state as well as steady state.

• Korean Journal of Materials Research
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• v.22 no.11
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• pp.609-614
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• 2012

We report on the NO gas sensing properties of non-directional ZnO nanofibers synthesized using a typical electrospinning technique. These non-directional ZnO nanofibers were electrospun on an $SiO_2$/Si substrate from a solution containing poly vinyl alcohol (PVA) and zinc nitrate hexahydrate dissolved in distilled water. Calcination processing of the ZnO/PVA composite nanofibers resulted in a random network of polycrystalline ZnO nanofibers of 50 nm to 100 nm in diameter. The diameter of the nanofibers was found to depend primarily on the solution viscosity; a proper viscosity was maintained by adding PVA to fabricate uniform ZnO nanofibers. Microstructural measurements using scanning electron microscopy revealed that our synthesized ZnO nanofibers after calcination had coarser surface morphology than those before calcination, indicating that the calcination processing was sufficient to remove organic contents. From the gas sensing response measurements for various NO gas concentrations in dry air at several working temperatures, it was found that gas sensors based on electrospun ZnO nanofibers showed quite good responses, exhibiting a maximum sensitivity to NO gas in dry air at an operating temperature of $200^{\circ}C$. In particular, the non-directional electrospun ZnO nanofiber gas sensors were found to have a good NO gas detection limit of sub-ppm levels in dry air. These results illustrate that non-directional electrospun ZnO nanofibers are promising for use in low-cost, high-performance practical NO gas sensors.

• Korean Journal of Materials Research
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• v.34 no.5
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• pp.235-241
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• 2024

Gas identification techniques using pattern recognition methods were developed from four micro-electronic gas sensors for noxious gas mixture analysis. The target gases for the air quality monitoring inside vehicles were two exhaust gases, carbon monoxide (CO) and nitrogen oxides (NO_x), and two odor gases, ammonia (NH₃) and formaldehyde (HCHO). Four MEMS gas sensors with sensing materials of Pd-SnO₂ for CO, In₂O₃ for NO_X, Ru-WO₃ for NH₃, and hybridized SnO₂-ZnO material for HCHO were fabricated. In six binary mixed gas systems with oxidizing and reducing gases, the gas sensing behaviors and the sensor responses of these methods were examined for the discrimination of gas species. The gas sensitivity data was extracted and their patterns were determined using principal component analysis (PCA) techniques. The PCA plot results showed good separation among the mixed gas systems, suggesting that the gas mixture tests for noxious gases and their mixtures could be well classified and discriminated changes.

• Journal of Sensor Science and Technology
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• v.30 no.1
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• pp.1-9
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• 2021

This mini review summarizes some of the recent advances in machine-learning (ML)-driven chemical and biological sensors. Specific focus is on field-effect-transistor (FET)-based sensors with a description of their structures and detection mechanisms. Key ML techniques are briefly reviewed for an audience not familiar with the basic principles. We mainly discuss two aspects: (1) data analysis based on ML and (2) ML applied to sensor design. In conclusion, the challenges and opportunities for the advancement of ML-based sensors are briefly considered.

• Journal of Biosystems Engineering
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• v.33 no.5
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• pp.333-339
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• 2008

The purpose of this study was to develop a portable electronic nose system to measure volatile components of agricultural and food products. Also, a graphical operating software to control the electronic nose system and to acquire signals through the Internet was developed. An array of five commercial metal oxide gas sensors was used to detect various volatile gas components of target samples. Transient and steady state signals were analyzed to extract variables related to sample states, To find optimal operating conditions of the system, several experiments were performed with different gas chambers, vacuum pumps, gas sampling temperatures, and sample container sizes. The patterns of gas sensor signals were analysed to find effects of the various conditions.

