No abstract

Flexible strain sensors have attracted a great amount of attention for promising applications in next-generation artificially intelligent devices. However, it is difficult for conventional planar strain sensors to meet the requirements of miniature size and light weight for flexible electronics. Herein, a highly sensitive and stretchable fiber strain sensor with a millimeter diameter was innovatively fabricated by the capillary tube method to integrate silver nanowires (AgNWs) in polyurethane (PU) fibers. Scanning electron microscopy results demonstrate that AgNWs were embedded into the surface layer of PU fibers and formed completely conductive networks. The unique AgNW networks endow the PU/AgNW fibers with superior electrical conductivity of 3.1 S/cm, high elongation at break of 265%, wide response range of 43%, high gauge factor of 87.6 up to 22% strain, fast response time of 49 ms, and excellent reliability and stability. Such satisfactory stretchability and sensitivity is attributed to the combination of the highly stretchable PU matrix and the embedded architecture of the AgNW conductive network. Moreover, PU/AgNW fibers can be employed as wearable devices to detect various human motions and to drive light-emitting diodes at a lower voltage (2.7 V).

The pressure sensor with high sensitivity and a broad pressure sensing range is highly desired for flexible electronics. Here, a high-performance pressure sensor based on a hybrid structure was facilely fabricated using the glass template method, which consists of polyurethane (PU) mesodomes embedded with gradient-distributed silver nanowire (AgNW). Such a novel hybrid architecture enables the as-prepared PU/AgNW pressure sensor to have high sensitivity as well as a wide detection range. Moreover, the obtained PU/AgNW pressure sensors have a fast response time (20 ms), good cycling stability, and excellent flexibility. The pressure sensor, benefiting from its outstanding comprehensive sensing performance, can be used for expression recognition and human activity monitoring, showing tremendous application potential in wearable devices. The proposed architecture and developed methodology in this work is promising for future flexible electronic applications.