Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/117658
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dc.contributorDepartment of Civil and Environmental Engineering-
dc.creatorWang, D-
dc.creatorZhang, Z-
dc.creatorDing, S-
dc.creatorNing, C-
dc.creatorShi, C-
dc.creatorLiu, X-
dc.creatorRen, Q-
dc.creatorJiang, Z-
dc.date.accessioned2026-02-26T03:47:51Z-
dc.date.available2026-02-26T03:47:51Z-
dc.identifier.issn2522-0128-
dc.identifier.urihttp://hdl.handle.net/10397/117658-
dc.language.isoenen_US
dc.publisherSpringer New York LLCen_US
dc.rights© The Author(s) 2025en_US
dc.rightsOpen Access This article is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License, which permits any non-commercial use, sharing, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if you modified the licensed material. You do not have permission under this licence to share adapted material derived from this article or parts of it. The images or other third party material in this article are included in the article’s Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by-nc-nd/4.0/.en_US
dc.rightsThe following publication Wang, D., Zhang, Z., Ding, S. et al. Manufacturing a low-carbon geopolymer self-sensing composite for intelligent structure. Adv Compos Hybrid Mater 8, 363 (2025) is available at https://doi.org/10.1007/s42114-025-01462-3.en_US
dc.subjectFlexural loadingen_US
dc.subjectGeopolymeren_US
dc.subjectIntelligent structureen_US
dc.subjectSelf-sensingen_US
dc.subjectStructural health monitoringen_US
dc.titleManufacturing a low-carbon geopolymer self-sensing composite for intelligent structureen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume8-
dc.identifier.issue5-
dc.identifier.doi10.1007/s42114-025-01462-3-
dcterms.abstractThe advancement of smart building and infrastructure has increased the demand for intelligent materials with highly sensitive structural health monitoring (SHM) function. This study reports a high cost-effective strategy of manufacturing geopolymer self-sensing composites (GSCs) with high strength and sensitivity yet low carbon footprint. The effects of the precursor composition and conductive fillers, i.e., nano carbon black (NCB) and copper coated steel fiber (CSF), on the mechanical and electrical properties were investigated. To achieve high and stable sensitivity, the self-sensing behaviors and underlying mechanisms of hybrid NCB and CSF reinforced GSCs were examined through multiscale microstructural analyses. Pore structures were systematically analyzed using nitrogen adsorption desorption (NAD), mercury intrusion porosimetry (MIP), and X-ray computed tomography (X-CT), while interface microstructure was characterized via scanning electron microscopy (SEM), transmission electron microscopy (TEM), and energy-dispersive spectroscopy (EDS). The results indicate that the hybrid NCB and CSF system forms a three-dimensional reinforcing and continuous conductive network within the cross-linked SiO₄ and AlO₄ tetrahedral framework. This synergistic effect significantly enhances the self-sensing performance of GSCs by refining the nanopore structure, improving conductive pathway connectivity, enhancing ductility at low strain levels, and maintaining structural stability under high strain. An optimal GSC mixture composed of 60% ground granulated blast furnace slag, 25% metakaolin, and 15% silica fume manufactured in this study achieved a maximum gauge factor of 3853.4, representing an order-of-magnitude improvement in sensitivity compared to the Portland cement–based counterpart. GSCs demonstrated high potential for SHM application, providing an innovative material manufacturing strategy for next-generation intelligent structure.-
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationAdvanced composites and hybrid materials, Oct. 2025, v. 8, no. 5, 363-
dcterms.isPartOfAdvanced composites and hybrid materials-
dcterms.issued2025-10-
dc.identifier.scopus2-s2.0-105017701001-
dc.identifier.eissn2522-0136-
dc.identifier.artn363-
dc.description.validate202602 bcch-
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumberOA_Scopus/WOSen_US
dc.description.fundingSourceOthersen_US
dc.description.fundingTextThis work was supported by the National Natural Science Foundation of China (52378257 and U2001225), Fundamental Research Funds for the Central Universities (22120230174), Open Funds of Ningbo Institute of Materials Technology and Engineering, Chinese Academy of Sciences (2024K08), and the Science and Technology Program of Jiaxing, Zhejiang Province (2023AY11039). This work was also supported by Geopoly ® (Shanghai, China).en_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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