Dual conductive network enabled superhydrophobic and high performance strain sensors with outstanding electro-thermal performance and extremely high gauge factors

By Liwei Lin, Ling Wang, Bei Li, Junchen Luo, Xuewu Huang, Q. Gao, Huaiguo Xue, Jie-feng Gao. 2020

205 citations recorded by the source corpus.

Abstract Conductive nanofiber composites (CNCs) are promising as wearable strain sensors (WSSs) due to their unique porous structure and thus good breathability, flexibility, skin affinity, and so forth. It still remains a great challenge to develop flexible and stretchable CNCs for high performance WSSs that possess a high sensitivity, large working strain and can also be applied in various harsh conditions such as extremely cold and corrosive environment. Here, we propose a facile strategy for preparation of superhydrophobic and multi-functional CNCs with a dual conductive network by sequential decoration of acid modified carbon nanotubes (ACNTs), Ag nanoparticles (AgNPs) and polydimethylsiloxane (PDMS) onto the elastic thermoplastic polyurethanes (TPU) nanofiber surface. The introduction of ACNTs, AgNPs and PDMS significantly improves the Young’s modulus and tensile strength while maintaining the superelasticity of the TPU nanofibrous membrane. The multi-functional CNCs possess high conductivity (up to 3031.5 S/m) and thus the excellent electro-thermal effect and deicing performance. The CNC based strain sensor possesses an extremely large gauge factor of 1.04 × 105 (with the strain ranging from 20% to 70%), which is the highest value ever reported for the CNC strain sensors. Thanks to the high sensitivity, the sensor can be used to monitor and distinguish various body motions including large and subtle human joint movement even in a corrosive condition. The superhydrophobic and multi-functional CNC has potential application prospects in water proof wearable electronics and heaters.

Subfields: Biomedical Engineering, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/1ebb0b565935b1fc98e0b819796a9844a26eed6d