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Fabrication and Properties of Carbon Fibers
Open accessAbstract
This paper reviews the research and development activities conducted over the past few decades on carbon fibers. The two most important precursors in the carbon fiber industry are polyacrylonitrile (PAN) and mesophase pitch (MP). The structure and composition of the precursor affect the properties of the resultant carbon fibers significantly. Although the essential processes for carbon fiber production are similar, different precursors require different processing conditions in order to achieve improved performance. The research efforts on process optimization are discussed in this review. The review also attempts to cover the research on other precursor materials developed mainly for the purpose of cost reduction.
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Citations
Cited by
Tjong, S. C. (2013) · Materials Science and Engineering: R: Reports · doi:10.1016/j.mser.2013.08.001 · Cited by 1,155
Figueiredo, P., Lintinen, K., Hirvonen, J. T., Kostiainen, M. A., & Santos, H. A. (2018) · Progress in Materials Science · doi:10.1016/j.pmatsci.2017.12.001 · Cited by 956
Sankaran, S., Deshmukh, K., Ahamed, M. B., & Khadheer Pasha, S. K. (2018) · Composites Part A: Applied Science and Manufacturing · doi:10.1016/j.compositesa.2018.08.006 · Cited by 837
Recent advances in low‐cost carbon fiber manufacture from lignin
Baker, D. A., & Rials, T. G. (2013) · Journal of Applied Polymer Science · doi:10.1002/app.39273 · Cited by 664
Recent advances in carbon nanomaterial-based adsorbents for water purification
Gusain, R., Kumar, N., & Ray, S. S. (2020) · Coordination Chemistry Reviews · doi:10.1016/j.ccr.2019.213111 · Cited by 566
Metadata
- Authors
- Huang, X.
- Venue
- Materials
- Publisher
- MDPI AG
- Published
- 2009-12-16
- Volume
- 2
- Issue
- 4
- Pages
- 2369-2403
- ISSN
- 1996-1944 (ISSN-L)
- OpenAlex
- W2116590770
- Cited by
- 969
- References
- 0
- FWCI
- 15.97
- Type
- journal article
- Language
- en
- Open access
- gold
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.
