Micromesh reinforced strain sensor with high stretchability and stability for full‐range and periodic human motions monitoring

Abstract The development of strain sensors with high stretchability and stability is an inevitable requirement for achieving full‐range and long‐term use of wearable electronic devices. Herein, a resistive micromesh reinforced strain sensor (MRSS) with high stretchability and stability is prepared,...

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Bibliographic Details
Main Authors: Haidong Liu, Chang Liu, Jinan Luo, Hao Tang, Yuanfang Li, Houfang Liu, Jingzhi Wu, Fei Han, Zhiyuan Liu, Jianhe Guo, Rongwei Tan, Tian‐Ling Ren, Yancong Qiao, Jianhua Zhou
Format: Article
Language:English
Published: Wiley 2024-04-01
Series:InfoMat
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Online Access:https://doi.org/10.1002/inf2.12511
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Summary:Abstract The development of strain sensors with high stretchability and stability is an inevitable requirement for achieving full‐range and long‐term use of wearable electronic devices. Herein, a resistive micromesh reinforced strain sensor (MRSS) with high stretchability and stability is prepared, consisting of a laser‐scribed graphene (LSG) layer and two styrene‐block‐poly(ethylene‐ran‐butylene)‐block‐poly‐styrene micromesh layers embedded in Ecoflex. The micromesh reinforced structure endows the MRSS with combined characteristics of a high stretchability (120%), excellent stability (with a repetition error of 0.8% after 11 000 cycles), and outstanding sensitivity (gauge factor up to 2692 beyond 100%). Impressively, the MRSS can still be used continauously within the working range without damage, even if stretched to 300%. Furthermore, compared with different structure sensors, the mechanism of the MRSS with high stretchability and stability is elucidated. What's more, a multilayer finite element model, based on the layered structure of the LSG and the morphology of the cracks, is proposed to investigate the strain sensing behavior and failure mechanism of the MRSS. Finally, due to the outstanding performance, the MRSS not only performes well in monitoring full‐range human motions, but also achieves intelligent recognitions of various respiratory activities and gestures assisted by neural network algorithms (the accuracy up to 94.29% and 100%, respectively). This work provides a new approach for designing high‐performance resistive strain sensors and shows great potential in full‐range and long‐term intelligent health management and human–machine interactions applications.
ISSN:2567-3165