A triboelectric nanogenerator powered piezoresistive strain sensing technique insensitive to output variations. (April 2023)

• Record Type: Journal Article
• Authors: Li, Guang; Wu, Shuying; Sha, Zhao; Zhao, Liya; Chu, Dewei; Wang, Chun H.; Peng, Shuhua
• Is Part Of: Nano energy. Volume 108(2023)
• Publication Date: 2023-04
• Subjects: Triboelectric nanogenerator -- Piezoresistive strain sensor -- Output variations; Nanoscience -- Periodicals; Nanotechnology -- Periodicals; Nanostructured materials -- Periodicals; Power resources -- Technological innovations -- Periodicals; Nanoscience; Nanostructured materials; Nanotechnology; Power resources -- Technological innovations; Periodicals; 621.042
• DOI: 10.1016/j.nanoen.2023.108185
• Languages: English
• ISSNs: 2211-2855

Abstract

Abstract: With the increasing trend of self-powered sensing in the era of Internet of Things (IoTs), triboelectric nanogenerator (TENG) sensors have attracted great attention due to their high efficiency, versatile configuration, and low cost. However, because of their inherent variation of outputs due to changing environmental conditions, the output magnitude of TENGs cannot be used directly as the primary sensing signal in practical scenario. To address this issue, herein a new method of extracting sensing signal is proposed that is independent of TENG output variations. The core idea is to split the output current of TENG into two parallel branches containing a piezoresistive strain sensor and reference resistors, respectively. The ratio of the currents in the two branches can be used to accurately determine the applied strain because the ratio is uniquely dependent on the resistance of the piezoresistive sensor and is insensitive to the TENG output magnitude, thus eliminating the effect of output variation on the sensing performance. As demonstrated in this work, a TENG can be used as the power source to activate piezoresistive sensors without knowing its output characteristics, although higher current outputs are preferred to minimise error from noise. This new method provides a new self-powered sensing solution that is invariant to output vairations due to changing environments. Graphical Abstract: Conventional TENG-based sensors directly use the TENG output as the sensing signal, which is inevitably affected by the variations of TENG output resulting from various factors including temperature and humidity fluctuation. A more reliable and output variation-insensitive TENG-based sensing method is proposed in this paper. ga1 Highlights: Piezoresistive strain sensor based on microcracks shows a linear response with high sensitivity. TENG output variations due to environmental interferences or operation condition do not affect the sensing performance. Sensitivity can be tuned by using different reference resistors.