4.8 Article

Ultralightweight and 3D Squeezable Graphene-Polydimethylsiloxane Composite Foams as Piezoresistive Sensors

期刊

ACS APPLIED MATERIALS & INTERFACES
卷 11, 期 38, 页码 35201-35211

出版社

AMER CHEMICAL SOC
DOI: 10.1021/acsami.9b11776

关键词

multilayer graphene; piezoresistive sensor; squeezable sensor; flexible sensor; gait monitoring

资金

  1. University of Groningen
  2. MIT Sea Grants program

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The growing demand for flexible, ultrasensitive, squeezable, skin-mountable, and wearable sensors tailored to the requirements of personalized health-care monitoring has fueled the necessity to explore novel nanomaterial-polymer composite-based sensors. Herein, we report a sensitive, 3D squeezable graphene-polydimethylsiloxane (PDMS) foam-based piezoresistive sensor realized by infusing multilayered graphene nanoparticles into a sugar-scaffolded porous PDMS foam structure. Static and dynamic compressive strain testing of the resulting piezoresistive foam sensors revealed two linear response regions with an average gauge factor of 2.87-8.77 over a strain range of 0-50%. Furthermore, the dynamic stimulus-response revealed the ability of the sensors to effectively track dynamic pressure up to a frequency of 70 Hz. In addition, the sensors displayed a high stability over 36000 cycles of cyclic compressive loading and 100 cycles of complete human gait motion. The 3D sensing foams were applied to experimentally demonstrate accurate human gait monitoring through both simulated gait models and real-time gait characterization experiments. The real-time gait experiments conducted demonstrate that the information of the pressure profile obtained at three locations in the shoe sole could not only differentiate between different kinds of human gaits including walking and running but also identify possible fall conditions. This work also demonstrates the capability of the sensors to differentiate between foot anatomies, such as a flat foot (low central arch) and a medium arch foot, which is biomechanically more efficient. Furthermore, the sensors were able to sense various basic joint movement responses demonstrating their suitability for personalized health-care applications.

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