• Bulletin of the Korean Chemical Society
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• v.32 no.10
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• pp.3735-3737
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• 2011

We report a simple method for fabricating ZnO gas sensors via a sonochemical route and their $H_2$ gas sensing properties. Vertically aligned ZnO nanorod arrays as a sensing material were synthesized on a Pt-electrode patterned alumina substrate under ambient conditions. The advantage of the proposed method is a high speed of processing. The gas sensor based on ZnO nanorod arrays with large specific surface area showed a high response to $H_2$ and a detection limit of 70 ppm at $250^{\circ}C$. Also, their response and recovery time were relatively short and a complete regeneration was observed. A mechanism for sensing $H_2$ gas on the surface of ZnO nanorods is proposed.

• Journal of Sensor Science and Technology
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• v.29 no.3
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• pp.211-214
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• 2020

Chlorine dioxide is very effective gas for sterilization or disinfection (in manufacturing), and does not produce harmful by-products after use. However, if its concentration exceeds 10 %, it become explosive and cannot be compressed or stored. Therefore, it is necessary to measure its concentration. In this study, the concentration of chlorine dioxide with a high oxidizing strength was measured using a metal oxide sensor. The sensor was a commercially available TGS series from Figaro. The sensitivity of the sensor was inversely proportional to a low concentration of chlorine dioxide gas below 6 ppm and returned to the initial resistance at about 6 ppm. When the gas concentration reached multiples of 10 ppm, resistance of the sensor increased to several megaohms.

• Korean Journal of Metals and Materials
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• v.49 no.4
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• pp.304-312
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• 2011

In this study, MOSFET type micro hydrogen gas sensors with platinum catalytic metal gates were designed, fabricated, and their electrical characteristics were analyzed. The devised MOSFET Hydrogen Sensors, called MHS-1 and -2, were designed with a platinum gate for hydrogen gas adsorption, and an additional sensing part for higher gas sensitivity and with a micro heater for operation temperature control. In the electrical characterization of the fabricated Pt-gate MOSFET (MHS-1), the saturated drain current was 3.07 mA at 3.0 V of gate voltage, which value in calculation was most similar to measurement data. The amount of threshold voltage shift and saturated drain current increase to variation of hydrogen gas concentration were calculated and the hydrogen gas sensing properties were anticipated and analyzed.

• Journal of the Korean Institute of Telematics and Electronics
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• v.23 no.6
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• pp.766-772
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• 1986

SnO2/Pt CO gas sensors operating at relatively low temperature were fabricated, and their performance characteristics were measured. When the mixing weight ratio of SnO2/Pt was 99.5/0.5, a good sensitivity to CO gas was obtained. And the experimental results were in consistent with the gas sensing model. The optimum operating, temperature range of the fabricated devices was 50-80\ulcorner and the response time was 15 sec. at 80\ulcorner in 1000 ppm CO ambient. The humidity dependence of sensitibity to CO gas could be reduced by adding hydrophokbic silica to the mixture of SnO2 and Pt. For the practical application of the fabricated devices, a CO gas alarming system has been developed.

• Korean Journal of Materials Research
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• v.26 no.12
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• pp.741-750
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• 2016

Nanofibers(NFs), because of their high surface area and nanosized grains, have appropriate morphologies for use in chemiresistive-type sensors for gas detection applications. In this study, a highly sensitive and selective CO gas sensing material based on Au-decorated $SnO_2$ NFs was fabricated by electrospinning. $SnO_2$ NFs were synthesized by electrospinning and subsequently decorated with various amounts of Au nanoparticles(NPs) by sputtering; this was followed by thermal annealing. Different characterizations showed the successful formation of Au-decorated $SnO_2$ NFs. Gas sensing tests were performed on the fabricated sensors, which showed bell-shaped sensing behavior with respect to the amount of Au decoration. The best CO sensing performance, with a response of ~20 for 10 ppm CO, was obtained at an optimized amount of Au (2.6 at.%). The interplay between Au and $SnO_2$ in terms of the electronic and chemical sensitization by Au NPs is responsible for the great improvement in the CO sensing capability of pure $SnO_2$ NFs, suggesting that Au-decorated $SnO_2$ NFs can be a promising material for fabricating highly sensitive and selective chemiresistive-type CO gas sensors.