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Cited by 1,481

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Selective Gas Transport Through Few-Layered Graphene and Graphene Oxide Membranes

Kim, Hyo Won, Yoon, Hee Wook, Yoon, Seon-Mi, Yoo, Byung Min, Ahn, Byung Kook, Cho, Young Hoon, Shin, Hye Jin, Yang, Hoichang, Paik, Ungyu, Kwon, Soongeun, Choi, Jae-Young, Park, Ho Bum·2013·Science

Abstract

Gas Separations: When gas separation membranes are made thinner, they usually allow permeating gases to pass through faster. However, a thinner membrane may be poorer at separating between gas species. Kim et al. (p. 91 ) examined the permeability and selectivity of layered graphene and graphene oxide membranes. Gas molecules diffuse through defective pores and channels that form between the layers. Controlling these structures tuned the properties of the membranes to allow the extraction of carbon dioxide from other gases. Li et al. (p. 95 ) describe membranes as thin as 1.8 nanometers made from only two to three layers of graphene oxide. Small defects within the layers allowed hydrogen to pass through, separating it from carbon dioxide and nitrogen.

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Metadata

Authors
Kim, H. W., Yoon, H. W., Yoon, S.-M., Yoo, B. M., Ahn, B. K., Cho, Y. H., Shin, H. J., Yang, H., Paik, U., Kwon, S., Choi, J.-Y., & Park, H. B.
Venue
Science
Published
2013-10-04
Volume
342
Issue
6154
Pages
91-95
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
OpenAlex
W1991619674
Cited by
1,481
References
0
FWCI
132.85
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: Selective Gas Transport Through Few-Layered Graphene and Graphene Oxide Membranes. https://app.cochat.ai/papers/10.1126/science.1236098
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Kim, H. W., Yoon, H. W., Yoon, S.-M., Yoo, B. M., Ahn, B. K., Cho, Y. H., Shin, H. J., Yang, H., Paik, U., Kwon, S., Choi, J.-Y., & Park, H. B. (2013). Selective Gas Transport Through Few-Layered Graphene and Graphene Oxide Membranes. Science. https://doi.org/10.1126/science.1236098

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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.