The DOI matches its Crossref record; 13 of the 13 references it cites were found in a registry or an index.
Strain-dependent electrical resistance of multi-walled carbon nanotube/polymer composite films
Open accessAbstract
The strain-dependent electrical resistance characteristics of multi-walled carbon nanotube (MWCNT)/polymer composite films were investigated. In this research, polyethylene oxide (PEO) is used as the polymer matrix. Two representative volume fractions of MWCNT/PEO composite films were selected: 0.56 vol% (near the percolation threshold) and 1.44 vol% (away from the percolation threshold) of MWCNT. An experimental setup which can measure electrical resistance and strain simultaneously and continuously has been developed. Unique and repeatable relationships in resistance versus strain were obtained for multiple specimens with different volume fractions of MWCNT. The overall pattern of electrical resistance change versus strain for the specimens tested consists of linear and nonlinear regions. A resistance change model to describe the combination of linear and nonlinear modes of electrical resistance change as a function of strain is suggested. The unique characteristics in electrical resistance change for different volume fractions imply that MWCNT/PEO composite films can be used as tunable strain sensors and for application into embedded sensor systems in structures.
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Cited by
Hammock, M. L., Chortos, A., Tee, B. C. ‐., Tok, J. B. ‐., & Bao, Z. (2013) · Advanced Materials · doi:10.1002/adma.201302240 · Cited by 2,396
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Investigation on sensitivity of a polymer/carbon nanotube composite strain sensor
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High‐Strain Sensors Based on ZnO Nanowire/Polystyrene Hybridized Flexible Films
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Graphene-based wearable piezoresistive physical sensors
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Metadata
- Authors
- Park, M., Kim, H., & Youngblood, J. P.
- Venue
- Nanotechnology
- Publisher
- IOP Publishing
- Published
- 2008-01-14
- Volume
- 19
- Issue
- 5
- Pages
- 055705
- ISSN
- 0957-4484 (ISSN-L)
- 1361-6528
- OpenAlex
- W2150351724
- Cited by
- 331
- References
- 13
- FWCI
- 7.58
- Type
- journal article
- Language
- en
- Open access
- green
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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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