Hollow-Structured Graphene–Silicone-Composite-Based Piezoresistive Sensors: Decoupled Property Tuning and Bending Reliability

5 years ago

Hollow-Structured Graphene–Silicone-Composite-Based Piezoresistive Sensors: Decoupled Property Tuning and Bending Reliability

Yan Huang, Ni Zhao, Ningqi Luo, Ching Ping Wong, Shih-Chi Chen, Jing Liu

A versatile flexible piezoresistive sensor should maintain high sensitivity in a wide linear range, and provide a stable and repeatable pressure reading under bending. These properties are often difficult to achieve simultaneously with conventional filler–matrix composite active materials, as tuning of one material component often results in change of multiple sensor properties. Here, a material strategy is developed to realize a 3D graphene–poly(dimethylsiloxane) hollow structure, where the electrical conductivity and mechanical elasticity of the composite can be tuned separately by varying the graphene layer number and the poly(dimethylsiloxane) composition ratio, respectively. As a result, the sensor sensitivity and linear range can be easily improved through a decoupled tuning process, reaching a sensitivity of 15.9 kPa−1 in a 60 kPa linear region, and the sensor also exhibits fast response (1.2 ms rising time) and high stability. Furthermore, by optimizing the density of the graphene percolation network and thickness of the composite, the stability and repeatability of the sensor output under bending are improved, achieving a measurement error below 6% under bending radius variations from −25 to +25 mm. Finally, the potential applications of these sensors in wearable medical devices and robotic vision are explored. A 3D graphene–poly(dimethylsiloxane) hollow-structured composite is developed to independently tune the electrical and mechanical properties of the composite, thus allowing simultaneous improvement of both the sensitivity and linear range of the composite-based piezoresistive sensor. High reliability and repeatability of the sensor output under bending are achieved by optimizing the density of the percolation network and thickness of the hollow structure.

Publisher URL: http://onlinelibrary.wiley.com/resolve/doi

DOI: 10.1002/adma.201702675