4.7 Article

Hierarchical Wrinkles for Tunable Strain Sensing Based on Programmable, Anisotropic, and Patterned Graphene Hybrids

期刊

POLYMERS
卷 14, 期 14, 页码 -

出版社

MDPI
DOI: 10.3390/polym14142800

关键词

reduced graphene oxide (RGO); wrinkle; strain sensors; electronic materials

资金

  1. National Natural Science Foundation of China [52073302]

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This study demonstrates the use of reduced graphene oxide (RGO) with hierarchical oriented wrinkle microstructures, generated using a two-step shrinkage of a rubber substrate, for preparing high-performance electronic materials with adjustable strain sensitivity and different levels of wrinkles. The sensors exhibit improved GF values range and stability, showing potential for monitoring vital signs and large motions in various health or motion monitoring fields.
Flexible, stretchable, wearable, and stable electronic materials are widely studied, owing to their applications in wearable devices and the Internet of Things. Because of the demands for both strain-insensitive resistors and high gauge factor (GF) strain-sensitive materials, anisotropic strain sensitivity has been an important aspect of electronic materials. In addition, the materials should have adjustable strain sensitivities. In this work, such properties are demonstrated in reduced graphene oxide (RGO) with hierarchical oriented wrinkle microstructures, generated using the two-step shrinkage of a rubber substrate. The GF values range from 0.15 to 28.32 at 100% strain. For device demonstrations, macrostructure patterns are designed to prepare patterned wrinkling graphene at rubber substrate (PWG@R). Serpentiform curves can be used for the constant-value resistor, combined with the first-grade wrinkles. Strip lines can increase the strain-sensing property, along with the second-grade wrinkles. The patterned sensor exhibits improved GF values range from 0.05 to 49.5. The assembled sensor shows an excellent stability (>99% retention after 600 cycles) with a high GF (49.5). It can monitor the vital signs of the throat and wrist and sense large motions of fingers. Thus, PWG@R-based strain sensors have great potential in various health or motion monitoring fields.

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