Controllable Graphene Wrinkle for a High-Performance Flexible Pressure Sensor

Flexible pressure sensors have aroused tremendous attention, owing to their broad applications in healthcare, robotics, and prosthetics. So far, it remains a critical challenge to develop low-cost and controllable microstructures for flexible pressure sensors. Herein, a high-sensitivity and low-cost flexible piezoresistive sensor was developed by combining a controllable graphene-nanowalls (GNWs) wrinkle and a polydimethylsiloxane (PDMS) elastomer. For the GNWs-PDMS bilayer, the vertically grown GNWs film can effectively improve the interface strength and form delamination-free conformal wrinkles. More importantly, a controllable microstructure can be easily tuned through the thermal wrinkling method. The wrinkled graphene-nanowalls (WG) piezoresistive sensor has a high sensitivity (S = 59.0 kPa(-1) for the 0-2 kPa region and S = 4.8 kPa(-1) for the 2-20 kPa region), a fast response speed (<6.9 ms), and a low limit of detection (LOD) of 2 mg (similar to 0.2 Pa). The finite element method was used to analyze the working mechanism of the sensor, which revealed that the periods of the wrinkles play a dominant role in the performances of the sensors. These prominent merits enable wrinkled graphene sensors to successfully detect various signals from a weak stimulus to large pressures, for example, the detection of weak gas and plantar pressure. Furthermore, object manipulation, tactile imaging, and braille recognition applications have been demonstrated, showing their great potential in prosthetics limbs and intelligent robotics.

Automated summary

This study developed a high-sensitivity and low-cost flexible piezoresistive sensor by combining controllable graphene-nanowalls wrinkle and a polydimethylsiloxane elastomer. The sensor exhibited fast response speed and low limit of detection, with a controllable microstructure allowing successful detection of various signals. The sensor's potential applications in prosthetics limbs and intelligent robotics were demonstrated through object manipulation, tactile imaging, and braille recognition.