The DOI matches its Crossref record.
Macroscopic Fibers and Ribbons of Oriented Carbon Nanotubes
Abstract
A simple method was used to assemble single-walled carbon nanotubes into indefinitely long ribbons and fibers. The processing consists of dispersing the nanotubes in surfactant solutions, recondensing the nanotubes in the flow of a polymer solution to form a nanotube mesh, and then collating this mesh to a nanotube fiber. Flow-induced alignment may lead to a preferential orientation of the nanotubes in the mesh that has the form of a ribbon. Unlike classical carbon fibers, the nanotube fibers can be strongly bent without breaking. Their obtained elastic modulus is 10 times higher than the modulus of high-quality bucky paper.
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
Polymer Nanocomposites Containing Carbon Nanotubes
Moniruzzaman, M., & Winey, K. I. (2006) · Macromolecules · doi:10.1021/ma060733p · Cited by 3,416
Dispersion and functionalization of carbon nanotubes for polymer-based nanocomposites: A review
Ma, P.-C., Siddiqui, N. A., Marom, G., & Kim, J.-K. (2010) · Composites Part A: Applied Science and Manufacturing · doi:10.1016/j.compositesa.2010.07.003 · Cited by 3,414
The revolutionary creation of new advanced materials—carbon nanotube composites
Lau, A. K.-T., & Hui, D. (2002) · Composites Part B: Engineering · doi:10.1016/s1359-8368(02)00012-4 · Cited by 1,020
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
Ultrastrong Fibers Assembled from Giant Graphene Oxide Sheets
Xu, Z., Sun, H., Zhao, X., & Gao, C. (2013) · Advanced Materials · doi:10.1002/adma.201203448 · Cited by 699
Metadata
- Authors
- Vigolo, B., Pénicaud, A., Coulon, C., Sauder, C., Pailler, R., Journet, C., Bernier, P., & Poulin, P.
- Venue
- Science
- Published
- 2000-11-17
- Volume
- 290
- Issue
- 5495
- Pages
- 1331-1334
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- OpenAlex
- W2089637736
- Cited by
- 1,851
- References
- 0
- FWCI
- 33.41
- 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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Macroscopic Fibers and Ribbons of Oriented Carbon Nanotubes. https://app.cochat.ai/papers/10.1126/science.290.5495.1331
- The paper
- Vigolo, B., Pénicaud, A., Coulon, C., Sauder, C., Pailler, R., Journet, C., Bernier, P., & Poulin, P. (2000). Macroscopic Fibers and Ribbons of Oriented Carbon Nanotubes. Science. https://doi.org/10.1126/science.290.5495.1331
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.
