• Title/Summary/Keyword: Gas Detection Sensor

검색결과 351건 처리시간 0.02초

휘발성 질소화합물 감응형 색변환 센서를 활용한 연어 신선도 모니터링 (Freshness Monitoring of Raw Salmon Filet Using a Colorimetric Sensor that is Sensitive to Volatile Nitrogen Compounds)

  • 김재만;이현지;현정호;박준식;김용신
    • 센서학회지
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    • 제29권2호
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    • pp.93-99
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    • 2020
  • A colorimetric paper sensor was used to detect volatile nitrogen-containing compounds emitted from spoiled salmon filets to determine their freshness. The sensing mechanism was based on acid-base reactions between acidic pH-indicating dyes and basic volatile ammonia and amines. A sensing layer was simply fabricated by drop-casting a dye solution of bromocresol green (BCG) on a polyvinylidene fluoride substrate, and its color-change response was enhanced by optimizing the amounts of additive chemicals, such as polyethylene glycol, p-toluene sulfonic acid, and graphene oxide in the dye solution. To avoid the adverse effects of water vapor, both faces of the sensing layer were enclosed by using a polyethylene terephthalate film and a gas-permeable microporous polytetrafluoroethylene sheet, respectively. When exposed to basic gas analytes, the paper-like sensor distinctly exhibited a color change from initially yellow, then to green, and finally to blue due to the deprotonation of BCG via the Brønsted acid-base reaction. The use of ammonia analyte as a test gas confirmed that the sensing performance of the optimized sensor was reversible and excellent (detection time of < 15 min, sensitive naked-eye detection at 0.25 ppm, good selectivity to common volatile organic gases, and good stability against thermal stress). Finally, the coloration intensity of the sensor was quantified as a function of the storage time of the salmon filet at 28℃ to evaluate its usefulness in monitoring of the food freshness with the measurement of the total viable count (TVC) of microorganisms in the food. The TVC value increased from 3.2 × 105 to 3.1 × 109 cfu/g in 28 h and then became stable, whereas the sensor response abruptly changed in the first 8 h and slightly increased thereafter. This result suggests that the colorimetric response could be used as an indicator for evaluating the degree of decay of salmon induced by microorganisms.

프리스탠딩 저항형 가스 센서용 산화구리 무전해 도금 탄소스펀지 제조 및 일산화질소 감지 (Fabrication of Copper(II) Oxide Plated Carbon Sponge for Free-standing Resistive Type Gas Sensor and Its Application to Nitric Oxide Detection)

  • 김석진;하성민;명성재;이영석
    • 공업화학
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    • 제33권6호
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    • pp.630-635
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    • 2022
  • 멜라민 스펀지를 열처리하여 제조된 질소함유 탄소 스펀지에 산화구리(CuO)를 무전해 도금하여 기판없이 작동하는 일산화질소(NO) 가스 센서를 제조하였다. 탄소 스펀지 표면의 CuO 함량은 도금 시간이 증가함에 따라 증가하였으나, NO 가스 흡착을 유도한다고 알려져 있는 질소의 함량은 CuO 표면 함량이 증가함에 따라 감소하였다. 미처리 탄소스펀지는 NO 가스에 대하여 18 min에 최대 저항 변화(5.0%)를 나타내었다. 반면에, CuO가 도금된 샘플(CuO30s-CS)은 8 min만에 최대 18.3%의 저항변화를 보였다. 이러한 NO 가스 감지 능력 향상은 CuO로 인하여 탄소 스펀지의 정공 캐리어 수 증가 및 전자전달 촉진에 기인하는 것으로 판단된다. 그러나, 60 s 동안 CuO 무전해 도금된 탄소 스펀지의 NO가스 감지 저항은 1.9%로 오히려 감소하였다. 이는 탄소 스펀지 표면에 CuO로 완전히 도금되어 NO 가스 흡착 능력이 떨어져 저항변화가 감소한 것으로 판단된다. 따라서, CuO가 도금된 탄소 스펀지는 빠르고 우수한 저항변화 특성을 가지고 있어 유용한 NO 가스 센서로 사용할 수 있으나, CuO가 탄소 스펀지 표면을 완전히 도금해서는 안 된다.

분광특성을 이용한 소형의 메탄 가스 감지 시스템 (Small Methane Detection System using Optical Spectrum Characteristics)

  • 조경화;류근준;김응수
    • 센서학회지
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    • 제20권1호
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    • pp.53-57
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    • 2011
  • We developed a small methane detection system because methane gas is used in many areas and is dangerous. The developed system consisted of LD(Laser Diode) tuned a wavelength of $1.65\;{\mu}m$, two mirrors to collect a laser beam, photo detector. It could detect methane gas at a long range and its sensitivity was 1.98 V/$CH_4%$.

가스절연개폐장치용 UHF 부분방전검출장치의 새로운 감도 측정방법 (A Novel Sensitivity Verification Method for the UHF Partial Discharge Detection System in Gas Insulated Switchgear (GIS))

  • 구선근;박기준;윤진열
    • 대한전기학회논문지:전기물성ㆍ응용부문C
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    • 제50권9호
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    • pp.450-455
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    • 2001
  • We proposed a new sensitivity verification method for the UHF partial discharge(PD) detection system. Initially, we measure the UHF power induced by 5 pC PD which takes place near UHF sensor. Subsequently, we inject the swept UHF signal from a network analyzer into the GIS and measure the attenuation of the signal along the 71S Both the UHF power by 5 pC PD and the attenuation make it possible to verify the sensitivity and spatial coverage of the PD detection system. This method doesn\`t require the calibration of injected pulse type UHF signal into the GIS and makes us precisely measure the attenuation in frequency domain.

