RESUMEN
Printed strain sensors will be important in applications such as wearable devices, which monitor breathing and heart function. Such sensors need to combine high sensitivity and low resistance with other factors such as cyclability, low hysteresis, and minimal frequency/strain-rate dependence. Although nanocomposite sensors can display a high gauge factor (G), they often perform poorly in the other areas. Recently, evidence has been growing that printed, polymer-free networks of nanoparticles, such as graphene nanosheets, display very good all-round sensing performance, although the details of the sensing mechanism are poorly understood. Here, we perform a detailed characterization of the thickness dependence of piezoresistive sensors based on printed networks of graphene nanosheets. We find both conductivity and gauge factor to display percolative behavior at low network thickness but bulk-like behavior for networks above â¼100 nm thick. We use percolation theory to derive an equation for gauge factor as a function of network thickness, which well-describes the observed thickness dependence, including the divergence in gauge factor as the percolation threshold is approached. Our analysis shows that the dominant contributor to the sensor performance is not the effect of strain on internanosheet junctions but the strain-induced modification of the network structure. Finally, we find these networks display excellent cyclability, hysteresis, and frequency/strain-rate dependence as well as gauge factors as high as 350.
RESUMEN
Conductive nanocomposites are often piezoresistive, displaying significant changes in resistance upon deformation, making them ideal for use as strain and pressure sensors. Such composites typically consist of ductile polymers filled with conductive nanomaterials, such as graphene nanosheets or carbon nanotubes, and can display sensitivities, or gauge factors, which are much higher than those of traditional metal strain gauges. However, their development has been hampered by the absence of physical models that could be used to fit data or to optimize sensor performance. Here we develop a simple model which results in equations for nanocomposite gauge factors as a function of both filler volume fraction and composite conductivity. These equations can be used to fit experimental data, outputting figures of merit, or predict experimental data once certain physical parameters are known. We have found these equations to match experimental data, both measured here and extracted from the literature, extremely well. Importantly, the model shows the response of composite strain sensors to be more complex than previously thought and shows factors other than the effect of strain on the interparticle resistance to be performance limiting.