Highly Efficient 3D-Printed Graphene Strain Sensors Using Fused Deposition Modeling with Filament Deposition Techniques
DC Field | Value | Language |
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dc.contributor.author | Lim, Sooman | - |
dc.contributor.author | Che Ab Rahman, Aqila | - |
dc.contributor.author | Qi, Xue | - |
dc.contributor.author | Kim, Haeji | - |
dc.contributor.author | Lee, Bum-Joo | - |
dc.contributor.author | Kim, Se Hyun | - |
dc.contributor.author | Hwang, Byungil | - |
dc.date.accessioned | 2023-12-05T11:41:37Z | - |
dc.date.available | 2023-12-05T11:41:37Z | - |
dc.date.issued | 2023-11 | - |
dc.identifier.issn | 1544-0478 | - |
dc.identifier.issn | 1544-046X | - |
dc.identifier.uri | https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/68837 | - |
dc.description.abstract | Graphene is a two-dimensional (2D) material known for its exceptional strength and high electrical conductivity, making it an ideal substance for resistive strain sensors. Recently, fused deposition modeling (FDM) in three-dimensional (3D) printing has gained attractiveness as a promising process due to its ability to produce 3D structured strain sensors by layer-by-layer melting and depositing conductive polymer composites. To ensure reliable strain sensors, comprehending how sensor properties change based on strain direction is crucial. In this study, graphene-based sensors with different slicing angles were successfully fabricated using FDM, enabling systematic study of the effect of strain angles on the performance of graphene-based sensors. The alignment of graphene filaments relative to the direction of applied strain was found to impact the gauge factor (GF) and other important sensor parameters. Our results showed that the 45° pattern exhibited higher sensitivity and stability compared to the 180° pattern, while the GF was greater for the 180° pattern. Additionally, we demonstrated high reliability and linearity through 1000 bending tests. The findings of this study will contribute to the growing body of research on FDM-fabricated graphene-based strain sensors. © 2023 The Author(s). Published with license by Taylor & Francis Group, LLC. | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | Taylor and Francis Ltd. | - |
dc.title | Highly Efficient 3D-Printed Graphene Strain Sensors Using Fused Deposition Modeling with Filament Deposition Techniques | - |
dc.type | Article | - |
dc.identifier.doi | 10.1080/15440478.2023.2276723 | - |
dc.identifier.bibliographicCitation | Journal of Natural Fibers, v.20, no.2 | - |
dc.description.isOpenAccess | Y | - |
dc.identifier.wosid | 001100871400001 | - |
dc.identifier.scopusid | 2-s2.0-85175988333 | - |
dc.citation.number | 2 | - |
dc.citation.title | Journal of Natural Fibers | - |
dc.citation.volume | 20 | - |
dc.type.docType | Article | - |
dc.publisher.location | 미국 | - |
dc.subject.keywordAuthor | electrode | - |
dc.subject.keywordAuthor | filament deposition | - |
dc.subject.keywordAuthor | Graphene | - |
dc.subject.keywordAuthor | strain sensor | - |
dc.subject.keywordAuthor | wearables | - |
dc.relation.journalResearchArea | Materials Science | - |
dc.relation.journalWebOfScienceCategory | Materials Science, Textiles | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
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