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Choi, Kyoung Jin
Energy Conversion Materials Lab.
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dc.citation.startPage 132939 -
dc.citation.title SENSORS AND ACTUATORS B-CHEMICAL -
dc.citation.volume 375 -
dc.contributor.author Kwon, Yeong Min -
dc.contributor.author Oh, Byungjoo -
dc.contributor.author Purbia, Rahul -
dc.contributor.author Chae, Hee Young -
dc.contributor.author Han, Gi Hyeon -
dc.contributor.author Kim, Sun-Woo -
dc.contributor.author Choi, Kyoung Jin -
dc.contributor.author Lee, Yunsik -
dc.contributor.author Kim, Jae Joon -
dc.contributor.author Baik, Jeong Min -
dc.date.accessioned 2023-12-21T13:10:39Z -
dc.date.available 2023-12-21T13:10:39Z -
dc.date.created 2022-11-10 -
dc.date.issued 2023-01 -
dc.description.abstract Developing a better understanding of gas-metal oxide interactions as well as improving the output performance with the aging of the gas sensing array represents a critical challenge. In this work, we have designed a surface-functionalized metal-oxide sensors array containing six units for detecting NO2, SO2, H2S, and CO hazardous gases. The responses of the sensor array to four target gases are enhanced by various catalytic effects on the surface, and they show distinctive responses to each gas. For improved selectivity, a pattern recognition algorithm is implemented under an edge computing-based environment to relieve the overload of a monitoring server. Moreover, a self-calibration method for long-term stability is designed to indirectly calibrate gas responses with aging. With its edge-computing device prototype, which includes a sensor array and its readout integrated circuit, four target gases are distinguished by an artificial neural network algorithm with 97% accuracy. The present work describes the effective platforms for emerging next-generation gas sensors with improved communication and monitoring systems. -
dc.identifier.bibliographicCitation SENSORS AND ACTUATORS B-CHEMICAL, v.375, pp.132939 -
dc.identifier.doi 10.1016/j.snb.2022.132939 -
dc.identifier.issn 0925-4005 -
dc.identifier.scopusid 2-s2.0-85141322327 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/59985 -
dc.identifier.wosid 000905098900004 -
dc.language 영어 -
dc.publisher Elsevier BV -
dc.title High-performance and self-calibrating multi-gas sensor interface to trace multiple gas species with sub-ppm level -
dc.type Article -
dc.description.isOpenAccess FALSE -
dc.relation.journalWebOfScienceCategory Chemistry, Analytical;Electrochemistry;Instruments & Instrumentation -
dc.relation.journalResearchArea Chemistry;Electrochemistry;Instruments & Instrumentation -
dc.type.docType Article -
dc.description.journalRegisteredClass scie -
dc.description.journalRegisteredClass scopus -
dc.subject.keywordAuthor Next -generation gas sensors -
dc.subject.keywordAuthor Functionalization -
dc.subject.keywordAuthor Sensor array -
dc.subject.keywordAuthor Self -calibration -
dc.subject.keywordAuthor Pattern recognition algorithm -
dc.subject.keywordPlus SENSING PROPERTIES -
dc.subject.keywordPlus SNO2 -
dc.subject.keywordPlus HETEROSTRUCTURES -
dc.subject.keywordPlus NANOPARTICLES -
dc.subject.keywordPlus PD -

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