Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 224

The DOI matches its Crossref record.

A metal–polymer composite with unusual properties

Open access
Bloor, D, Donnelly, K, Hands, P J, Laughlin, P, Lussey, D·2005·Journal of Physics D: Applied Physics

Abstract

Electrically conductive composites that contain conductive filler dispersed in an insulating polymer matrix are usually prepared by the vigorous mixing of the components. This affects the structure of the filler particles and thereby the properties of the composite. It is shown that by careful mixing nano-scale features on the surface of the filler particles can be retained. The fillers used possess sharp surface protrusions similar to the tips used in scanning tunnelling microscopy. The electric field strength at these tips is very large and results in field assisted (Fowler–Nordheim) tunnelling. In addition the polymer matrix intimately coats the filler particles and the particles do not come into direct physical contact. This prevents the formation of chains of filler particles in close contact as the filler content increases. In consequence the composite has an extremely high resistance even at filler loadings above the expected percolation threshold. The retention of filler particle morphology and the presence of an insulating polymer layer between them endow the composite with a number of unusual properties. These are presented here together with appropriate physical models.

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 · 10.1088/0022-3727/38/16/018

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.

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

Cited by

See all 224

Metadata

Authors
Bloor, D., Donnelly, K., Hands, P. J., Laughlin, P., & Lussey, D.
Venue
Journal of Physics D: Applied Physics
Published
2005-08-05
Volume
38
Issue
16
Pages
2851-2860
ISSN
  • 0022-3727 (ISSN-L)
  • 1361-6463
OpenAlex
W2008075367
Cited by
224
References
0
FWCI
5.04
Type
journal article
Language
en
Open access
bronze

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: A metal–polymer composite with unusual properties. https://app.cochat.ai/papers/10.1088/0022-3727/38/16/018
The paper
Bloor, D., Donnelly, K., Hands, P. J., Laughlin, P., & Lussey, D. (2005). A metal–polymer composite with unusual properties. Journal of Physics D: Applied Physics. https://doi.org/10.1088/0022-3727/38/16/018

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.