Facile fabrication of silicone rubber composite foam with dual conductive networks and tunable porosity for intelligent sensing

In this work, silicone rubber based on conductive polymer composites containing carbon nanotubes (CNTs) and synergetic reduced graphene oxide (rGO) was used to fabricate highly elastic sensors through a simple strategy. Notably, the porosity of the sensor is tunable by incorporating the different sized inorganic salt particles. The porosity and filler conductive networks significantly influenced the sensing performance of the sensor. Benefiting from the controllable porosity and synergistic effect, the sensor exhibits a high conductivity of 2.8 x 10(-4) (S/m), high strain sensitivity (0-2.5%, GF = 14.18; 21-35%, GF = 13.1), high pressure sensitivity (0-2.5%, S = 3.4 kPa(-1); 2.5-6.3%, S = 0.26 kPa(-1); 6.3-12%, S = 0.03 kPa(-1)), high linearity (R-2 > 0.97), fast response (similar to 97 ms), and good repeatability (1000 cycles). Based on these good sensing performances, the sensor is applied to detect both physiological activities (the pulse signal from arteries) and movements of the human body (bending of fingers, arms and knees), measure pressure distribution and identify temperature.

Automated summary

In this study, a highly elastic sensor was fabricated using silicone rubber based on conductive polymer composites containing carbon nanotubes and reduced graphene oxide. The sensor's performance was significantly influenced by the porosity and filler conductive networks. The sensor exhibited high conductivity, strain sensitivity, pressure sensitivity, linearity, response time, and repeatability, making it suitable for detecting physiological activities, human body movements, pressure distribution, and temperature identification.