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<p>The 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&#xa0;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.</p>

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Manufacturing a low-carbon geopolymer self-sensing composite for intelligent structure

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2025年10月1日

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  • Dongyu Wang,
  • Zuhua Zhang,
  • Siqi Ding,
  • Chaolie Ning,
  • Cheng Shi,
  • Xiaoqing Liu,
  • Qiang Ren,
  • Zhengwu Jiang

摘要

The 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.