Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 667

The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.

In situ Polymerization Approach to Graphene-Reinforced Nylon-6 Composites

Xu, Zhen, Gao, Chao·2010·Macromolecules

Abstract

We reported an efficient method to prepare nylon-6− (PA6−) graphene (NG) composites by in situ polymerization of caprolactam in the presence of graphene oxide (GO). During the polycondensation, GO was thermally reduced to graphene simultaneously. By adjusting the feed ratio of caprolactam to GO, various composites with 0.01−10 wt % content of graphene were obtained. The highly grafting nylon-6 arms on graphene sheets was confirmed by XPS, FTIR, TGA and AFM measurements, showing the grafting content up to 78 wt % and homogeneous 2D brush-like morphology from AFM observations. The efficient polymer-chain grafting makes the graphene homogeneously dispersed in PA6 matrix and depresses the crystallization of PA6 chains. Furthermore, we prepared NG fibers by melt spinning process, and found that the tensile strength increased by 2.1 folds and Young’s modulus increased by 2.4 folds with the graphene loading of 0.1 wt % only, revealing an excellent reinforcement to composites by graphene. The in situ condensation polymerization approach paves the way to prepare graphene-based nanocomposites of condensation polymers with high performances and novel functionalities.

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/ma1009337

Cites

7 of 7 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 7 references

Cited by

See all 667

Metadata

Authors
Xu, Z., & Gao, C.
Venue
Macromolecules
Published
2010-07-19
Volume
43
Issue
16
Pages
6716-6723
ISSN
  • 0024-9297 (ISSN-L)
  • 1520-5835
OpenAlex
W2055055939
Cited by
667
References
7
FWCI
38.73
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: In situ Polymerization Approach to Graphene-Reinforced Nylon-6 Composites. https://app.cochat.ai/papers/10.1021/ma1009337
The paper
Xu, Z., & Gao, C. (2010). In situ Polymerization Approach to Graphene-Reinforced Nylon-6 Composites. Macromolecules. https://doi.org/10.1021/ma1009337

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.