Piezoresistive 3D graphene-PDMS spongy pressure sensors for IoT enabled wearables and smart products

Recently, 3D porous graphene-polymer composite-based piezoresistive sensors have drawn great interest of researchers in the field of flexible electronics owing to their ultralightweight nature, compressability, robustness, and excellent electromechanical properties. In this work, we present a facile recipe for developing repeatable, reliable, and linear 3D graphene-PDMS spongy sensors for internet-of-things (IoT)-enabled wearable systems and smart consumer products. Fundamental morphological characterization and sensing performance assessment of the piezoresistive 3D graphene-polymer sensors were conducted to establish its suitability for the development of squeezable, flexible, and skin-mountable human motion sensors. The density and porosity of the sponges were determined to be 250 mgcm-3 and 74% respectively. Mechanical compressive loading tests conducted on the sensors showed an average elastic modulus as low as ~56.7 kPa. Dynamic compressive force-resistance change response tests conducted on four identical sensors revealed a linear piezoresistive response (in the compressive load range 0.42–3.90 N) with an average force sensitivity of 0.209±0.027 N-1. In addition, an accelerated lifetime test comprising 1500 compressive loading cycles (at 3.90 N uniaxial compressive loading) was conducted to demonstrate the long-term reliability of the sensor. To test the applicability of the sensors in smart wearables, four identical graphene-PDMS sponges were configured on the fingertip regions of a soft nitrile glove to develop a pressure sensing smart glove for real-time haptic pressure monitoring. The sensors were also integrated into Philips electronic shaver to realize smart shaving applications with the ability to monitor shaving motions. Furthermore, the readiness of our system for next-generation IoT-enabled applications was demonstrated by integrating the smart glove with an embedded system software utilizing the Arduino-Uno platform. The system was capable of identifying real-time qualitative pressure distribution across the fingertips while grasping daily life objects, thus establishing the suitability of such sensors for next-generation wearables for prosthetics, consumer devices, and personalized healthcare monitoring devices