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김재준

Kim, Jae Joon
Circuits & Systems Design Lab.
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dc.citation.endPage 223 -
dc.citation.number 3 -
dc.citation.startPage 208 -
dc.citation.title Journal of Sensor Science and Technology -
dc.citation.volume 34 -
dc.contributor.author Kim, Sang Heon -
dc.contributor.author Kim, Yonggi -
dc.contributor.author Choi, Han Sol -
dc.contributor.author Kim, Jae Joon -
dc.contributor.author Baik, Jeong Min -
dc.date.accessioned 2025-12-04T09:29:17Z -
dc.date.available 2025-12-04T09:29:17Z -
dc.date.created 2025-12-03 -
dc.date.issued 2025-05 -
dc.description.abstract This review summarizes recent progress in metal oxide-based gas sensors, focusing on material design, catalytic engineering, and real-time sensing strategies. Advances in nanostructured materials, heterojunctions, and noble metal catalysts have significantly improved sensor sensitivity, selectivity, and stability. Techniques such as Schottky barrier modulation, spill-over effects, and
interfacial charge transfer are key to enhancing gas response. Additionally, integrating sensor arrays with artificial intelligence (AI)-
based analysis, including Edge AI and convolutional neural networks, enables accurate, low-power, and real-time gas detection.
These combined strategies pave the way for next-generation gas sensors suitable for diverse applications in environmental monitoring, safety, and healthcare
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dc.identifier.bibliographicCitation Journal of Sensor Science and Technology, v.34, no.3, pp.208 - 223 -
dc.identifier.doi 10.46670/JSST.2025.34.3.208 -
dc.identifier.issn 1225-5475 -
dc.identifier.scopusid 2-s2.0-105008237317 -
dc.identifier.uri https://scholarworks.unist.ac.kr/handle/201301/88875 -
dc.language 영어 -
dc.publisher 한국센서학회 -
dc.title Smart Metal Oxide Gas Sensors with Catalytic and Artificial Intelligence-Driven Selectivity -
dc.type Article -
dc.description.isOpenAccess TRUE -
dc.type.docType Review -
dc.description.journalRegisteredClass scopus -
dc.description.journalRegisteredClass kci -

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