Enhanced performance of 3D printed highly elastic strain sensors of carbon nanotube/thermoplastic polyurethane nanocomposites via non-covalent interactions

Abstract

Strain sensors based on conductive polymer composites have been widely investigated due to their excellent elasticity and sensitivity. Such sensors may be manufactured using additive manufacturing techniques but there are some challenges to overcome in terms of performance if this technique is to be used. In this work, a high-performance strain sensor of carbon nanotube/thermoplastic polyurethane (CNT/TPU) nanocomposites was printed by fused deposition modeling (FDM), and 1-pyrenecarboxylic acid (PCA) was introduced to non-covalently modify the CNTs and improve the polymer-nanofiller interactions. It is shown that the tensile and electrical properties of the modified composites are increased as a result of more uniform CNT dispersion. The 3D printed sensors demonstrate excellent properties with high gauge factor (GF = 117213 at a strain of 250%), large detectable strain (0–250%), good stability (up to 1000 loading/unloading cycles) and wide frequency response range of 0.01–1 Hz. Also, the strain sensing ability of the sensor is greatly improved with the introduction of PCA. The working mechanism of strain sensor was further studied based on the Simmons’ tunneling theory. In addition, the sensor demonstrates the capability to monitor human body movements and voice, showing its potential for applications in intelligent robots and wearable electronics where customizability is demanded.