Student or educator? Sign up with your school email and get 6 months of Pro free.
CoChat
Sign Up
Cited by 253

The DOI matches its Crossref record; 49 of the 49 references it cites were found in a registry or an index.

Rapid, Solventless, Bulk Preparation of Metal Nanoparticle-Decorated Carbon Nanotubes

Lin, Yi, Watson, Kent A., Fallbach, Michael J., Ghose, Sayata, Smith, Joseph G., Delozier, Donavon M., Cao, Wei, Crooks, Roy E., Connell, John W.·2009·ACS Nano
DOI 10.1021/nn8009097
Open this paper in CoChat — free account

Abstract

A rapid, solventless method is described for the decoration of carbon nanotubes with metal nanoparticles. The straightforward two-step process utilizes neither reducing agents nor electric current and involves the dry mixing of a precursor metal salt (e.g., a metal acetate) with carbon nanotubes (single- or multi-walled) followed by heating in an inert atmosphere. The procedure is scalable to multigram quantities and generally applicable to various other carbon substrates (e.g., carbon nanofiber, expanded graphite, and carbon black) and many metal salts (e.g., Ag, Au, Co, Ni, and Pd acetates). As a model system, Ag nanoparticle-decorated carbon nanotube samples were prepared under various mixing techniques, metal loading levels, thermal treatment temperatures, and nanotube oxidative acid treatments. These nanohybrids were characterized by a variety of microscopic and spectroscopic techniques. For example, X-ray diffraction and scanning electron microscopy indicated that the average size of the Ag nanoparticles has little to do with the thermal treatment temperature but can be easily controlled by varying the Ag loading. Raman spectroscopy illustrated both the metal-nanotube electronic interactions and the surface enhancement effect from the Ag nanoparticle attachment. High-resolution transmission electron microscopy captured the in situ salt-to-metal conversion events on the nanotube surface. The mechanistic implications from the characterization results are discussed.

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/nn8009097

Cites

49 of 49 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

Cited by

See all 253

Metadata

Authors
Lin, Y., Watson, K. A., Fallbach, M. J., Ghose, S., Smith, J. G., Delozier, D. M., Cao, W., Crooks, R. E., & Connell, J. W.
Venue
ACS Nano
Publisher
American Chemical Society (ACS)
Published
2009-03-11
Volume
3
Issue
4
Pages
871-884
ISSN
  • 1936-0851 (ISSN-L)
  • 1936-086X
DOI
10.1021/nn8009097
OpenAlex
W2001546513
Cited by
253
References
49
FWCI
11.17
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

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.