Highly sensitive, direction-aware, and transparent strain sensor based on oriented electrospun nanofibers for wearable electronic applications

Wearable strain sensors have made great progress in sensing performance, stretchability and durability. However, practical applications of these sensors are still quite challenging because they are incapable of detecting multi-degree-of-freedom strains due to the interference of multidirectional strains. Herein, a high-sensing performance, direction-aware and transparent strain sensor is reported based on antimony-doped tin oxide oriented nanofiber (ATO-ONF) films prepared by electrospinning. The monolayer ATO-ONF strain sensor shows remarkable anisotropic sensing performance, namely GFs of 250 and 1.2 for the nanofiber orientation and its transverse directions, suggesting the realization of the unidirectional sensing capability of the strain sensor, i.e., only responding to strains along the nanofiber direction. In addition, this strain sensor also exhibits high transparency with a light transmittance of ~ 80%, and excellent sensing performance including high sensitivity, high linearity, low hysteresis, good repeatability and durability (> 2000 cycles). Based on these superior sensing properties, the direction-aware biaxial strain sensor is designed by orthogonally stacking ATO-ONF films, by which the predicted magnitude and direction of the tensile strains agree well with those of the actual strains. Furthermore, the multi-degree-of-freedom applications of direction-aware strain sensors in human motion monitoring and human-machine interaction are demonstrated, showing a great application potential in next generation wearable electronics.

Automated summary

This study reports a high-performance, direction-aware and transparent strain sensor based on antimony-doped tin oxide oriented nanofiber films. The sensor exhibits remarkable anisotropic sensing performance, high transparency, and excellent sensing properties including high sensitivity and durability. It has the potential for multi-degree-of-freedom applications in human motion monitoring and human-machine interaction.