Large-scale fabrication of conductive yarn with synergistic conductive coating for high-efficient strain sensing and photothermal conversion

Abstract

With the rapid development of wearable electronics, conductive yarn strain sensors have attracted much attention due to their excellent flexibility, conformability, and knittability. However, it is still a great challenge to prepare flexible conductive yarn strain sensors with high sensitivity and wide working range simultaneously. Here, a large-scale fabrication of conductive spandex yarn (SY) with synergistic conductive coating composed of lower stable carbon nanotubes (CNTs)-polyaniline (PANi) hybrid layer and upper ultrasensitive cracked PANi layer was successfully achieved via the simple solvent swelling, non-solvent-induced phase separation (NIPS), and in-situ reduction processes. Thanks to the synergistic effect of the double layered conductive coating and its tunable microstructure based on the PANi content, the assembled conductive SY strain sensor exhibits wide working range (0–321 %), high sensitivity (GF is 43, 950, and 2439 for strain range of 0–100 %, 170–270 %, and 280–321 %, respectively), ultralow detection limit (0.5 %), fast response/recovery time (140 ms/160 ms), and excellent fatigue resistance (4000 cycles). As a proof of concept, the strain sensor can be used for wearable applications to achieve the effective detection of full-range human motion and physiologic signals. Besides, it also displays great potential in human-computer interaction for reliable operation of remote-control manipulator and flexible electronic textile for spatial pressure distribution identification. Finally, owing to the excellent optical absorbing ability of PANi and CNTs, the conductive SY exhibits high-efficient and stable photothermal conversion capacity even under the stretching and bending states, endowing it with good wearing comfort. This study provides a convenient but effective strategy for the fabrication of high-performance wearable strain sensor with excellent thermal management capacity.