Nonlinear Poisson's Ratio for Modeling Hyperelastic Capacitive Sensors

Abstract

Highly stretchable capacitive sensors are of great interest for soft robotic control due to their ability to measure relatively large strains. These sensors are often multilayered materials, with one or more of the layers made from silicones filled with functional particles. However, the models used to describe the material behavior do not always account for the hyperelastic nature of the silicones, the altered material properties due to fillers, and potential anisotropy due to the layered structure. Large errors arise when predicting capacitance using widespread assumptions of linear elastic mechanics and isotropic material properties. This study demonstrates how these modeling assumptions are inadequate for predicting sensor performance, and compares alternative models based on empirical material mechanics. The Poisson's ratio of multi‐layered hyperelastic capacitors is measured in both the width and thickness directions by imaging the sensor dimensions during strain. The results indicate that the sensors are anisotropic and have a strain‐dependent Poisson's ratio, demonstrating the validity of the proposed model. Considering these properties in capacitance models will lead to an improved ability to predict sensor performance, especially at high strains.

Are Liquid Metals Bulk Conductors?

“…While authors typically assume a constant Poisson's ratio, such as 0.5, we have found that silicones, such as Dragon Skin, can have nonconstant Poisson's ratio. [ 50 ] An interesting open problem complicating all of these proposed studies is how to unify the theory for the electromechanical response of pure EGaIn traces, LMEEs, and bGaIn. For example, should bGaIn be modeled more like EGaIn, or as a tortuous LMEE‐like conductive network?…”

Stretchable, Breathable, and Washable Fabric Sensor for Human Motion Monitoring

“…However, continuous non‐linear models may be helpful to further predict sensor performance for a wide range of sensor designs. As it is known that the Poisson's ratio of elastic and porous systems is dependent on strain, [ 58 ] we speculate that there further exists a dependence between the dielectric properties of the sensors to strain, as the fabric's microstructure undergoes compression during stretch inducing changes in the effective dielectric constant. Similar results have been observed in microstructure capacitive pressure sensors where the effective dielectric constant changes with the displaced air in the dielectric layer upon compression.…”

“…The nonlinearity in the relative capacitance of our sensors can be explained by changes in the mesostructure of the fabric dielectric layer under strain, such as reduction of the porosity, [56] partial alignment of the fibers, [57] and compressive deformation. [58,59] For the purpose of our analysis, we define three linear strain regions: 𝜖 < 25%, 25% <𝜖 < 50%, 𝜖 > 50%.…”

Characterization of Temperature and Humidity Dependence in Soft Elastomer Behavior

“…Capacitive sensors were manufactured similar to the method described in an earlier work. 14 , 17 In short, expanded intercalated graphite (EIG) was prepared as conductive filler for the sensor electrodes. Expandable graphite (5 g; Sigma Aldrich) was expanded at 800°C and soaked in cyclohexane (0.5 L; Thermo Fisher Scientific).…”

“…The base materials in soft robots' comprising structures, actuators, 10–13 and sensors 14–17 are often commercial silicones. These materials are attractive to use because they can often stretch to very large strains (>50%) and are easy to process.…”