Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/118304
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dc.contributorResearch Institute for Intelligent Wearable Systemsen_US
dc.contributorSchool of Fashion and Textilesen_US
dc.creatorDong, Sen_US
dc.creatorJu, Zen_US
dc.creatorYao, Pen_US
dc.creatorLiu, Yen_US
dc.creatorXu, Ben_US
dc.creatorHu, Hen_US
dc.date.accessioned2026-04-01T03:16:36Z-
dc.date.available2026-04-01T03:16:36Z-
dc.identifier.urihttp://hdl.handle.net/10397/118304-
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.subjectFreely cuttableen_US
dc.subjectSelf-powered flexible sensoren_US
dc.subjectThree-thread fleecy knittingen_US
dc.subjectTriboelectric nanogeneratoren_US
dc.subjectUltra-high scalabilityen_US
dc.titleFlexible and freely cuttable fleecy triboelectric fabrics for ultra-high scalability in self-powered sensing applicationsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume42en_US
dc.identifier.doi10.1016/j.apmt.2024.102569en_US
dcterms.abstractFlexible textile-based sensors, renowned for their adaptability and comfort, hold considerable promise across multiple fields. However, their scalability remains constrained by factors such as material selection and manufacturing processes. This study presents an innovative approach for the efficient production of flexible sensing fabrics utilizing three-thread fleecy knitting technology, achieving a high production rate of approximately 11.53 m²/h. The resulting fleecy sensing fabric works as a triboelectric nanogenerator, generating electrical signals and reaching a peak power density of approximately 2446 μW/m² when rubbed against cotton fabric. Constructed entirely from commercially available yarn materials, the fabric exhibits exceptional flexibility, fullness, and breathability, while maintaining consistent output performance even after multiple machine wash cycles. This fabric can be freely cut and customized into self-powered flexible sensors for diverse applications, such as insoles for monitoring movement patterns and carpets for tracking movement postures. Enhanced by machine learning algorithms, the fleecy sensing fabric demonstrates robust recognition capabilities. This synergy paves the way for the development of cost-effective, comfortable, and widely applicable flexible sensors, thereby broadening their potential for practical implementation in diverse scenarios.en_US
dcterms.accessRightsembargoed accessen_US
dcterms.bibliographicCitationApplied materials today, Feb. 2025, v. 42, 102569en_US
dcterms.isPartOfApplied materials todayen_US
dcterms.issued2025-02-
dc.identifier.scopus2-s2.0-85213006770-
dc.identifier.eissn2352-9407en_US
dc.identifier.artn102569en_US
dc.description.validate202604 bchyen_US
dc.description.oaNot applicableen_US
dc.identifier.SubFormIDG001409/2026-03-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextThis work was supported by the Research Institute for Intelligent Wearable Systems of The Hong Kong Polytechnic University in the form of an internal project (No. P0039471).en_US
dc.description.pubStatusPublisheden_US
dc.date.embargo2027-02-28en_US
dc.description.oaCategoryGreen (AAM)en_US
Appears in Collections:Journal/Magazine Article
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Embargo End Date 2027-02-28
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