The DOI matches its Crossref record; 16 of the 16 references it cites were found in a registry or an index.
Carbon Nanotubes Reinforced Nylon-6 Composite Prepared by Simple Melt-Compounding
Abstract
Because of their high aspect ratio, nanosize in diam-eter, very low density, and, more importantly, excellent physical properties (such as extremely high mechanical strength, high electrical and thermal conductivity),1 carbon nanotubes (CNTs) have been considered as ideal reinforcing fillers in polymer nanocomposites with high performance2-4 and multifunctions.5-9 The challenges for developing high-performance CNTs/polymer nano-composites are (i) homogeneous dispersion of CNTs in the polymeric matrix and (ii) strong interfacial interac-tions so as to effect efficient load transfer from the polymeric matrix to the CNTs. Without chemically bonding, load transfer between the CNTs and the matrix mainly comes from electrostatic and van der Waals interactions.10 Much efficiency of load transfer
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Citations
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Cited by
Carbon nanotube–polymer composites: Chemistry, processing, mechanical and electrical properties
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Mechanical Reinforcement of Polymers Using Carbon Nanotubes
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Structural and mechanical properties of polymer nanocomposites
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A review of stimuli-responsive shape memory polymer composites
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Polyethylene multiwalled carbon nanotube composites
McNally, T., Pötschke, P., Halley, P., Murphy, M., Martin, D., Bell, S. E. J., Brennan, G. P., Bein, D., Lemoine, P., & Quinn, J. P. (2005) · Polymer · doi:10.1016/j.polymer.2005.06.094 · Cited by 802
Metadata
- Authors
- Zhang, W. D., Shen, L., Phang, I. Y., & Liu, T.
- Venue
- Macromolecules
- Publisher
- American Chemical Society (ACS)
- Published
- 2003-12-24
- Volume
- 37
- Issue
- 2
- Pages
- 256-259
- ISSN
- 0024-9297 (ISSN-L)
- 1520-5835
- OpenAlex
- W2001741130
- Cited by
- 461
- References
- 16
- FWCI
- 11.87
- Type
- journal article
- Language
- en
- Open access
- closed
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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.
