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Polymer Composites (Self-Sensing) | Piezoresistive Network using SWCNT
Mechanical strain perturbs nanotube–nanotube spacing and contact topology, converting deformation into a measurable resistance change through percolation and electron tunneling pathways.
Introduction

Self-Sensing Composites | SWCNT

Technical Summary

This application note explains how SWCNT-enabled conductive networks in polymer composites convert strain and damage into resistance change for in-situ structural feedback.

Material Type
Single-walled carbon nanotubes (SWCNT)
Primary Function
Piezoresistive self-sensing
Key Mechanism
Percolation network + tunneling/contact resistance modulation
Application Area
Polymer matrix composites (structural health monitoring)
Self-Sensing Composites | SWCNT SWCNT networks convert strain/damage into resistance change by shifting percolation contacts and tunneling gaps, enabling self-sensing. SWCNT

Direct Answer

SWCNT enables self-sensing polymer composites by forming a sparse conductive network where strain shifts nanotube spacing and contacts, changing tunneling/contact resistance and producing a resistance signal correlated to deformation and damage.

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Why This Material Is Considered

SWCNT is used when the composite must remain polymer-dominant mechanically while still supporting a conductive pathway at low filler loading. High aspect ratio lowers the percolation threshold, and the measurable signal is often dominated by junction resistance rather than bulk filler resistivity.

Governing Mechanisms & Activation

  • Network formation: SWCNT forms an interconnected pathway once the system crosses the percolation threshold (geometry + processing controlled).
  • Tunneling/contact control: Small changes in nanotube junction gap distance under strain change tunneling probability and contact resistance.
  • Topology change under load: Microcracks and debonding re-route current paths; resistance increases as conductive bridges are disrupted.
  • Processing dependency: Conductive continuity is gated by dispersion quality; poor distribution increases isolated clusters and unstable signals.

Variables That Typically Matter

  • SWCNT loading vs. target resistivity: Sensitivity often peaks near the percolation threshold; far above it, the signal can flatten.
  • Matrix viscosity and shear history: Controls bundle breakup vs. tube damage; sets final network topology.
  • Interfacial wetting and cure shrinkage: Tightens/loosens junction gaps, shifting baseline resistance and gauge factor.
  • Route choice: Slurry vs. powder processing changes debundling workload and effective percolation point.
  • Damage mode: Matrix microcracking vs. fiber breakage produces different resistance signatures and hysteresis.
  • Thermal cycling: Expansion mismatch changes junction spacing, causing baseline drift if unmanaged.

Known Constraints & Failure Sensitivities

Non-Applicability: If the process window cannot achieve stable dispersion (e.g., viscosity limits prevent adequate shear/mixing), SWCNT networks remain discontinuous and self-sensing becomes noise-dominant.

Unknown/Unverified: Long-term gauge stability (baseline drift + hysteresis) under combined humidity and thermal cycling is formulation-specific and not universally predictable from loading alone.

Activation Boundary: Below the effective percolation point, the composite remains insulating and strain response is typically not measurable; in practice, self-sensing usually requires bulk resistivity below about 1e8 to 1e9 ohm-cm (target dependent).

A common failure sensitivity is re-bundling or agglomeration, which localizes current paths and destabilizes resistance under cyclic loading.

Data Confidence

Mechanisms summarized here follow established CNT/polymer literature on electrical percolation and piezoresistive sensing: junction-dominated conduction near threshold, tunneling/contact modulation under strain, and topology-driven signal amplification during damage evolution.

Last Updated: 2026-01-21