Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/108958
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dc.contributorDepartment of Applied Physicsen_US
dc.creatorDai, Xen_US
dc.creatorWu, Yen_US
dc.creatorLiang, Qen_US
dc.creatorYang, Jen_US
dc.creatorHuang, LBen_US
dc.creatorKong, Jen_US
dc.creatorHao, Jen_US
dc.date.accessioned2024-09-11T08:33:55Z-
dc.date.available2024-09-11T08:33:55Z-
dc.identifier.issn1616-301Xen_US
dc.identifier.urihttp://hdl.handle.net/10397/108958-
dc.language.isoenen_US
dc.publisherWiley-VCH Verlag GmbH & Co. KGaAen_US
dc.rights© 2023 Wiley-VCH GmbHen_US
dc.rightsThis is the peer reviewed version of the following article: X. Dai, Y. Wu, Q. Liang, J. Yang, L.-B. Huang, J. Kong, J. Hao, Soft Robotic-Adapted Multimodal Sensors Derived from Entirely Intrinsic Self-Healing and Stretchable Cross-Linked Networks. Adv. Funct. Mater. 2023, 33, 2304415, which has been published in final form at https://doi.org/10.1002/adfm.202304415. 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.subjectFlexible sensing technologyen_US
dc.subjectMultimodalen_US
dc.subjectSelf-healingen_US
dc.subjectSoft roboticsen_US
dc.subjectStretchabilityen_US
dc.titleSoft robotic-adapted multimodal sensors derived from entirely intrinsic self-healing and stretchable cross-linked networksen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume33en_US
dc.identifier.issue44en_US
dc.identifier.doi10.1002/adfm.202304415en_US
dcterms.abstractFlexible sensing technologies that play a pivotal role in endowing robots with detection capabilities and monitoring their motions are impulsively desired for intelligent robotics systems. However, integrating and constructing reliable and sustainable flexible sensors with multifunctionality for robots remains an everlasting challenge. Herein, an entirely intrinsic self-healing, stretchable, and attachable multimodal sensor is developed that can be conformally integrated with soft robots to identify diverse signals. The dynamic bonds cross-linked networks including the insulating polymer and conductive hydrogel with good comprehensive performances are designed to fabricate the sensor with prolonged lifespan and improved reliability. Benefiting from the self-adhesiveness of the hydrogel, strong interfacial bonding can be formed on various surfaces, which promotes the conformable integration of the sensor with robots. Due to the ionic transportation mechanism, the sensor can detect strain and temperature based on piezoresistive and thermoresistive effect, respectively. Moreover, the sensor can work in triboelectric mode to achieve self-powered sensing. Various information can be identified from the electrical signals generated by the sensor, including hand gestures, soft robot crawling motions, a message of code, the temperature of objects, and the type of materials, holding great promise in the fields of environmental detection, wearable devices, human-machine interfacing, and robotics.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationAdvanced functional materials, 25 Oct. 2023, v. 33, no. 44, 2304415en_US
dcterms.isPartOfAdvanced functional materialsen_US
dcterms.issued2023-10-25-
dc.identifier.scopus2-s2.0-85163849587-
dc.identifier.eissn1616-3028en_US
dc.identifier.artn2304415en_US
dc.description.validate202409 bcchen_US
dc.description.oaAccepted Manuscripten_US
dc.identifier.FolderNumbera3188-
dc.identifier.SubFormID49757-
dc.description.fundingSourceRGCen_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryGreen (AAM)en_US
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