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지하매설 가스배관의 가스 누출시 지하 확산거동에 관한 연구 (A Study on the Diffusion Behavior of Leak Gas from Underground Gas Pipeline)

  • 최송천;조영도;김교선
    • 한국가스학회지
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    • 제3권2호
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    • pp.43-52
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    • 1999
  • 지하에 매설된 도시가스 배관에서의 누출 가스에 대한 확산 거동을 관찰하기 위하여 지중 확산실험조를 제작하여 실험하였다. 실험조는 도시가스 공급위치와 농도의 측정위치를 변화시킬 수 있도록 acryl로 제작하였으며, MOS 센서를 이용하여 도시가스 농도를 측정하였다. 가스의 지하 확산을 측정하기 위한 토질로서 주문진 표준사와 화강풍화토를 이용하였으며, 가스누출 속도 변화에 따른 도시가스 농도 변화를 시간에 따라 측정하였다. 누출점으로부터 센서의 측정위치가 가까울수록 또는 누출 속도가 증가할수록 가스의 감지시간이 감소하였으며, 누출가스 농도의 빠른 증가로 인하여 정상상태시 높은 농도를 나타내었다. 또한, 주문진 표준사보다 다짐에 의해 밀도가 증가한 화강풍화토에서 초기에 농도가 낮게 측정되었으나, 시간이 지남에 따라 농도가 높게 나타났다.

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ssDNA를 이용한 그래핀 가스 센서 (Vapor Detection of ssDNA Decorated Graphene Transistor)

  • 정영모;김영준;문희규;김수민;신범주;이주송;서민아;이택진;김재헌;전성찬;이석;김철기
    • 센서학회지
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    • 제23권5호
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    • pp.310-313
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    • 2014
  • We report a way to improve the ability of graphene to operate as a gas sensor by applying single stranded deoxyribonucleic acid (DNA). The sensitivity and recovery of the DNA-graphene sensor depending on the different DNA sequences are analyzed. The different sensor responses to reactive chemical vapors are demonstrated in the time domain. Because of the chemical gating effect of the deposited DNA, the resulting devices show complete and rapid recovery to baseline unlike the bare graphene at room temperature. The application of the pattern recognition technique can increase the potential of DNA-graphene sensors as a chemical vapor classifier.

DMMP 검출용 금속산화물을 첨가한 $SnO_2$ 가스센서 제조 (Fabrication of $SnO_2$ Gas Sensor added by Metal Oxide for DMMP)

  • 최낙진;반태현;곽준혁;백원우;김재창;허증수;이덕동
    • 한국군사과학기술학회지
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    • 제6권3호
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    • pp.54-61
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    • 2003
  • $SnO_2$ gas sensor for the detection DMMP, simulant of nerve gas was fabricated and its characteristics were examined. Sensing materials were $SnO_2$ added by TEX>$\alpha$-$Al_{2}O_{3}$ with 0∼20wt.% and $In_{2}O_{3}$ with 0∼3wt.% and were physically mixed each material. They were deposited by screen printing method on alumina substrate. The sensor was consisted of sensing electrode with interdigit(IDT) type in front and a heater in back side. Its dimension was 7$\times$10$\times$0.6$\textrm{mm}^2$. Crystallite size 8t phase identification, specific surface area and morphology of fabricated $SnO_2$ powders were analyzed by X-ray diffraction(XRD), surface area analyzer(BET) and by a scanning electron microscope(SEM), respectively. Sensor was measured as flow type and sensor resistance change was monitored as real time using LabVIEW program. The best sensitivities were 75% at adding 4wt.% TEX>$\alpha$-$Al_{2}O_{3}$, operating temperature $300^{\circ}C$ and 87% at adding 2wt.% $In_{2}O_{3}$, operating temperature $350^{\circ}C$ to DMMP 0.5ppm. Response and recovery times were about 1 and 3 min., respectively. Repetition measurement was very good with $\pm$3% in full scale. As a result, operating temperature was lower TEX>$\alpha$-$Al_{2}O_{3}$ than $In_{2}O_{3}$, but sensitivity was higher $In_{2}O_{3}$ than $\alpha$-$Al_{2}O_{3}$.

인공지능 기반의 스마트 센서 기술 개발 동향 (Recent Progress of Smart Sensor Technology Relying on Artificial Intelligence)

  • 신현식;김종웅
    • 마이크로전자및패키징학회지
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    • 제29권3호
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    • pp.1-12
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    • 2022
  • 인공지능 기술의 급속한 발전으로 기존 센서에 인간의 지능과 유사한 기능을 부여하기 위한 연구가 큰 주목을 받고 있다. 기존에는 주로 센서로써의 기초 성능지표, 예를 들어 감도 및 속도 등을 향상시키기 위한 연구가 주로 진행되었지만, 최근에는 분류나 예측 등의 인공지능을 센서에 결합하기 위한 시도가 확대되고 있다. 이를 바탕으로 최근 질병 감지 센서, 모션 감지 센서 및 가스 센서 등 거의 센서 전 분야에서 지능형 센서에 대한 연구 결과가 활발히 보고되고 있다. 본 논문에서는 인공지능의 기본적인 개념, 종류 및 메커니즘과 더불어, 최근 보고된 지능형 센서에의 적용 사례에 대해 알아보고자 한다.

Machine Learning in FET-based Chemical and Biological Sensors: A Mini Review

  • Ahn, Jae-Hyuk
    • 센서학회지
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    • 제30권1호
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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.