• Journal of the Korean Chemical Society
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• v.32 no.4
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• pp.323-332
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• 1988

The bacteria containing urease convert each molecule of urea into two molecules of ammonia and one molecule of carbon dioxide gas. Bacterial electrodes have been constructed by immobilizing the Proteus vulgaris on an ammonia and a carbon dioxide gas-sensors, and were investigated for the effects of pH, temperature, buffer solution, bacterial amounts and interferences, and life time. NH3-bacterial electrode based on ammonia gas-sensor had linearity in the range of $7.0{\times}10^{-4}\;-\;3.0{\times}10^{-2}$M urea in pH 7.4, 0.05M phosphate buffer at $25^{\circ}C$ with a slope of 116.7 mV/decade. While $CO_{2-}$bacterial electrode based on carbon dioxide gas-sensor bad linearity in the range of $7.0{\times}10^{-4}\;-\;5. 0{\times}10^{-2}$M urea in pH 7.0, 0.1M phosphate buffer at $30^{\circ}C$with a slope of $45.4{\times}45.7mV/decade$. As the clinical application, urea in urine was determined by these devices and this result was compared with spectrophotometric method. Consequently, these electrodes could be used for the analysis of many samples because of simplicity, rapidity and convenience of the experimental procedure.

• Journal of Korean Society of Environmental Engineers
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• v.35 no.4
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• pp.233-239
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• 2013

This study was carried out to develop the realtime evaluation system of $NH_3$ absorption efficiency with gas sensors which were installed on the inlet and outlet of lab-scale scrubber system. The $NH_3$ absorption amount, calculated by sensor outcomes for 3 hr, 6 hr, and 12 hr of absorption process, was compared with the results analysed by Indo-phenol method for the absorption solution. Even though the difference between two methods was about 20%, the correlation coefficient between the two results was very high, more than 0.99. In addition, we could find very good correlation between pH, absorption amount and reaction time. Also we could find out the breakthrough time in the middle of absorption process. With more diverse experiment in the future, we can make gas sensor system for the realtime evaluation of the odor and/or air pollution treatment efficiency.

• Applied Chemistry for Engineering
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• v.8 no.2
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• pp.332-338
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• 1997

$SnO_2$ as raw material of sensor for $NO_2$ detection was prepared by precipitating $SnCl_4$ solution with aqueous ammonia followed by calcining in air. The characterization of $SnO_2$ was carried out using FT-IR and XRD, and $SnO_2$ thick film sensor was fabricated by screen-printing method. The particle size of $SnO_2$ calcined at higher temperature increased due to the growth of crystalline. $SnO_2$ sensor fabricated by using $SnO_2$ sample calcined at $1000^{\circ}C$ followed by heat treatment at $700^{\circ}C$ exhibited excellent sensing characteristics and selectivity for $NO_2$ gas at the operating temperature of $250^{\circ}C$.

• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.1
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• pp.49-54
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• 2011

In this paper, we represent a mobile robot which can recognize chemical odor, measure concentration, and track its source indoors. The mobile robot has the function of smell that can sort several gases in experiment such as ammonia, ethanol, and their mixture with neural network algorithm and measure each gas concentration with fuzzy rules. In addition, it can not only navigate to the desired position with vision system by avoiding obstacles but also transmit odor information and warning messages earned from its own operations to other nodes by multi-hop communication in wireless sensor network. We suggest the way of odor sorting, concentration measurement, and source tracking for a mobile robot in wireless sensor network using a hybrid algorithm with vision system and gas sensors. The experimental studies prove that the efficiency of the proposed algorithm for odor recognition, concentration measurement, and source tracking.

• Korean Journal of Environmental Agriculture
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• v.24 no.4
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• pp.386-390
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• 2005

This study was conducted to develop the biofilter fur reducing ammonia $(NH_3)$ and hydrogen sulfide $(H_2S)$ gas emission from a pig house. A biofilter was designed and constructed by a type of squeeze air into the column type of air flow upward. Its column size was ${\Phi}260{\times}360mm$. It was used pressure drop gauge, turbo blower, air temperature, velocity sensor and control program that was programed by LabWindows CVI 5.5. Mixing materials were consisted with composted pine tree bark and perlite with 7:3 ratio (volume). The biofilter media inoculated with ammonia (Rhodococcus equi A3) and hydrogen sulfide (Alcaligenes sp. S5-5.2) oxidizing microorganisms was installed in a commercial pig house to analyzed the effectiveness of biogas removal for 10 days. Removal rates of ammonia and hydrogen sulfide gases were 90.8% and 81.5%, respectively. This result suggests that the pine compost-perlite mixture biofilter is effective and economic for reducing ammonia ana hydrogen sulfide gases.

