• Journal of Sensor Science and Technology
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• v.18 no.1
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• pp.1-21
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• 2009

There have been continued effects to develop various types of chemical sensors according to the demands in many application fields such as safety, pollution, environment, medical engineering and food industries etc. In this review, the author intended to cover the general aspects of chemical sensors, including the history of the development, the classification, the sensing properties, and the types and application examples. And the future outlook of the chemical sensor technology, focusing on the advanced materials, high technology fusion, miniaturized intelligent system and ubiquitous sensor networks etc., has been described.

• Journal of Sensor Science and Technology
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• v.20 no.4
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• pp.279-285
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• 2011

This study was carried out to apply chemical gas sensors for the identification of bad breath which is one of the important sensitive problem for the humans' daily life. Seven sensors, including five semiconductor sensors and two electrochemical sensors, were tested for the three panels three times in several conditions. The results showed that the reproducibility of sensors were generally good, and electrochemical sensors showed better reproducibility while semiconductor sensors showed better sensitivity. No rinsing before measurement showed relatively better results in terms of both sensitivity and reproducibility. Semiconductor gas sensors for hydrogen sulfide shows the highest sensitivity, and it was recommended to use the odor-free bag for the measurement of bad breath.

• Journal of Sensor Science and Technology
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• v.23 no.5
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• pp.299-304
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• 2014

Optimizing the performance of a composite sensor array is necessary when the number of sensors to choose from is large. In this paper, we present a chemical sensors array optimization method using Wilks Lamda algorithm applicable a device to detect low concentration of alcohol from driver's exhale breath for interlocking engine ignition preventing drink-driving. More than 20 chemical sensors fabricated different synthetic stuffs and heater temperatures by collaborators were nominated, 5 sensors were selected for optimal sensors array using the method, and alcohol samples were well discriminated from the interference gases inside the vehicle. It has been confirmed by Principal Component Analysis (PCA).

• Journal of Sensor Science and Technology
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• v.31 no.6
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• pp.389-396
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• 2022

Quartz crystal microbalance (QCM) based sensors are used for various applications owing to advantages such as excellent accuracy and precision, rapid response, and tiny footprint. Traditional applications of QCM-based sensors include biological sensing and thin-film thickness monitoring. Recently, QCMs have been used as functional material for novel physical and chemical detections, and with improved device design. QCM-based sensors are garnering considerable attention in particulate matter sensing and electric nose application. This review covers the challenges and solutions in physical, chemical, and biological sensing applications. First, various physical sensing applications are introduced. Secondly, the toxic gas and chemical detection studies are outlined, focusing on introducing a coating method for uniform sensing film and sensing materials for a minimal damping effect. Lastly, the biological and medical sensing applications, which use the monomolecularly decorating method for biomolecule recognition and a brief description of the overall measuring system, are also discussed.

• 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.

• Proceedings of the Korean Vacuum Society Conference
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• 2016.02a
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• pp.363.2-363.2
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• 2016

Stretchable strain sensors are becoming essential in diverse future applications, such as human motion detection, soft robotics, and various biomedical devices. One of the well-known approaches for fabricating stretchable strain sensors is to embed conductive nanomaterials such as metal nanowires/nanoparticles, graphene, conducting polymer and carbon nanotubes (CNTs) within an elastomeric substrate. Among various conducting nanomaterials, CNTs have been considered as important and promising candidate materials for stretchable strain sensors owing to their high electrical conductivity and excellent mechanical properties. In the past decades, CNT-based strain sensors with high stretchability or sensitivity have been developed. However, CNT-based strain sensors which show both high stretchability and sensitivity have not been reported. Herein, highly stretchable and sensitive strain sensors were fabricated by integrating single-walled carbon nanotubes (SWNTs) and nylon textiles via vacuum-assisted spray-layer-by-layer process. Our strain sensors had high sensitivity with 100 % tensile strain (gauge factor ~ 100). Cyclic tests confirmed that our strain sensors showed very robust and reliable characteristic. Moreover, our SWNTs-based strain sensors were easily and successfully integrated on human finger and knee to detect bending and walking motion. Our approach presented here might be route to preparing highly stretchable and sensitive strain sensors with providing new opportunity to realize practical wearable devices.

• Journal of Sensor Science and Technology
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• v.28 no.3
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• pp.139-145
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• 2019

Precautionary detection of chemical warfare agents (CWAs) has been an important global issue mainly owing to their toxicity. To achieve proper detection, many studies have been conducted to develop sensitive gas sensors for CWAs. In particular, metal-oxide semi-conductors (MOS) have been investigated as promising sensing materials owing to their abundance in nature and excellent sensitivity. In this review, we mainly focus on various MOS-based gas sensors that have been fabricated for the detection of two specific CWA simulants, 2-chloroethyl ethyl sulfide (2-CEES) and dimethyl methyl phosphonate (DMMP), which are simulants of sulfur mustard and sarin, respectively. In the case of 2-CEES, we mainly discuss $CdSnO_3-$ and ZnO-based sensors and their reaction mechanisms. In addition, a method to improve the selectivity of ZnO-based sensors is mentioned. Various sensors and their sensing mechanisms have been introduced for the detection of DMMP. As the reaction with DMMP may directly affect the sensing properties of MOS, this paper includes previous studies on its poisoning effect. Finally, promising sensing materials for both gases are proposed.

• Proceedings of the Materials Research Society of Korea Conference
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• 2011.10a
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• pp.3.2-3.2
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• 2011

Nanofibers, one of various one-dimensional nanomaterials such as nanorods, nanowires and nanotubes have been successfully synthesized by many groups in recent years and their applications to chemical sensors, catalytic filters and biomedicine, etc. are extensively tested. In particular, there is a possibility that chemical sensors based on oxide nanofibers can overcome the shortcomings of chemical sensors based on single nanowires. In order to prepare oxide nanofibers, the electrospinning method is most widely used. In this work, we synthesized various oxide nanofibers including ZnO, SnO2 and CuO by employing an electrospinning method and various shapes of nanofibers including core-shell nanofibers and hollow nanofibers as well. The response properties of the various nanofibers to oxidizing and reducing gaseous species have been investigated systematically. The normal oxide nanofibers showed high sensitivity and quite fast response time to many gaseous species. Furthermore, derivatives of normal nanofibers including hollow nanofibers, core-shell nanofibers and heterostructured nanofibers display much superior sensing properties. These results hold promise for the practical application of oxide nanofibers to chemical sensors. In addition, the sensing mechanisms operated in the nanofibers will be discussed in detail.

• Elastomers and Composites
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• v.56 no.3
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• pp.117-123
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• 2021

Electronic skin (or E-skin) is an artificial smart skin composed of one or more than two sensors. E-skins detect external stimuli and convert them into electrical signals. Various types of E-skin sensors exist, including mechanical, physical, and chemical, depending on the detection signals involved. For wearable E-skins with superior sensitivity and reliability, developing conductors that possess both good elasticity and sensitivity is essential. Typical electrical conductors used in these sensors show very high sensitivity, but they have drawbacks such as non-linearity, irreversibility, and a narrow sensing range. To address these issues, stretchable and lightweight ionic conductors have been actively used in E-skin applications. This study summarizes the recent progress on various types of ionic conductors and ionic-conductor-based E-skin sensors.

• 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.