Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/113919
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dc.contributorDepartment of Biomedical Engineeringen_US
dc.contributorResearch Institute for Smart Ageingen_US
dc.contributorDepartment of Electrical and Electronic Engineeringen_US
dc.contributorDepartment of Applied Biology and Chemical Technologyen_US
dc.creatorYao, KYen_US
dc.creatorLai, DKHen_US
dc.creatorLim, HJen_US
dc.creatorSo, BPHen_US
dc.creatorChan, ACHen_US
dc.creatorYip, PYMen_US
dc.creatorWong, DWCen_US
dc.creatorDai, BYen_US
dc.creatorZhao, Xen_US
dc.creatorWong, SHDen_US
dc.creatorCheung, JCWen_US
dc.date.accessioned2025-06-27T09:30:41Z-
dc.date.available2025-06-27T09:30:41Z-
dc.identifier.issn0264-1275en_US
dc.identifier.urihttp://hdl.handle.net/10397/113919-
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.rights© 2025 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).en_US
dc.rightsThe following publication Yao, K.-Y., Lai, D. K.-H., Lim, H.-J., So, B. P.-H., Chan, A. C.-H., Yip, P. Y.-M., Wong, D. W.-C., Dai, B., Zhao, X., Wong, S. H. D., & Cheung, J. C.-W. (2025). 2H-MoS2 lubrication-enhanced MWCNT nanocomposite for subtle bio-motion piezoresistive detection with deep learning integration. Materials & Design, 253, 113861 is available at https://dx.doi.org/10.1016/j.matdes.2025.113861.en_US
dc.subjectFlexible piezoresistive sensoren_US
dc.subjectMWCNT/MoS2 nanocompositeen_US
dc.subjectLubrication tougheningen_US
dc.subjectDeep learningen_US
dc.subjectSubtle-to-moderate biophysical signalen_US
dc.title2H-MoS2 lubrication-enhanced MWCNT nanocomposite for subtle bio-motion piezoresistive detection with deep learning integration☆en_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume253en_US
dc.identifier.doi10.1016/j.matdes.2025.113861en_US
dcterms.abstractIntelligent piezoresistive health monitoring systems integrate advanced nanocomposite architectures with precise algorithmic analysis for real-time physiological assessment. However, existing works often prioritize high sensitivity at the expense of strain tolerance and require complex fabrication procedures. Herein, we present an environmentally friendly, low-cost, and nonionic fabrication approach for a 2H-phase molybdenum disulfide (2H-MoS2)-enhanced multi-walled carbon nanotube (MWCNT) strain sensor, developed via a systematically optimized vacuum-assisted filtration process. This study is the first to validate the dual enhancement effect of MoS2, leveraging its shear-exfoliation properties to simultaneously improve strain gauge performance and mechanical robustness. The resulting nacre-like layered hybrid nanocomposite achieves a remarkable gauge factor of 675.7 (R-2 similar to 0.993) at low strain (similar to 0-4.5 %), representing a 3881.5 % improvement over pure MWCNT systems, alongside enhanced toughness (similar to 89.17 %) and strain tolerance (similar to 53.93 %). Meanwhile, the optimized composition ensures low rest-state resistance (similar to 13.1 Omega), minimal hysteresis (similar to 5.7 %), and robust durability over 5000 cycles at 10 % strain. As a result, the proposed sensor enables highly consistent, high-fidelity monitoring of various subtle-to-moderate biomotions. Integrated with a fine-tuned InceptionTime deep learning model, it achieves an F1-score of 98 % in classifying Dysphagia Diet Standardization Initiative (IDDSI)-standard swallowing activities, demonstrating its potential for AI-driven health monitoring applications.en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationMaterials and design, May 2025, v. 253, 113861en_US
dcterms.isPartOfMaterials and designen_US
dcterms.issued2025-05-
dc.identifier.scopus2-s2.0-105001340477-
dc.identifier.eissn1873-4197en_US
dc.identifier.artn113861en_US
dc.description.validate202506 bcchen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOS, a3815b-
dc.identifier.SubFormID51228-
dc.description.fundingSourceOthersen_US
dc.description.fundingTextthe Health Bureau of Hong Kongen_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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