Detailed Information

Cited 0 time in webofscience Cited 0 time in scopus
Metadata Downloads

Ion trap and release dynamics enables nonintrusive tactile augmentation in monolithic sensory neuron

Full metadata record
DC Field Value Language
dc.contributor.authorKweon, Hyukmin-
dc.contributor.authorKim, Joo Sung-
dc.contributor.authorKim, Seongchan-
dc.contributor.authorKang, Haisu-
dc.contributor.authorKim, Dong Jun-
dc.contributor.authorChoi, Hanbin-
dc.contributor.authorRoe, Dong Gue-
dc.contributor.authorChoi, Young Jin-
dc.contributor.authorLee, Seung Geol-
dc.contributor.authorCho, Jeong Ho-
dc.contributor.authorKim, Do Hwan-
dc.date.accessioned2023-11-14T08:15:45Z-
dc.date.available2023-11-14T08:15:45Z-
dc.date.created2023-10-31-
dc.date.issued2023-10-
dc.identifier.issn2375-2548-
dc.identifier.urihttps://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/192175-
dc.description.abstractAn iontronic-based artificial tactile nerve is a promising technology for emulating the tactile recognition and learning of human skin with low power consumption. However, its weak tactile memory and complex integration structure remain challenging. We present an ion trap and release dynamics (iTRD)-driven, neuro-inspired monolithic artificial tactile neuron (NeuroMAT) that can achieve tactile perception and memory consolidation in a single device. Through the tactile-driven release of ions initially trapped within iTRD-iongel, NeuroMAT only generates nonintrusive synaptic memory signals when mechanical stress is applied under voltage stimulation. The induced tactile memory is augmented by auxiliary voltage pulses independent of tactile sensing signals. We integrate NeuroMAT with an anthropomorphic robotic hand system to imitate memory-based human motion; the robust tactile memory of NeuroMAT enables the hand to consistently perform reliable gripping motion.-
dc.language영어-
dc.language.isoen-
dc.publisherAMER ASSOC ADVANCEMENT SCIENCE-
dc.titleIon trap and release dynamics enables nonintrusive tactile augmentation in monolithic sensory neuron-
dc.typeArticle-
dc.contributor.affiliatedAuthorKim, Do Hwan-
dc.identifier.doi10.1126/sciadv.adi3827-
dc.identifier.scopusid2-s2.0-85174641515-
dc.identifier.wosid001085556000001-
dc.identifier.bibliographicCitationScience advances, v.9, no.42, pp.1 - 10-
dc.relation.isPartOfScience advances-
dc.citation.titleScience advances-
dc.citation.volume9-
dc.citation.number42-
dc.citation.startPage1-
dc.citation.endPage10-
dc.type.rimsART-
dc.type.docTypeArticle-
dc.description.journalClass1-
dc.description.isOpenAccessY-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaScience & Technology - Other Topics-
dc.relation.journalWebOfScienceCategoryMultidisciplinary Sciences-
dc.subject.keywordPlusFORCE-FIELD-
dc.subject.keywordPlusMEMORY-
dc.subject.keywordPlusTRANSISTORS-
dc.subject.keywordPlusSIMULATIONIMPLICITOBJECTS-
dc.identifier.urlhttps://www.science.org/doi/10.1126/sciadv.adi3827-
Files in This Item
Go to Link
Appears in
Collections
서울 공과대학 > 서울 화학공학과 > 1. Journal Articles

qrcode

Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.

Related Researcher

Researcher Kim, Do Hwan photo

Kim, Do Hwan
COLLEGE OF ENGINEERING (DEPARTMENT OF CHEMICAL ENGINEERING)
Read more

Altmetrics

Total Views & Downloads

BROWSE