The DOI matches its Crossref record; 53 of the 53 references it cites were found in a registry or an index.
Epidermis Microstructure Inspired Graphene Pressure Sensor with Random Distributed Spinosum for High Sensitivity and Large Linearity
Abstract
Recently, wearable pressure sensors have attracted tremendous attention because of their potential applications in monitoring physiological signals for human healthcare. Sensitivity and linearity are the two most essential parameters for pressure sensors. Although various designed micro/nanostructure morphologies have been introduced, the trade-off between sensitivity and linearity has not been well balanced. Human skin, which contains force receptors in a reticular layer, has a high sensitivity even for large external stimuli. Herein, inspired by the skin epidermis with high-performance force sensing, we have proposed a special surface morphology with spinosum microstructure of random distribution via the combination of an abrasive paper template and reduced graphene oxide. The sensitivity of the graphene pressure sensor with random distribution spinosum (RDS) microstructure is as high as 25.1 kPa –1 in a wide linearity range of 0–2.6 kPa. Our pressure sensor exhibits superior comprehensive properties compared with previous surface-modified pressure sensors. According to simulation and mechanism analyses, the spinosum microstructure and random distribution contribute to the high sensitivity and large linearity range, respectively. In addition, the pressure sensor shows promising potential in detecting human physiological signals, such as heartbeat, respiration, phonation, and human motions of a pushup, arm bending, and walking. The wearable pressure sensor array was further used to detect gait states of supination, neutral, and pronation. The RDS microstructure provides an alternative strategy to improve the performance of pressure sensors and extend their potential applications in monitoring human activities.
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Metadata
- Authors
- Pang, Y., Zhang, K., Yang, Z., Jiang, S., Ju, Z., Li, Y., Wang, X., Wang, D., Jian, M., Zhang, Y., Liang, R., Tian, H., Yang, Y., & Ren, T.-L.
- Venue
- ACS Nano
- Publisher
- American Chemical Society (ACS)
- Published
- 2018-01-29
- Volume
- 12
- Issue
- 3
- Pages
- 2346-2354
- ISSN
- 1936-0851 (ISSN-L)
- 1936-086X
- OpenAlex
- W2785597507
- Cited by
- 774
- References
- 53
- FWCI
- 29.16
- Type
- journal article
- Language
- en
- Open access
- closed
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