Mechanism of resistance relaxation and hysteresis in viscoelastic piezoresistive polymer nanocomposites
Source abstract
Abstract
Carbon nanotube polymer nanocomposites exhibit outstanding mechanical, electrical, and thermal properties, enabling a myriad of sensor and actuation applications. Piezoresistivity in particular is achieved by the creation of a deformation-sensitive electrical conductor network and is the underlying effect of most structural health and motion sensing. The polymer matrix, however, introduces time-dependent mechanical behavior known as viscoelasticity. Viscoelasticity affects the relationship between relative resistance change and mechanical strain over time and becomes particularly important over long times, as well as at high temperatures, radiation aging, and in the presence of high mechanical stresses. The characterization of these influences on the piezoresistivity is therefore crucial to maintain sensor stability under harsh conditions. While experimental studies have been conducted, the effect of viscoelasticity has not been thorougly analyzed. Here we study resistance relaxation and hysteresis in carbon nanotube nanocomposites under the influence of matrix viscoelasticity. First we characterize the multiaxial viscoelastic behavior directly without invoking the common assumption of constant Poisson’s ratio, which is central to predicting resistnace relaxation and hysteresis. We then apply the viscoelastic master curve to a micromechanics-based numerical piezoresistive model and study the relative resistance change under relaxation, creep, and deformation-controlled cyclic loading. The results are compared to the common assumptions of constant Poisson’s ratio and constant bulk modulus. We show that the time-dependent transverse deformation leads to network compaction and is the mechanism behind resistance relaxation and hysteresis.
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Research context
OpenAlex topics: Carbon Nanotubes in Composites · Conducting polymers and applications · Advanced Sensor and Energy Harvesting Materials
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (55)
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