The DOI matches its Crossref record; 5 of the 5 references it cites were found in a registry or an index.
Highly Stretchable and Sensitive Strain Sensors Using Fragmentized Graphene Foam
Abstract
Stretchable electronics have recently been extensively investigated for the development of highly advanced human‐interactive devices. Here, a highly stretchable and sensitive strain sensor is fabricated based on the composite of fragmentized graphene foam (FGF) and polydimethylsiloxane (PDMS). A graphene foam (GF) is disintegrated into 200–300 μm sized fragments while maintaining its 3D structure by using a vortex mixer, forming a percolation network of the FGFs. The strain sensor shows high sensitivity with a gauge factor of 15 to 29, which is much higher compared to the GF/PDMS strain sensor with a gauge factor of 2.2. It is attributed to the great change in the contact resistance between FGFs over the large contact area, when stretched. In addition to the high sensitivity, the FGF/PDMS strain sensor exhibits high stretchability over 70% and high durability over 10 000 stretching‐releasing cycles. When the sensor is attached to the human body, it functions as a health‐monitoring device by detecting various human motions such as the bending of elbows and fingers in addition to the pulse of radial artery. Finally, by using the FGF, PDMS, and μ‐LEDs, a stretchable touch sensor array is fabricated, thus demonstrating its potential application as an artificial skin.
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Kim, D.-H., Lu, N., Ma, R., Kim, Y.-S., Kim, R.-H., Wang, S., Wu, J., Won, S. M., Tao, H., Islam, A., et al. (2011) · Science · doi:10.1126/science.1206157 · Cited by 4,836
Highly Stretchable and Sensitive Strain Sensor Based on Silver Nanowire–Elastomer Nanocomposite
Amjadi, M., Pichitpajongkit, A., Lee, S., Ryu, S., & Park, I. (2014) · ACS Nano · doi:10.1021/nn501204t · Cited by 2,350
Self-citationHighly Stretchable Piezoresistive Graphene–Nanocellulose Nanopaper for Strain Sensors
Yan, C., Wang, J., Kang, W., Cui, M., Wang, X., Foo, C. Y., Chee, K. J., & Lee, P. S. (2014) · Advanced Materials · doi:10.1002/adma.201304742 · Cited by 1,179
Sensitive, High-Strain, High-Rate Bodily Motion Sensors Based on Graphene–Rubber Composites
Boland, C. S., Khan, U., Backes, C., O’Neill, A., McCauley, J., Duane, S., Shanker, R., Liu, Y., Jurewicz, I., Dalton, A. B., et al. (2014) · ACS Nano · doi:10.1021/nn503454h · Cited by 793
Park, S., Kim, H., Vosgueritchian, M., Cheon, S., Kim, H., Koo, J. H., Kim, T. R., Lee, S., Schwartz, G., Chang, H., et al. (2014) · Advanced Materials · doi:10.1002/adma.201402574 · Cited by 565
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Cited by
Stretchable, Skin-Mountable, and Wearable Strain Sensors and Their Potential Applications: A Review
Amjadi, M., Kyung, K., Park, I., & Sitti, M. (2016) · Advanced Functional Materials · doi:10.1002/adfm.201504755 · Cited by 3,202
Bio-Integrated Wearable Systems: A Comprehensive Review
Ray, T. R., Choi, J., Bandodkar, A. J., Krishnan, S., Gutruf, P., Tian, L., Ghaffari, R., & Rogers, J. A. (2019) · Chemical Reviews · doi:10.1021/acs.chemrev.8b00573 · Cited by 1,350
Cai, G., Wang, J., Qian, K., Chen, J., Li, S., & Lee, P. S. (2017) · Advanced Science · doi:10.1002/advs.201600190 · Cited by 921
Liao, M., Wan, P., Wen, J., Gong, M., Wu, X., Wang, Y., Shi, R., & Zhang, L. (2017) · Advanced Functional Materials · doi:10.1002/adfm.201703852 · Cited by 760
Liu, Q., Chen, J., Li, Y., & Shi, G. (2016) · ACS Nano · doi:10.1021/acsnano.6b03813 · Cited by 609
Metadata
- Authors
- Jeong, Y. R., Park, H., Jin, S. W., Hong, S. Y., Lee, S., & Ha, J. S.
- Venue
- Advanced Functional Materials
- Publisher
- Wiley
- Published
- 2015-05-27
- Volume
- 25
- Issue
- 27
- Pages
- 4228-4236
- ISSN
- 1616-301X (ISSN-L)
- 1616-3028
- OpenAlex
- W1482619460
- Cited by
- 641
- References
- 5
- FWCI
- 30.04
- Type
- journal article
- Language
- en
- Open access
- closed
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- Jeong, Y. R., Park, H., Jin, S. W., Hong, S. Y., Lee, S., & Ha, J. S. (2015). Highly Stretchable and Sensitive Strain Sensors Using Fragmentized Graphene Foam. Advanced Functional Materials. https://doi.org/10.1002/adfm.201501000
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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