Environmentally Friendly and Sensitive Strain Sensor Based on Multiwalled Carbon Nanotubes/Lignin-Based Carbon Nanofibers

材料科学 环境友好型 碳纳米管 复合材料 极限抗拉强度 碳化 聚丙烯腈 静电纺丝 纳米技术 化学工程 聚合物 扫描电子显微镜 生态学 工程类 生物
作者
Hao Wang,Hanlin Cao,Hong Wu,Xuefeng Zhang,Xue Mao,Liang Wei,Fenglei Zhou,Runjun Sun,Chengkun Liu
出处
期刊:ACS applied nano materials [American Chemical Society]
卷期号:6 (15): 14165-14176 被引量:12
标识
DOI:10.1021/acsanm.3c02073
摘要

The flexible strain sensors have flourished in the field of smart wearables due to their good flexibility and ease of integration with textiles or human skin and have good prospects for application. However, the selected materials of sensing layers are generally unfriendly to the environment, and the tensile range and sensitivity also need to be further improved. Therefore, the preparation of strain sensors with the characteristics of green, environmentally friendly, large tensile range, and high sensitivity has become the main focus of our current research. Lignin as the second most abundant green biomass polymer in nature is of significance for the development of green strain sensors. In this paper, multiwalled carbon nanotubes (MWCNTs)/lignin-based carbon nanofibers (LCNFs) were prepared by electrospinning, preoxidation, and carbonization. Specifically, water-soluble sodium lignosulfonate (SLS) and poly(vinyl alcohol) (PVA) were blended, and MWCNTs were used as functional fillers. The MWCNTs/LCNFs were then coated with polyurethane (PU) film to produce biomass-based strain sensors. The raw materials and solvents used in the preparation of the sensing layer are abundant and environmentally friendly, and the prepared sensor has the advantage of wide stretching range, high sensitivity, and good repeatability due to the synergistic effect of LCNFs and MWCNTs. The GF was 137.3 and 2746.4 in the strain range of 0–160% and 160–240%, respectively, and was able to maintain good repeatability (over 10 000 tensile cycles). In addition, the sensor performed well in terms of human activity monitoring and Bluetooth signal transmission from mobile phones, indicating that the sensor had very good prospects for application in the field of smart wearables.
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