High sensitive thermoplastic polyurethane/carbon nanotubes strain sensor fitting by a novel optimization empirical model

Abstract A variety of high-performance strain sensors for monitoring changes in physical quantities has attracted considerable interest from academia and industry. In this work, a high sensitive flexible strain sensor is fabricated through electrospun thermoplastic polyurethane (TPU) fibrous film with dip-coating ultrasonication treated carbon nanotubes (CNTs). TPU/CNTs strain sensor exhibits an excellent comprehensive performance of high sensitivity (maximum gauge factor of 1571), outstanding tensile strength and toughness (stress > 24 MPa, strain > 400%), brilliant durability (10000 cycles at 10% strain) and a widely workable stretching range (0 ~ 400%). Based on the properties of high sensitivity, wearable and wide workable, TPU/CNTs strain sensor has been prepared as a simple application for intelligent terminals, e-skins and body activity monitoring. More importantly, this work introduces a novel optimization empirical equation provided by our group to describe and predict the conductive response on the stretching of the sensor. Compared with the general optimization model, our novel optimization empirical model presents a better fitting degree and more similar to the benchmark mathematic model from tunnelling theory. Furthermore, this model provides a good description of the changes in the conductive pathways during the operation of different sensors as well.