Ultrathin GPU/CNTs@Ag Electrospun Fibers for Use as Strain/Piezoresistive Flexible Wearable Sensors
Carbon-based nanomaterials are excellent candidates for constructing conductive sensing networks in a flexible polymer matrix, which is widely used. However, it remains a challenge to improve the flexibility and sensitivity of multifunctional sensor by synergistically combining several conductive materials in the sensor fabrication processes. In this study, graphene (GR)-dopped thermoplastic polyurethane (TPU) GPU was adopted as the matrix material with surface grafting of carbon nanotubes (CNTs) and silver nanoparticles (Ag) for fabricating fibrous membranes by electrospinning and ultrasonic adsorption. Then, GPU/CNTs@Ag-based sensors were made and tested for their piezoresistive and strain sensing properties. The results showed that GR and Ag nanoparticles increased the initial piezoresistance response, and the piezoresistive sensor had the sensitivity of 0.08 kPa<inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">${}^{-{1}}$ </tex-math></inline-formula> within 0–6 kPa with the response/recovery time of 15/35 ms. The strain sensor performed well up to 400% deformation with a gauge factor (GF) of 349.8 and a response/recovery time of 68/199 ms. The sensors had stability for more than 5000 cycles. The sensors showed excellent detection of human body movements, including limb motion, respiration, and muscle rhythm. A <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$4\times 4$ </tex-math></inline-formula> piezoresistive array was fabricated and the corresponding data acquisition system has been developed to monitor the real-time signals of external stress distribution. Therefore, the GPU/CNTs@Ag sensors fabricated with the novel design strategy demonstrated considerable prospective applications such as human motion detection, smart skin, and machine haptics.
Authors
- Yongling Wu (ORCID: https://orcid.org/0000-0002-0725-8915)
- Hongyu Y. Zheng (ORCID: https://orcid.org/0000-0002-4895-0617)
- Mingming Liu (ORCID: https://orcid.org/0000-0002-8988-2104)
- Ruiyong Yang
Institutions
- Shandong University of Technology (CN)
Publication Details
- Journal
- IEEE Sensors Journal
- Published
- 2025-03-31
- DOI
- https://doi.org/10.1109/jsen.2025.3554561
- Citations
- 4
- Primary Topic
- Advanced Sensor and Energy Harvesting Materials
- Type
- article
- Field-Weighted Citation Impact
- 2.70
Funders
- Natural Science Foundation of Shandong Province
- Taishan Scholar Foundation of Shandong Province