• Applied Chemistry for Engineering
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• v.33 no.2
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• pp.126-132
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• 2022

Alkaline fuel cells using liquid fuels such as hydrazine and ammonia are gaining great attention as a clean and renewable energy solution possibly owing to advantages such as excellent energy density, simple structure, compact size in fuel container, and ease of storage and transportation. However, common shortcomings including cathode flooding, fuel crossover, side yield reactions, and fuel security and toxicity are still challenging issues. Real time monitoring of fuel concentrations integrated into a fuel cell device can help improving fuel cell performance via predicting any loss of fuels used at a cathode for efficient energy production. There have been extensive research efforts made on developing real-time sensing platforms for hydrazine and ammonia. Among these, recent advancements in electrochemical sensors offering high sensitivity and selectivity, easy fabrication, and fast monitoring capability for analysis of hydrazine and ammonia concentrations will be introduced. In particular, research trend on the integration of metallic and metal oxide nanoparticles and also their hybrids with carbon-based nanomaterials into electrochemical sensing platforms for improvement in sensitivity and selectivity will be highlighted.

• Journal of Sensor Science and Technology
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• v.30 no.6
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• pp.451-455
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• 2021

Porous copper bromide (CuBr) films are highly advantageous for detecting ammonia (NH₃). The fabrication of porous CuBr films requires complex high-temperature processes or multistep processes. Herein, we report the uncomplicated preparation of porous CuBr films by a spin-coating method and the films' excellent NH₃ sensing properties. The porous films were prepared by spin-coating 100, 150, and 200 mM CuBr solutions, and then dried in a vacuum oven for 2 h. All the films showed a high NH₃ response; in particular, the film prepared using a 100 mM CuBr solution showed an extremely high response (resistance ratio = 852) to 5 ppm NH₃. The film also showed fast response and recovery times, 272 s and 10 s respectively, even at room temperature. The outstanding NH₃ sensing characteristics were explained in relation to the porosity and thickness of the prepared films. The high-performance NH₃ sensors used in this study can be used for both indoor air quality and environmental monitoring applications.

• Proceedings of the Materials Research Society of Korea Conference
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• 2011.05a
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• pp.25.2-25.2
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• 2011

The tungsten oxide wire-like nanostructure is fabricated by deposition and thermal oxidation of tungsten metal on porous single wall carbon nanotubes (SWNTs). The morphology and crystalline quality of materials are investigated by SEM, TEM, XRD and Raman analysis. The results prove that $WO_3$ wire-like nanostructure fabricated on SWNTs show highly porous structures. Exposure of the sensors to NH3 gas in the temperature range of 150~300$^{\circ}C$ resulted in the highest sensitivity at $250^{\circ}C$ with quite rapid response and recovery time. Response time as a function of test concentrations and NH3 gas sensing mechanism is reported and discussed.

• International Journal of Advanced Culture Technology
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• v.11 no.1
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• pp.325-331
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• 2023

In this paper, we propose a mixed neural network structure of CNN and LSTM that can be used to detect or predict odor occurrence, which is most required in manufacturing industry or real life, using odor complex sensors. In addition, the proposed learning model uses a complex odor sensor to receive four types of data such as hydrogen sulfide, ammonia, benzene, and toluene in real time, and applies this data to an inference model to detect and predict odor conditions. The proposed model evaluated the prediction accuracy of the learning model through performance indicators according to accuracy, and the evaluation result showed an average performance of 94% or more.

• International Journal of Advanced Culture Technology
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• v.11 no.4
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• pp.464-469
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• 2023

As modern society develops, the number of diseases caused by bad smells is increasing. As it can harm people's health, it is important to predict in advance the extent to which bad smells may occur, inform the public about this, and take preventive measures. In this paper, we propose a hybrid neural network structure of CNN and LSTM that can be used to detect or predict the occurrence of odors, which are most required in manufacturing or real life, using odor complex sensors. In addition, the proposed learning model uses a complex odor sensor to receive four types of data, including hydrogen sulfide, ammonia, benzene, and toluene, in real time, and applies this data to the inference model to detect and predict the odor state. The proposed model evaluated the prediction accuracy of the training model through performance indicators based on accuracy, and the evaluation results showed an average performance of more than 94%.