Piezoresistivity and mechanical performance of self-sensing cement-based sensors under the influence of seawater

This study investigates the integration of multi-walled carbon nanotubes (MWCNTs) as conductive fillers and self-sensing sensors in cementitious composites. Seawater (SW) was used as mixing water to evaluate its influence on the self-sensing performance, percolation thresholds, and mechanical properties of the composites. A range of analytical techniques: Thermogravimetric Analysis (TGA), X-ray Diffraction (XRD), Inductively Coupled Plasma (ICP), Scanning Electron Microscopy (SEM), and Energy-Dispersive X-ray Spectroscopy (EDS) were employed to examine hydration products and microstructural characteristics. SW enhances early-age hydration and compressive strength, as evidenced by increased heat evolution. The percolation threshold was found to vary with MWCNT dosage and ion concentration in the pore solution. Notably, composites containing 0.7 wt% MWCNTs and 50 wt% SW exhibited the highest fractional change in electrical resistance, indicating superior self-sensing capability. These findings offer valuable insights into the development of seawater-based, self-sensing cementitious materials for smart infrastructure and structural health monitoring applications. • SW enhances hydration and boosts compressive strength after 28 days curing. • Friedel’s salt formation increases in SW-mixed cementitious composites. • 50 % SW blend yields steepest percolation threshold via ion conduction. • Optimal piezoresistivity achieved with 50 wt% SW in cement mixtures. • Ion concentration in 50SW improves self-sensing performance of specimens.

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Publication Details

Journal
Construction and Building Materials
Published
2025-11-13
DOI
https://doi.org/10.1016/j.conbuildmat.2025.144246
Citations
1
Primary Topic
Smart Materials for Construction
Type
article
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Piezoresistivity and mechanical performance of self-sensing cement-based sensors under the influence of seawater

1 citations
Construction and Building Materials
Smart Materials for Construction
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article

Piezoresistivity and mechanical performance of self-sensing cement-based sensors under the influence of seawater

article en
1 citations

Abstract

This study investigates the integration of multi-walled carbon nanotubes (MWCNTs) as conductive fillers and self-sensing sensors in cementitious composites. Seawater (SW) was used as mixing water to evaluate its influence on the self-sensing performance, percolation thresholds, and mechanical properties of the composites. A range of analytical techniques: Thermogravimetric Analysis (TGA), X-ray Diffraction (XRD), Inductively Coupled Plasma (ICP), Scanning Electron Microscopy (SEM), and Energy-Dispersive X-ray Spectroscopy (EDS) were employed to examine hydration products and microstructural characteristics. SW enhances early-age hydration and compressive strength, as evidenced by increased heat evolution. The percolation threshold was found to vary with MWCNT dosage and ion concentration in the pore solution. Notably, composites containing 0.7 wt% MWCNTs and 50 wt% SW exhibited the highest fractional change in electrical resistance, indicating superior self-sensing capability. These findings offer valuable insights into the development of seawater-based, self-sensing cementitious materials for smart infrastructure and structural health monitoring applications. • SW enhances hydration and boosts compressive strength after 28 days curing. • Friedel’s salt formation increases in SW-mixed cementitious composites. • 50 % SW blend yields steepest percolation threshold via ion conduction. • Optimal piezoresistivity achieved with 50 wt% SW in cement mixtures. • Ion concentration in 50SW improves self-sensing performance of specimens.

Construction and Building MaterialsVol. 502
University of Technology Sydney (AU), UNSW Sydney (AU)
Openalex Percentile: Top 30%
Smart Materials for Construction
0.50
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Piezoresistivity and mechanical performance of self-sensing cement-based sensors under the influence of seawater · Construction and Building Materials (2025) | TGRS Research Map | TGRS