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Cited by 285

The DOI matches its Crossref record; 2 of the 2 references it cites were found in a registry or an index.

Theoretical evaluation of hydrogen storage capacity in pure carbon nanostructures

Li, Ju, Furuta, Terumi, Goto, Hajime, Ohashi, Toshiyuki, Fujiwara, Yoshiya, Yip, Sidney·2003·The Journal of Chemical Physics

Abstract

Carbon nanotubes have been proposed as promising hydrogen storage materials for the automotive industry. By theoretical analyses and total-energy density functional theory calculations, we show that contribution from physisorption in nanotubes, though significant at liquid nitrogen temperature, should be negligible at room temperature; contribution from chemisorption has a theoretical upper limit of 7.7 wt %, but could be difficult to utilize in practice due to slow kinetics. The metallicity of carbon nanotube is lost at full hydrogen coverage, and we find strong covalent C–H bonding that would slow down the H2 recombination kinetics during desorption. When compared to other pure carbon nanostructures, we find no rational reason yet why carbon nanotubes should be superior in either binding energies or adsorption/desorption kinetics.

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Crossref · 10.1063/1.1582831

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Metadata

Authors
Li, J., Furuta, T., Goto, H., Ohashi, T., Fujiwara, Y., & Yip, S.
Venue
The Journal of Chemical Physics
Published
2003-07-22
Volume
119
Issue
4
Pages
2376-2385
ISSN
  • 0021-9606 (ISSN-L)
  • 1089-7690
OpenAlex
W1964014097
Cited by
285
References
2
FWCI
9.54
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Theoretical evaluation of hydrogen storage capacity in pure carbon nanostructures. https://app.cochat.ai/papers/10.1063/1.1582831
The paper
Li, J., Furuta, T., Goto, H., Ohashi, T., Fujiwara, Y., & Yip, S. (2003). Theoretical evaluation of hydrogen storage capacity in pure carbon nanostructures. The Journal of Chemical Physics. https://doi.org/10.1063/1.1582831

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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.