Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/118093
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dc.contributorSchool of Fashion and Textilesen_US
dc.creatorGao, Yen_US
dc.creatorXu, Ben_US
dc.creatorQiu, Men_US
dc.creatorLi, Zen_US
dc.creatorAhmed, Ten_US
dc.creatorYang, Yen_US
dc.creatorGuan, Xen_US
dc.creatorFu, Hen_US
dc.date.accessioned2026-03-13T06:53:47Z-
dc.date.available2026-03-13T06:53:47Z-
dc.identifier.issn1616-301Xen_US
dc.identifier.urihttp://hdl.handle.net/10397/118093-
dc.language.isoenen_US
dc.publisherWiley-VCHen_US
dc.rights© 2024 Wiley-VCH GmbHen_US
dc.rightsThis is the peer reviewed version of the following article: Y.Gao, B.Xu, M.Qiu, Z.Li, T.Ahmed, Y.Yang, X.Guan, H.Fu, Fabric-Reinforced Functional Insoles with Superior Durability and Antifracture Properties for Energy Harvesting and AI-Empowered Motion Monitoring. Adv. Funct. Mater.2025, 35, 2416577, which has been published in final form at https://doi.org/10.1002/adfm.202416577. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions. This article may not be enhanced, enriched or otherwise transformed into a derivative work, without express permission from Wiley or by statutory rights under applicable legislation. Copyright notices must not be removed, obscured or modified. The article must be linked to Wiley’s version of record on Wiley Online Library and any embedding, framing or otherwise making available the article or pages thereof by third parties from platforms, services and websites other than Wiley Online Library must be prohibited.en_US
dc.subjectEnergy harvestingen_US
dc.subjectFabric-reinforced structuresen_US
dc.subjectHuman motion recognitionen_US
dc.subjectMachine learningen_US
dc.subjectTriboelectric nanogeneratoren_US
dc.titleFabric-reinforced functional insoles with superior durability and antifracture properties for energy harvesting and AI-empowered motion monitoringen_US
dc.typeJournal/Magazine Articleen_US
dc.description.otherinformationTitle on author's file: Fabric-Reinforced Functional Insoles with Superior Durability and Anti-fracture Properties for Energy Harvesting and AI-empowered Motion Monitoringen_US
dc.identifier.volume35en_US
dc.identifier.issue10en_US
dc.identifier.doi10.1002/adfm.202416577en_US
dcterms.abstractFunctional triboelectric insoles hold promise for advancing self-powered wearable technologies. However, their durability is compromised by continuous compressive forces and friction, leading to surface abrasion and material fracturing. To address these challenges, an innovative fabric-reinforced structure combined with a dual-L backrest design is developed that enhances anti-fracture capabilities and electric outputs while enabling AI-empowered motion monitoring. Polydimethylsiloxane (PDMS) is used as the negative triboelectric material with a dual-L backrest design, while insulated copper wire (icuW) serves as the positive triboelectric material with an annular structure design. These components are intricately nested to enable a multilayered friction pairing. The fabric-reinforced structure demonstrates excellent compressive rebound resilience, withstanding forces of at least 1000 N. The functional insole, featuring a fabric-reinforced dual-L backrest structure (FRdL-insole), efficiently harvests biomechanical energy with a peak power of 8214 µW and maintains highly consistent performance after 10 washing cycles and 60 000 durability tests. It can power portable electronic devices such as digital watches, calculators, hygrometers, and LEDs. Enhanced with machine learning algorithms, the FRdL-insole processes sensor signals to monitor human movements, accurately identifying seven distinct motions. This positions the insole as a smart, real-time, self-powered tool for activity recognition, showcasing its potential in intelligent wearable technology.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationAdvanced functional materials, 4 Mar. 2025, v. 35, no. 10, 2416577en_US
dcterms.isPartOfAdvanced functional materialsen_US
dcterms.issued2025-03-04-
dc.identifier.scopus2-s2.0-86000426293-
dc.identifier.eissn1616-3028en_US
dc.identifier.artn2416577en_US
dc.description.validate202603 bcjzen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.SubFormIDG001237/2025-12-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextThe authors acknowledge the funding support from The Innovation and Technology Commission of Hong Kong (ITP/066/18TI) and The Hong Kong Polytechnic University (G-YWA2, 1-YXAK, 1-WZ1Y) for the work reported here.en_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryGreen (AAM)en_US
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