The DOI matches its Crossref record; 62 of the 62 references it cites were found in a registry or an index.
Graphene-Based Membranes for Molecular Separation
Open accessAbstract
In comparison with traditional chemical separation processes, membrane separation is much simpler and more efficient. An ideal membrane for molecular separation should be as thin as possible to maximize its solvent flux, be mechanically robust to prevent it from fracture, and have well-defined pore sizes to guarantee its selectivity. Graphene is an excellent platform for developing size-selective membranes because of its atomic thickness, high mechanical strength, and chemical inertness. In this Perspective, we review the recent advancements on the fabrication of nanoporous graphene membranes and graphene oxide membranes (GOMs) for molecular separation. The methods of fabricating these membranes are summarized, and the mechanisms of molecular separation based on these two types of graphene membranes are compared. The challenges of synthesizing and transferring large-area nanoporous graphene membranes and engineering the performances of GOMs are discussed.
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Cites
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Nanocatalysts and other nanomaterials for water remediation from organic pollutants
Lu, F., & Astruc, D. (2020) · Coordination Chemistry Reviews · doi:10.1016/j.ccr.2020.213180 · Cited by 682
Highly stable graphene-oxide-based membranes with superior permeability
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Graphene membranes for water desalination
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2D materials as an emerging platform for nanopore-based power generation
Macha, M., Marion, S., