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Graphene-based nanocomposite strain sensor response to ultrasonic guided waves
- Source :
- Composites Science and Technology. 174:42-49
- Publication Year :
- 2019
- Publisher :
- Elsevier BV, 2019.
-
Abstract
- Certain traditional sensors like lead zirconate titanate (PZT) wafers and ultrasonic probes can respond to extremely weak disturbances such as ultrasonic guided waves (UGWs). However, their further development for applications to meet increasing engineering demands is limited on account of their hardness, brittleness, and complex manufacturing processes. Now, emerging nanotechnology ushers in a brand-new world for nanocomposite-based strain sensors, endowing them with higher flexibility, better surface compatibility and easier fabrication. Yet there are few reports of composites which can be used to perceive high frequency UGWs with an ultralow magnitude. Here, we present a novel graphene-based nanocomposite possessing strong sensitivity for sensing ultrasonic waves by virtue of a neoteric sensing mechanism − the tunneling effect. By designing and optimizing the microstructure of the conductive network in the nanocomposite sensor, we successfully capture ultrasonic waves with high signal-to-noise ratio in a broad frequency range up to 1 MHz. With the feature of high sensitivity and rapid response times, the graphene-based nanocomposite becomes a promising candidate for structural health monitoring in developing prospective applications.
- Subjects :
- Fabrication
Materials science
Nanocomposite
Graphene
General Engineering
Nanotechnology
02 engineering and technology
010402 general chemistry
021001 nanoscience & nanotechnology
Microstructure
Lead zirconate titanate
01 natural sciences
0104 chemical sciences
law.invention
chemistry.chemical_compound
chemistry
law
Ceramics and Composites
Ultrasonic sensor
Wafer
Structural health monitoring
Composite material
0210 nano-technology
Subjects
Details
- ISSN :
- 02663538
- Volume :
- 174
- Database :
- OpenAIRE
- Journal :
- Composites Science and Technology
- Accession number :
- edsair.doi...........55bcf093447f350e7f24570f6e22d7d9
- Full Text :
- https://doi.org/10.1016/j.compscitech.2019.02.011