Full metadata record
DC Field | Value | Language |
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dc.contributor.author | Kim, Sohee | - |
dc.contributor.author | Jang, Hyun Woo | - |
dc.contributor.author | Kwon, Hyeokjin | - |
dc.contributor.author | Heo, Su Jin | - |
dc.contributor.author | Pyo, Goeun | - |
dc.contributor.author | Kim, Dong Su | - |
dc.contributor.author | Chae, Ji Won | - |
dc.contributor.author | Jang, Jae Eun | - |
dc.date.accessioned | 2023-12-26T18:43:03Z | - |
dc.date.available | 2023-12-26T18:43:03Z | - |
dc.date.created | 2022-02-15 | - |
dc.date.issued | 2021-11-03 | - |
dc.identifier.isbn | 9781728195018 | - |
dc.identifier.issn | 1930-0395 | - |
dc.identifier.uri | http://hdl.handle.net/20.500.11750/46888 | - |
dc.description.abstract | High selectivity of the sensor is one of the most important parameters for the electronic nose (E-nose) or gas sensor. However, many sensors have shown poor selectivity, even though some had high sensitivity. To solve this issue, we suggested a multi-sensor array concept, which consisted of thin-film transistors (TFTs) with various polymer selectors. By using TFT as a base sensor structure, sensitivity was significantly enhanced, and by adopting a polymer as the second dielectric layer, there was a remarkable improvement in selectivity. Some polymers showed unique selectivity to a specific odorant, whereas others had a moderate reaction to various odorants. Instead of common one-to-one matching between a sensor and an odorant, we used multi-output analysis using a dimensional bar chart. Eight different polymers TFTs made a specific chart pattern for four different odorants. Therefore, this sensor array and signal process concept can apply to the e-nose system, which can classify many odorants like a human simulator. © 2021 IEEE. | - |
dc.language | English | - |
dc.publisher | IEEE Sensors Council | - |
dc.title | Detection of Odorant using TFT multi-array with Various Polymers | - |
dc.type | Conference Paper | - |
dc.identifier.doi | 10.1109/SENSORS47087.2021.9639635 | - |
dc.identifier.scopusid | 2-s2.0-85123610319 | - |
dc.identifier.bibliographicCitation | IEEE SENSORS 2021, pp.1 - 4 | - |
dc.identifier.url | https://2021.ieee-sensorsconference.org/wp-content/uploads/sites/16/2021/10/sensors-2021_program_v10-1-2.pdf | - |
dc.citation.conferencePlace | AT | - |
dc.citation.conferencePlace | Sydney | - |
dc.citation.endPage | 4 | - |
dc.citation.startPage | 1 | - |
dc.citation.title | IEEE SENSORS 2021 | - |
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