The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
Effect of Nanoscale Curvature of Single-Walled Carbon Nanotubes on Adsorption of Polycyclic Aromatic Hydrocarbons
Abstract
Liquid-phase adsorption of tetracene and phenanthrene on a single-walled carbon nanotube (SWCNT) was examined. Tetracene adsorption was more than six times greater than that of phenanthrene. X-ray photoelectron spectroscopic examination clearly showed that tetracene and phenanthrene molecules efficiently coated the SWCNT external surfaces. The remarkable difference between the adsorption amounts of tetracene and phenanthrene was caused by the nanoscale curvature effect of the tube surface, resulting in a difference in the amount of contact between the molecule and the tube surface. The adsorption of tetracene and phenanthrene caused a significant higher frequency shift in the radial breathing mode (RBM) of the Raman band of the SWCNT, indicating an intensive pi-pi interaction between these polycyclic aromatic hydrocarbons and the external SWCNT surface.
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.
Integrity signals
Registry
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.
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
Zhu, D., & Pignatello, J. J. (2005) · Environmental Science & Technology · doi:10.1021/es0491376 · Cited by 425
Cited by
Environmental behavior and ecotoxicity of engineered nanoparticles to algae, plants, and fungi
Navarro, E., Baun, A., Behra, R., Hartmann, N. B., Filser, J., Miao, A.-J., Quigg, A., Santschi, P. H., & Sigg, L. (2008) · Ecotoxicology · doi:10.1007/s10646-008-0214-0 · Cited by 1,772
Carbon nanotubes as adsorbents in environmental pollution management: A review
Ren, X., Chen, C., Nagatsu, M., & Wang, X. (2011) · Chemical Engineering Journal · doi:10.1016/j.cej.2010.08.045 · Cited by 1,078
Ji, L., Chen, W., Duan, L., & Zhu, D. (2009) · Environmental Science & Technology · doi:10.1021/es803268b · Cited by 801
Lin, D., & Xing, B. (2008) · Environmental Science & Technology · doi:10.1021/es801297u · Cited by 593
Hyung, H., & Kim, J.-H. (2008) · Environmental Science & Technology · doi:10.1021/es702916h · Cited by 477
Metadata
- Authors
- Gotovac, S., Honda, H., Hattori, Y., Takahashi, K., Kanoh, H., & Kaneko, K.
- Venue
- Nano Letters
- Publisher
- American Chemical Society (ACS)
- Published
- 2007-02-23
- Volume
- 7
- Issue
- 3
- Pages
- 583-587
- ISSN
- 1530-6984 (ISSN-L)
- 1530-6992
- OpenAlex
- W2067377831
- Cited by
- 283
- References
- 1
- FWCI
- 13.89
- 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.
