Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 185

The DOI matches its Crossref record.

The synthesis of core–shell iron@gold nanoparticles and their characterization

Open access
Ban, Zhihui, Barnakov, Yuri A., Li, Feng, Golub, Vladimir O., O'Connor, Charles J.·2005·Journal of Materials Chemistry

Abstract

Au-coated magnetic Fe nanoparticles have been successfully synthesized by partial replacement reaction in a polar aprotic solvent with about 11 nm core of Fe and about 2.5 nm shell of Au. In this work, a combination of TEM (transmission electron microscopy), XRD (X-ray powder diffractometry), EDS (energy disperse X-ray spectroscopy), SQUID (superconducting quantum interference device), TGA (thermograviometric analysis) and UV–visible absorption spectroscopy were employed to characterize the morphology, structure, composition and magnetic properties of the products. HRTEM images show clear core–shell structure with different crystal lattices from Fe and Au. SQUID magnetometry reveals that particle magnetic properties are not significantly affected by the overlayer of a moderately thick Au shell. The Au-coated particles exhibit a surface plasmon resonance peak that red-shifts from 520 to 680 nm. And all the above characterizations show that in this sample there are no iron oxides inside the particle.

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 · 10.1039/b504304b

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 185

Metadata

Authors
Ban, Z., Barnakov, Y. A., Li, F., Golub, V. O., & O'Connor, C. J.
Venue
Journal of Materials Chemistry
Published
2005
Volume
15
Issue
43
Pages
4660
ISSN
  • 0959-9428 (ISSN-L)
  • 1364-5501
OpenAlex
W2153996213
Cited by
185
References
0
FWCI
3.83
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: The synthesis of core–shell iron@gold nanoparticles and their characterization. https://app.cochat.ai/papers/10.1039/b504304b
The paper
Ban, Z., Barnakov, Y. A., Li, F., Golub, V. O., & O'Connor, C. J. (2005). The synthesis of core–shell iron@gold nanoparticles and their characterization. Journal of Materials Chemistry. https://doi.org/10.1039/b504304b

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.