• Korean Journal of Metals and Materials
• /
• v.48 no.2
• /
• pp.169-174
• /
• 2010

A micro gas sensor for formaldehyde (HCHO) gas was fabricated by using MEMS (Micro Electro Mechanical System) technology and the sol-gel process. The sensing materials of the $SnO_2$-ZnO system were synthesized by the sol-gel method. The crystal structure and thermal analysis of the $SnO_{2}$-ZnO were characterized by XRD and DSC-TGA. The fabricated gas sensors were tested at various gas concentrations (0.5~5.0 ppm) and different operation temperatures ($350{\sim}550^{\circ}C$). The $SnO_2$-10 mol%ZnO sensor showed the highest sensitivity ($R_s=0.24$) for 1.0 ppm-formaldehyde at $500^{\circ}C$ and response time (90% saturation time) was within 20 seconds.

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

• Proceedings of the KWS Conference
• /
• 2005.06a
• /
• pp.106-108
• /
• 2005

The instrumented fuel irradiation test at a research reactor is needed to evaluate the performance of the developed nuclear fuel. The fuel elements can be designed to measure the center line temperature of fuel pellets during the irradiation test by using temperature sensor. The thermal sensor was composed of thermocouple and sensor sheath. Micro-laser welding technology was adopted to seal between seal tube and sensor sheath with thickness of 0.15 mm. The soundness of welding area has to be confirmed to prevent fission gas of the fuel from leaking out of the element during the fuel irradiation test. In this study, fundamental data for micro-laser welding technology was proposed to seal temperature sensor sheath of the instrumented fuel element. And, micro-laser welding for dissimilar metals between sensor sheath and seal tube was characterized by investigating welding conditions. Moreover, the micro-laser welding technology is closely related to advanced industry. It is expected that the laser material processing technology will be adopted to various a pplications in the industry.

• Journal of Sensor Science and Technology
• /
• v.19 no.6
• /
• pp.462-468
• /
• 2010

A low power gas sensor with microheater was fabricated by MEMS technology. In order to heat up the gas sensing material to a operating temperature, a platinum(Pt) micro heater was built on to the micromachined Si substrate. The width and gap of microheater were $20\;{\mu}m$ and $4.5\;{\mu}m$, respectively. ZnO nanowhisker arrays were fabricated on a sensor device by hydrothermal method. The sensor device was deposited with ZnO seeds using PLD systems. A 200 ml aqueous solution of 0.1 mol zinc nitrate hexahydrate, 0.1 mol hexamethylenetetramine, and 0.02 mol polyethylenimine was used for growthing ZnO nanowhiskers. The power consumption to heat up the gas sensor to a operating temperature was measured and temperature distribution of sensor was analyzed by a Infrared Thermal Camera. The optimum temperature for highest sensitivity was found to be $250^{\circ}C$ although relatively high(64 %) sensitivity was obtained even at as low as $150^{\circ}C$. The power consumption was 72 mW at $250^{\circ}C$ and was only 25 mW at $150^{\circ}C$.

• Journal of Sensor Science and Technology
• /
• v.20 no.5
• /
• pp.311-316
• /
• 2011

Monitoring the carbon dioxide concentration in arterial blood is vital for the evaluation and prevention of pulmonary disease. Yet, domestic pure arterial blood carbon dioxide sensor technologies are not being developed, instead all sensors are imported. In this paper, we develop a real time monitoring system for arterial blood partial pressure of carbon dioxide($pCO_2$) gas from the wrist by using a carbon micro-heater. The micro-heater was fabricated with a thickness of 0.3 ${\mu}m$ in order to collect the carbon dioxide under the skin. The micro-heater has been designed to perform temperature compensation in order to prevent damage to the skin. Two clinical trials of the system were undertaken. As a result, we demonstrated that a portable, transcutaneous carbon dioxide analysis($TcpCO_2$) device produced domestically is possible. In addition, this system reduced the analysis time significantly. Carbon films could reduce the unit price of these sensors by replacing the gold film used in foreign models. Also, we developed a real time monitoring system which can be used with optical biosensors for medical diagnostics as well as gas sensors for environmental monitoring.

