Carbon nanotube (CNT) and silver-nanoparticle-decorated multi-walled carbon nanotube (AgNP-MWCNT) strain sensors have progressed through three generations in roughly two decades, from randomly dispersed films sensitive only at small strains to aligned and percolating composites with a tunable gage factor (GF) to engineered-crack sensitive or hierarchical hybrids that report GFs above 10 4 . Yet the field has not converged on a shared evaluation framework: published GF values are reported across incommensurate strain windows, hysteresis is more often shown qualitatively than quantified, and durability tests range from 10 2 to 10 5 cycles without justification. In this review, we consider that the central problem of AgNP-MWCNT strain-sensor design is not maximizing any one metric but managing the GF, stretchability, hysteresis, and linearity trade-offs dictated by piezoresistance, tunneling, or crack-mediated conduction that dominates at the operating strain. We critically compare the three competing mechanistic models, propose a normalized reporting standard for performance comparison, and reframe AgNP-MWCNT strain sensors as nodes in intelligent material systems, where model-based calibration, sensor fusion, and embedded health-monitoring, not recorded GF values alone, will determine practical deployment in wearable and structural applications.
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Khan et al. (2026) studied this question.
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