Flexible and high-performance piezoresistive strain sensors based on carbon nanoparticles@polyurethane sponges. (10th November 2020)

• Record Type: Journal Article
• Authors: Zhang, Xuezhong; Xiang, Dong; Zhu, Wanqiu; Zheng, Yongfeng; Harkin-Jones, Eileen; Wang, Ping; Zhao, Chunxia; Li, Hui; Wang, Bin; Li, Yuntao
• Is Part Of: Composites science and technology. Volume 200(2020)
• Publication Date: 2020-11-10
• Subjects: Piezoresistive -- Strain sensor -- Self-assembly -- Carbon nanotube -- Graphene nanoplatelet; Composite materials -- Periodicals; Composite materials; Fibrous composites; Periodicals; 620.118
• DOI: 10.1016/j.compscitech.2020.108437
• Languages: English
• ISSNs: 0266-3538

Abstract

Abstract: In this work, flexible and high-performance piezoresistive strain sensors were fabricated by simple layer-by-layer electrostatic self-assembly of carbon nanoparticles on commercial polyurethane (PU) sponges. It was shown that the sponge-based strain sensors exhibited obviously positive and negative piezoresistive characteristics under tensile and compressive strains, respectively. The alternate assembly of carbon nanotubes (CNTs) and graphene nanoplatelets (GNPs) contributed to the construction of a more complete conductive network and significantly improved the sensing performance of the sensor due to the synergistic effect between CNTs and GNPs. Compared with the CNT@PU and CNT/GNP@PU sponge strain sensors, the CNT/GNP/CNT@PU sensor had a larger strain detection range and higher linearity. Besides, the CNT/GNP/CNT@PU sponge strain sensor showed high sensitivity (GF = 43, 000 at 60% tensile strain and GF = −1.1 at 50% compressive strain), responsive capability to very small strain (0.05%) and outstanding stability during 3000 loading cycles. Due to its excellent sensing performance, the CNT/GNP/CNT@PU sensor enabled monitoring of various physiological activities, including finger movements, wrist bending and walking etc. In addition, a 5 × 5 sensor array based on the sponge-based strain sensor was prepared to achieve accurate identification of weight distribution. This study provides valuable information for the development of flexible strain sensors with high-performance and low-cost. Graphical abstract: Image 1