• KSII Transactions on Internet and Information Systems (TIIS)
• /
• v.11 no.2
• /
• pp.1005-1018
• /
• 2017

This paper proposes an App Visualization (AppV) based on IoT Self-diagnosis Micro Control Unit (ISMCU) for accident prevention. It collects a current status of a vehicle through a sensor, visualizes it on a smart phone and prevents vehicles from accident. The AppV consists of 5 components. First, a Sensor Layer (SL) judges noxious gas from a current vehicle and a driver's driving habit by collecting data from various sensors such as an Accelerator Position Sensor, an O2 sensor, an Oil Pressure Sensor, etc. and computing the concentration of the CO collected by a semiconductor gas sensor. Second, a Wireless Sensor Communication Layer (WSCL) supports Zigbee, Wi-Fi, and Bluetooth protocol so that it may transfer the sensor data collected in the SL to ISMCU and the data in the ISMCU to a Mobile. Third, an ISMCU integrates the transferred sensor information and transfers the integrated result to a Mobile. Fourth, a Mobile App Block Programming Tool (MABPT) is an independent App generation tool that changes to visual data just the vehicle information which drivers want from a smart phone. Fifth, an Embedded Module (EM) records the data collected through a Smart Phone real time in a Cloud Server. Therefore, because the AppV checks a vehicle' fault and bad driving habits that are not known from sensors and performs self-diagnosis through a mobile, it can reduce time and cost spending on accidents caused by a vehicle's fault and noxious gas emitted to the outside.

• Proceedings of the KAIS Fall Conference
• /
• 2006.05a
• /
• pp.223-226
• /
• 2006

The micro-gas sensor based on carbon nanotubes (CNTs) was fabricated and its gas sensing characteristics on nitrogen dioxide ($NO_2$) have been investigated. The sensor consists of a heater, an insulating layer, a pair of contact electrodes, and CNT-sensing film on a micromachined diaphragm. The heater plays a role in the temperature change to modify sensor operation. Gas sensor responses of CNT-film to $NO_2$ at room temperature are reported. The sensor exhibits a reversible response with a time constant of a few minutes at thermal treatment temperature of $130^{\circ}C$.

• Journal of Sensor Science and Technology
• /
• v.24 no.5
• /
• pp.281-286
• /
• 2015

The importance of air quality monitoring is rapidly increasing. Even though state-of-the-art air quality monitoring technologies such as mass spectrometry, gas chromatography, and optical measurement enable high-fidelity measurement of air pollutants, they cannot be widely used for portable or personalized platforms because of their high cost and complexity. Recently, personalized and localized environmental monitoring, rather than global and averaged environmental monitoring, has drawn greater attention with the advancement of mobile telecommunication technologies. Here, micro- and nano-technologies enable highly integrated and ultra-compact sensors to meet the needs of personalized environmental monitoring. In this paper, several examples of MEMS-based gas sensors for compact and personalized air quality monitoring are explained. Additionally, the principles and usage of functional nanomaterials are discussed for highly sensitive and selective gas sensors.

• Journal of Sensor Science and Technology
• /
• v.21 no.6
• /
• pp.402-407
• /
• 2012

We report a Fabry-Perot interferometer (FPI)-based multi-channel micro-spectrometer used for multi-gas measurement in the spectral range of $3-5{\mu}m$ and its gas sensing performance. The fabricated infrared (IR) spectrometer consists of two parts: an FPI on the top side for selective IR filtering and a $V_2O_5$-based IR detector array on the bottom side for the detection of the filtered IR. Experimental results show that the FPI-based multi-channel gas sensor has reliability and selectivity for simultaneously detecting environmentally harmful gases such as $CH_4$, $CO_2$, $N_2O$ and CO in the spectral range of $3-5{\mu}m$. The fabricated FPI-based multi-channel gas sensor also demonstrated that a reliable and selective detection of gas concentrations ranging from 0 to 500 ppm is feasible. In addition, the electrical characteristics demonstrate a superior response performance in regards to the selectivity in the multi-target gases.

• Proceedings of the KIEE Conference
• /
• 2005.10b
• /
• pp.138-140
• /
• 2005

A fuzzy ARTMAP neural network and a fuzzy ART neural network are proposed to identify $H_2S$, $NH_3$ and their mixtures and to estimate their concentrations, respectively. Features are extracted from a micro gas sensor array operated in a thermal modulation plan. After dimensions of the features are reduced by a preprocessing scheme, the features are fed into the proposed fuzzy neural networks. By computer simulations, the proposed methods are shown to be fast in learning and accurate in concentration estimating. The results are compared with other methods and discussed.