51. CVD growth of fingerprint-like patterned 3D graphene film for an ultrasensitive pressure sensor
- Author
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Yingying Zhang, Qi Wang, Muqiang Jian, Chunya Wang, and Kailun Xia
- Subjects
Materials science ,business.industry ,Graphene ,Pressure sensing ,Nanotechnology ,02 engineering and technology ,010402 general chemistry ,021001 nanoscience & nanotechnology ,Condensed Matter Physics ,01 natural sciences ,Pressure sensor ,Atomic and Molecular Physics, and Optics ,0104 chemical sciences ,law.invention ,Pressure range ,Membrane ,Fingerprint ,law ,General Materials Science ,Electrical and Electronic Engineering ,0210 nano-technology ,business ,Sensitivity (electronics) ,Wearable technology - Abstract
With the rapid development of wearable devices, flexible pressure sensors with high sensitivity and wide workable range are highly desired. In nature, there are many well-adapted structures developed through natural selection, which inspired us for the design of biomimetic materials or devices. Particularly, human fingertip skin, where many epidermal ridges amplify external stimulations, might be a good example to imitate for highly sensitive sensors. In this work, based on unique chemical vapor depositions (CVD)-grown 3D graphene films that mimic the morphology of fingertip skin, we fabricated flexible pressure sensing membranes, which simultaneously showed a high sensitivity of 110 (kPa)−1 for 0–0.2 kPa and wide workable pressure range (up to 75 kPa). Hierarchical structured PDMS films molded from natural leaves were used as the supporting elastic films for the graphene films, which also contribute to the superior performance of the pressure sensors. The pressure sensor showed a low detection limit (0.2 Pa), fast response (< 30 ms), and excellent stability for more than 10,000 loading/unloading cycles. Based on these features, we demonstrated its applications in detecting tiny objects, sound, and human physiological signals, showing its potential in wearable electronics for health monitoring and human/machine interfaces.
- Published
- 2017
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