Mechanocombinatorially Screening Sensitivity of Stretchable Strain Sensors

Abstract

are often realized at the expense of stretchability, and vice versa. Hence, developing strain sensors with customizable sensitivity could be vital for reliable sensing. The sensitivity of resistive-type strain sensors is defined by gauge factor, GF = (ΔR/R 0 )/ε, where ΔR is the resistance change with strain, R 0 is the resistance before strain, and ε is the applied strain. [28] Currently, a large number of stretchable strain sensors are developed based on conductive materials, such as carbon nanotubes, graphene, metal networks, and liquid metal. [1,2,26,[29][30][31][32][33][34] The sensitivity is highly scattered and independent due to different sensing materials and diverse fabrication methods (Table S1, Supporting Information). Thus, it still remains a challenge to screen out the specific sensitivity from these traditional strain sensors.The resistive-type stretchable strain sensors are typically composed of conductive films and polymer substrates. [28,35,36] The mechanism involves the transfer of strain from the substrate to the conductive film during stretching, which induces cracks and thus increases electrical resistance; when the strain is released, the resistance returns to its initial value. [6] Hence, the strain distribution of polymer substrates largely determines the resistance-strain behavior of the conductive film, thereby determining sensitivity. According to mechanics of materials, strain is uniformly distributed over a mechanically homogeneous film ( Figure S1, Supporting Information). In contrast, taking a simplest mechanically heterogeneous film for example, strain is redistributed over the film, and local strain is determined by two factors, mechanics and structure parameters ( Figure S2, Supporting Information). Therefore, for the resistive-type stretchable strain sensors, the sensitivity could be screened via strain distribution of substrates. Based on finite element modeling (FEM), strain is indeed redistributed on mechanically heterogeneous substrates, which are composed of low and high modulus regions (Figure 1a,b). Numerous gradient structures can be precisely obtained by changing the parameter of substrates. By combining both mechanics and structure parameters of the substrates, a strategy we termed mechanocombinatorics, strain redistribution could be systematically studied. The strain enhancement is well customized by mechanically combined parameters, modulus ratio and pitch, which can be directly extracted from the strain enhancement library (Figure 1c). Stretchable strain sensors have aroused great interest for their application inhuman activity recognition, health monitoring, and soft robotics. For various scenarios involving the application of different strain ranges, specific sensitivities need to be developed, due to a trade-off between sensor sensitivity and stretchability. Traditional stretchable strain sensors are developed based on conductive sensing materials and still lack the function of customizable sensitivity. A novel strategy of mechanocombinatorics is proposed to scr...

In Situ Dynamic Manipulation of Graphene Strain Sensor with Drastically Sensing Performance Enhancement

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Cyber–Physiochemical Interfaces

“…Tuning strain distribution via deformation regulation is also proven to be a powerful strategy to obtain high sensitive strain sensors . For example, in terms of fiber‐shaped strain sensors, a surface strain redistribution strategy based on microbeads on fibers is proposed for increasing sensitivity (Figure b) .…”

Strategies for Designing Stretchable Strain Sensors and Conductors

“…This is the main reason causing the narrow workable strain range. For sensors based on a cracking mechanism, which will be discussed in the next section, the stretchability usually decreases by means that increase the sensitivity, e.g., through introducing large and long cracks …”

“…Apart from these piezoresistive mechanisms, a new cracking mechanism inspired by spider's sensory system basing on slit organ ( Figure a–c) . has recently been identified and used to develop highly sensitive sensors.…”