The DOI matches its Crossref record.
Reinforcement of Polymers with Carbon Nanotubes: The Role of Nanotube Surface Area
Abstract
Tensile tests were carried out on free-standing composite films of poly(vinyl alcohol) and six different types of carbon nanotubes for different nanotube loading levels. Significant increases in Young's modulus by up to a factor of 2 were observed in all cases. Theories such as the rule-of-mixtures or the Halpin-Tsai-theory could not explain the relative differences between composites made from different tube types. However, it is possible to show that the reinforcement scales linearly with the total nanotube surface area in the films, indicating that low diameter multiwall nanotubes are the best tube type for reinforcement. In addition, in all cases crystalline coatings around the nanotubes were detected by calorimetry, suggesting comparible polymer−nanotube interfaces. Thus, the reinforcement appears to be critically dependent on the polymer−nanotube interfacial interaction as previously suggested.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cited by
Carbon nanotube–polymer composites: Chemistry, processing, mechanical and electrical properties
Spitalsky, Z., Tasis, D., Papagelis, K., & Galiotis, C. (2010) · Progress in Polymer Science · doi:10.1016/j.progpolymsci.2009.09.003 · Cited by 3,125
Mechanical Reinforcement of Polymers Using Carbon Nanotubes
Coleman, J. N., Khan, U., & Gun'ko, Y. K. (2006) · Advanced Materials · doi:10.1002/adma.200501851 · Cited by 1,621
Self-citationA review of stimuli-responsive shape memory polymer composites
Meng, H., & Li, G. (2013) · Polymer · doi:10.1016/j.polymer.2013.02.023 · Cited by 1,190
Recent Advances in Research on Carbon Nanotube–Polymer Composites
Byrne, M. T., & Gun'ko, Y. K. (2010) · Advanced Materials · doi:10.1002/adma.200901545 · Cited by 873
Polymer Nanocomposites—A Comparison between Carbon Nanotubes, Graphene, and Clay as Nanofillers
Bhattacharya, M. (2016) · Materials · doi:10.3390/ma9040262 · Cited by 747
A review of shape memory polymer composites and blends
Meng, Q., & Hu, J. (2009) · Composites Part A: Applied Science and Manufacturing · doi:10.1016/j.compositesa.2009.08.011 · Cited by 609
Mechanisms of mechanical reinforcement by graphene and carbon nanotubes in polymer nanocomposites
Papageorgiou, D. G., Li, Z., Liu, M., Kinloch, I. A., & Young, R. J. (2020) · Nanoscale · doi:10.1039/c9nr06952f · Cited by 423
Shape and temperature memory of nanocomposites with broadened glass transition
Miaudet, P., Derré, A., Maugey, M., Zakri, C., Piccione, P. M., Inoubli, R., & Poulin, P. (2007) · Science · doi:10.1126/science.1145593 · Cited by 416
Kuan, H.-C., Ma, C.-C. M., Chang, W.-P., Yuen, S.-M., Wu, H.-H., & Lee, T.-M. (2005) · Composites Science and Technology · doi:10.1016/j.compscitech.2005.02.017 · Cited by 411
Yang, K., Gu, M., Guo, Y., Pan, X., & Mu, G. (2009) · Carbon · doi:10.1016/j.carbon.2009.02.029 · Cited by 408
Liu, L., Barber, A. H., Nuriel, S., & Wagner, H. D. (2005) · Advanced Functional Materials · doi:10.1002/adfm.200400525 · Cited by 381
Chae, H. G., Sreekumar, T. V., Uchida, T., & Kumar, S. (2005) · Polymer · doi:10.1016/j.polymer.2005.08.092 · Cited by 271
Alizadeh, B., Ghorbani, M., & Salehi, M. A. (2016) · Journal of Molecular Liquids · doi:10.1016/j.molliq.2016.04.065 · Cited by 93
Nanotube fibers for electromechanical and shape memory actuators
Viry, L., Mercader, C., Miaudet, P., Zakri, C., Derré, A., Kuhn, A., Maugey, M., & Poulin, P. (2010) · Journal of Materials Chemistry · doi:10.1039/b924430a · Cited by 70
Metadata
- Authors
- Cadek, M., Coleman, J. N., Ryan, K. P., Nicolosi, V., Bister, G., Fonseca, A., Nagy, J. B., Szostak, K., Béguin, F., & Blau, W. J.
- Venue
- Nano Letters
- Publisher
- American Chemical Society (ACS)
- Published
- 2004-01-07
- Volume
- 4
- Issue
- 2
- Pages
- 353-356
- ISSN
- 1530-6984 (ISSN-L)
- 1530-6992
- OpenAlex
- W1982728423
- Cited by
- 487
- References
- 0
- FWCI
- 20.41
- Type
- journal article
- Language
- en
- Open access
- closed
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
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.