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Cited by 885

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Multiscale Carbon Nanotube−Carbon Fiber Reinforcement for Advanced Epoxy Composites

Bekyarova, E., Thostenson, E. T., Yu, A., Kim, H., Gao, J., Tang, J., Hahn, H. T., Chou, T.-W., Itkis, M. E., Haddon, R. C.·2007·Langmuir

Abstract

We report an approach to the development of advanced structural composites based on engineered multiscale carbon nanotube-carbon fiber reinforcement. Electrophoresis was utilized for the selective deposition of multi- and single-walled carbon nanotubes (CNTs) on woven carbon fabric. The CNT-coated carbon fabric panels were subsequently infiltrated with epoxy resin using vacuum-assisted resin transfer molding (VARTM) to fabricate multiscale hybrid composites in which the nanotubes were completely integrated into the fiber bundles and reinforced the matrix-rich regions. The carbon nanotube/carbon fabric/epoxy composites showed approximately 30% enhancement of the interlaminar shear strength as compared to that of carbon fiber/epoxy composites without carbon nanotubes and demonstrate significantly improved out-of-plane electrical conductivity.

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Metadata

Authors
Bekyarova, E., Thostenson, E. T., Yu, A., Kim, H., Gao, J., Tang, J., Hahn, H. T., Chou, T.-W., Itkis, M. E., & Haddon, R. C.
Venue
Langmuir
Published
2007-02-28
Volume
23
Issue
7
Pages
3970-3974
ISSN
  • 0743-7463 (ISSN-L)
  • 1520-5827
OpenAlex
W2084510125
Cited by
885
References
1
FWCI
13.71
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Multiscale Carbon Nanotube−Carbon Fiber Reinforcement for Advanced Epoxy Composites. https://app.cochat.ai/papers/10.1021/la062743p
The paper
Bekyarova, E., Thostenson, E. T., Yu, A., Kim, H., Gao, J., Tang, J., Hahn, H. T., Chou, T.-W., Itkis, M. E., & Haddon, R. C. (2007). Multiscale Carbon Nanotube−Carbon Fiber Reinforcement for Advanced Epoxy Composites. Langmuir. https://doi.org/10.1021/la062743p

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Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.