Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 323

The DOI matches its Crossref record; 9 of the 9 references it cites were found in a registry or an index.

Hot-Drawing of Single and Multiwall Carbon Nanotube Fibers for High Toughness and Alignment

Miaudet, P., Badaire, S., Maugey, M., Derré, A., Pichot, V., Launois, P., Poulin, P., Zakri, C.·2005·Nano Letters

Abstract

We report a new hot-drawing process for treating wet-spun composite fibers made of single- and multiwall carbon nanotubes and poly(vinyl alcohol). As shown in previous reports, untreated composite nanotube fibers exhibit a very large strain-to-failure, and their toughness, which is the energy needed to break the fibers, exceeds that of any other known materials. However, untreated composite nanotube fibers absorb a very small amount of energy at low strain and become degraded in humid conditions. In this work, we use hot-drawing treatments, a concept inspired from textile technologies, to improve the properties of nanotube/PVA fibers. This treatment yields a crystallinity increase of the PVA and an unprecedented degree of alignment of the nanotubes. These structural modifications lead to a markedly improved energy absorption at low strain and make the fibers resistant to moisture. Hot-drawn nanotube/PVA fibers hold great potential for a number of applications such as bulletproof vests, protective textiles, helmets, and so forth.

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.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1021/nl051419w

Cites

9 of 9 references verified0 citation errors · 0 not checkable

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.

A few free checks a day · papers already verified open instantly · results are public

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

Cites

Show all 9 references

Cited by

See all 323

Metadata

Authors
Miaudet, P., Badaire, S., Maugey, M., Derré, A., Pichot, V., Launois, P., Poulin, P., & Zakri, C.
Venue
Nano Letters
Published
2005-10-11
Volume
5
Issue
11
Pages
2212-2215
ISSN
  • 1530-6984 (ISSN-L)
  • 1530-6992
OpenAlex
W2080360601
Cited by
323
References
9
FWCI
7.86
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: Hot-Drawing of Single and Multiwall Carbon Nanotube Fibers for High Toughness and Alignment. https://app.cochat.ai/papers/10.1021/nl051419w
The paper
Miaudet, P., Badaire, S., Maugey, M., Derré, A., Pichot, V., Launois, P., Poulin, P., & Zakri, C. (2005). Hot-Drawing of Single and Multiwall Carbon Nanotube Fibers for High Toughness and Alignment. Nano Letters. https://doi.org/10.1021/nl051419w

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.