Robust Superhydrophobic rGO/PPy/PDMS Coatings on a Polyurethane Sponge for Underwater Pressure and Temperature Sensing

Flexible wearable pressure sensors have attracted great interest from researchers in recent years because of their important applications in human-machine interaction, human behavior detection, medical diagnosis, and other fields. At present, integrating multiple functions such as pressure and temperature sensing and self-cleaning into a single material remains a challenging task. Here, by in situ reduction of graphene oxide (GO) grown on a sponge surface and deposition of polypyrrole (PPy) nanoparticles, we have built a highly sensitive, stable, and multifunctional rGO/PPy/poly(dimethylsiloxane) (PDMS) polyurethane (PU) sponge (GPPS) sensor for the detection of pressure, water level, and temperature. This multifunctional sensor shows excellent pressure-sensing performance, ultrasensitive loading sensing of a leaf (98 mg), and outstanding reproducibility over 5000 cycles. Due to the stability of the superhydrophobic surface water contact angle (WCA) = 153.3 degrees, our sensor can work in an underwater environment, which can sense water levels from 1 cm (similar to 98 Pa) to 40 cm and also a variety of underwater behaviors (knock, ultrasonication, blow, etc.) with high stability. In addition, the sensor can be integrated into a circuit for the water level and pressure detection. The sensor can also be used as a smart underwater-temperature sensor; it shows a linear temperature coefficient of resistance (TCR) of 0.48% degrees C-1 in a temperature range of 35-80 degrees C. This multifunctional sensor shows potential application prospects in wearable electronic devices for sensing.

Automated summary

Flexible wearable pressure sensors have important applications in human-machine interaction, human behavior detection, medical diagnosis, and other fields. A highly sensitive, stable, and multifunctional sensor for the detection of pressure, water level, and temperature has been developed in this study, showing potential application prospects.