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

The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index.

Temperature-Programmed Precise Control over the Sizes of Carbon Nanospheres Based on Benzoxazine Chemistry

Wang, Shuai, Li, Wen-Cui, Hao, Guang-Ping, Hao, Yan, Sun, Qiang, Zhang, Xiang-Qian, Lu, An-Hui·2011·Journal of the American Chemical Society

Abstract

On the basis of benzoxazine chemistry, we have established a new way to synthesize highly uniform carbon nanospheres with precisely tailored sizes and high monodispersity. Using monomers including resorcinol, formaldehyde, and 1,6-diaminohexane, and in the presence of Pluronic F127 surfactant, polymer nanospheres are first synthesized under precisely programmed reaction temperatures. Subsequently, they are pseudomorphically and uniformly converted to carbon nanospheres in high yield, due to the excellent thermal stability of such polybenzoxazine-based polymers. The correlation between the initial reaction temperature (IRT) and the nanosphere size fits well with the quadratic function model, which can in turn predict the nanosphere size at a set IRT. The nanosphere sizes can easily go down to 200 nm while retaining excellent monodispersity, i.e., polydispersity <5%. The particle size uniformity is evidenced by the formation of large areas of periodic assembly structure. NMR, FT-IR, and elemental analyses prove the formation of a polybenzoxazine framework. As a demonstration of their versatility, nanocatalysts composed of highly dispersed Pd nanoparticles in the carbon nanospheres are fabricated, which show high conversion and selectivity, great reusability, and regeneration ability, as evidenced in a selective oxidation of benzyl alcohol to benzaldehyde under moderate conditions.

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/ja206333w

Cites

40 of 40 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
Wang, S., Li, W.-C., Hao, G.-P., Hao, Y., Sun, Q., Zhang, X.-Q., & Lu, A.-H.
Venue
Journal of the American Chemical Society
Published
2011-09-12
Volume
133
Issue
39
Pages
15304-15307
ISSN
  • 0002-7863 (ISSN-L)
  • 1520-5126
OpenAlex
W1966012964
Cited by
253
References
40
FWCI
6.82
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.