Issue 11, 2022

Intelligent and highly sensitive strain sensor based on indium tin oxide micromesh with a high crack density

Abstract

Cracks play an important role in strain sensors. However, a systematic analysis of how cracks influence the strain sensors has not been proposed. In this work, an intelligent and highly sensitive strain sensor based on indium tin oxide (ITO)/polyurethane (PU) micromesh is realized. The micromesh has good skin compatibility, water vapor permeability, and stability. Due to the color of the ITO/PU micromesh, it can be invisible on the skin. Based on the fragility of ITO, the density and resistance of cracks in the micromesh are greatly improved. Therefore, the ITO/PU micromesh strain sensor (IMSS) has an ultrahigh gauge factor (744.3). In addition, a finite element model based on four resistance layers is proposed to explain the performance of the IMSS and show the importance of high-density cracks. Compared with other strain sensors based on low-density cracks, the IMSS based on high-density cracks has larger sensitivity and better linearity. Physiological signals, such as respiration, pulse, and joint motion, can be monitored using the IMSS self-fixed on the skin. Finally, an invisible and artificial throat has been realized by combining the IMSS with a convolutional neural network algorithm. The artificial throat can translate the throat vibrations of the tester automatically with an accuracy of 86.5%. This work has great potential in health care and language function reconstruction.

Graphical abstract: Intelligent and highly sensitive strain sensor based on indium tin oxide micromesh with a high crack density

Supplementary files

Article information

Article type
Paper
Submitted
06 Dec 2021
Accepted
06 Feb 2022
First published
07 Feb 2022

Nanoscale, 2022,14, 4234-4243

Intelligent and highly sensitive strain sensor based on indium tin oxide micromesh with a high crack density

Y. Qiao, H. Tang, H. Liu, J. Jian, S. Ji, F. Han, Z. Liu, Y. Liu, Y. Li, T. Cui, J. Cai, G. Gou, B. Zhou, Y. Yang, T. Ren and J. Zhou, Nanoscale, 2022, 14, 4234 DOI: 10.1039/D1NR08005A

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