DC Field | Value | Language |
---|---|---|
dc.contributor.author | Han, Joon-Kyu | ko |
dc.contributor.author | Park, Sang-Chan | ko |
dc.contributor.author | Yu, Ji-Man | ko |
dc.contributor.author | Ahn, Jae-Hyuk | ko |
dc.contributor.author | Choi, Yang-Kyu | ko |
dc.date.accessioned | 2022-12-19T02:01:46Z | - |
dc.date.available | 2022-12-19T02:01:46Z | - |
dc.date.created | 2022-06-22 | - |
dc.date.created | 2022-06-22 | - |
dc.date.issued | 2022-06 | - |
dc.identifier.citation | NANO LETTERS, v.22, no.13, pp.5244 - 5251 | - |
dc.identifier.issn | 1530-6984 | - |
dc.identifier.uri | http://hdl.handle.net/10203/303156 | - |
dc.description.abstract | A novel biomimicked neuromorphic sensor for an energy efficient and highly scalable electronic tongue (E-tongue) is demonstrated with a metal-oxide-semiconductor field-effect transistor (MOSFET). By mimicking a biological gustatory neuron, the proposed E-tongue can simultaneously detect ion concentrations of chemicals on an extended gate and encode spike signals on the MOSFET, which acts as an input neuron in a spiking neural network (SNN). Such in-sensor neuromorphic functioning can reduce the energy and area consumption of the conventional E-tongue hardware. pH-sensitive and sodium-sensitive artificial gustatory neurons are implemented by using two different sensing materials: Al2O3 for pH sensing and sodium ionophore X for sodium ion sensing. In addition, a sensitivity control function inspired by the biological sensory neuron is demonstrated. After the unit device characterization of the artificial gustatory neuron, a fully hardware-based E-tongue that can classify two distinct liquids is demonstrated to show a practical application of the artificial gustatory neurons. | - |
dc.language | English | - |
dc.publisher | AMER CHEMICAL SOC | - |
dc.title | A Bio-inspired Artificial Gustatory Neuron for a Neuromorphic based Electronic-tongue | - |
dc.type | Article | - |
dc.identifier.wosid | 000821555300001 | - |
dc.identifier.scopusid | 2-s2.0-85134426612 | - |
dc.type.rims | ART | - |
dc.citation.volume | 22 | - |
dc.citation.issue | 13 | - |
dc.citation.beginningpage | 5244 | - |
dc.citation.endingpage | 5251 | - |
dc.citation.publicationname | NANO LETTERS | - |
dc.identifier.doi | 10.1021/acs.nanolett.2c01107 | - |
dc.contributor.localauthor | Choi, Yang-Kyu | - |
dc.contributor.nonIdAuthor | Park, Sang-Chan | - |
dc.contributor.nonIdAuthor | Ahn, Jae-Hyuk | - |
dc.description.isOpenAccess | N | - |
dc.type.journalArticle | Article | - |
dc.subject.keywordAuthor | Biosensor | - |
dc.subject.keywordAuthor | electronic tongue | - |
dc.subject.keywordAuthor | gustatory neuron | - |
dc.subject.keywordAuthor | neuromorphic | - |
dc.subject.keywordAuthor | spiking neural network (SNN) | - |
dc.subject.keywordPlus | TRANSISTOR | - |
dc.subject.keywordPlus | NETWORK | - |
dc.subject.keywordPlus | SYSTEM | - |
dc.subject.keywordPlus | ARRAY | - |
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