Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | 김웅 | - |
dc.date.accessioned | 2022-05-10T01:00:10Z | - |
dc.date.available | 2022-05-10T01:00:10Z | - |
dc.date.issued | 2020-09 | - |
dc.identifier.citation | ACS APPLIED MATERIALS & INTERFACES, v. 12, no. 41, page. 46629-46638 | en_US |
dc.identifier.issn | 1944-8244 | - |
dc.identifier.issn | 1944-8252 | - |
dc.identifier.uri | https://pubs.acs.org/doi/10.1021/acsami.0c11435 | - |
dc.identifier.uri | https://repository.hanyang.ac.kr/handle/20.500.11754/170707 | - |
dc.description.abstract | Graphene-based electronic textile (e-textile) gas sensors have been developed for detecting hazardous NO2 gas. For the e-textile gas sensor, electrical conductivity is a critical factor because it directly affects its sensitivity. To obtain a highly conductive e-textile, biomolecules have been used for gluing the graphene to the textile surface, though there remain areas to improve, such as poor conductivity and flexibility. Herein, we have developed a dopamine-graphene hybrid electronic textile yarn (DGY) where the dopamine is used as a bio-inspired adhesive to attach graphene to the surface of yarns. The DGY shows improved electrical conductivity (similar to 40 times) compared to conventional graphene-based e-textile yarns with no glue. Moreover, it exhibited improved sensing performance in terms of short response time (similar to 2 min), high sensitivity (0.02 mu A/ppm), and selectivity toward NO2. The mechanical flexibility and durability of the DGY were examined through a 1000-cycle bending test. For a practical application, the DGY was attempted to detect the NO(x )emitted from vehicles, including gasoline, diesel, and fuel cell electric vehicles. Our results demonstrated that the DGYs-as a graphene-based e-textile gas sensor for detecting NO2-are simple to fabricate, cheap, disposable, and mechanically stable. | en_US |
dc.description.sponsorship | This work was supported by the National Research Foundation of Korea (NRF) Grant funded by the Korean Government (MSIP) (No. NRF-2020R1A6A3A01096477, NRF-2019R1A2B5B01070617, and NRF2018M3C1B7020722). | en_US |
dc.language.iso | en | en_US |
dc.publisher | AMER CHEMICAL SOC | en_US |
dc.subject | graphene | en_US |
dc.subject | E-textile gas sensor | en_US |
dc.subject | flexible device | en_US |
dc.subject | dopamine | en_US |
dc.subject | nitrogen dioxide | en_US |
dc.title | Highly Conductive and Flexible Dopamine-Graphene Hybrid Electronic Textile Yarn for Sensitive and Selective NO2 Detection | en_US |
dc.type | Article | en_US |
dc.identifier.doi | 10.1021/acsami.0c11435 | - |
dc.relation.journal | ACS APPLIED MATERIALS & INTERFACES | - |
dc.contributor.googleauthor | Lee, Sang Won | - |
dc.contributor.googleauthor | Jung, Hyo Gi | - |
dc.contributor.googleauthor | Kim, Insu | - |
dc.contributor.googleauthor | Lee, Dongtak | - |
dc.contributor.googleauthor | Kim, Woong | - |
dc.contributor.googleauthor | Kim, Sang Hun | - |
dc.contributor.googleauthor | Lee, Jong-Heun | - |
dc.contributor.googleauthor | Park, Jinsung | - |
dc.contributor.googleauthor | Lee, Jeong Hoon | - |
dc.contributor.googleauthor | Lee, Gyudo | - |
dc.relation.code | 2020051325 | - |
dc.sector.campus | S | - |
dc.sector.daehak | COLLEGE OF ENGINEERING[S] | - |
dc.sector.department | SCHOOL OF MECHANICAL ENGINEERING | - |
dc.identifier.pid | oong0331 | - |
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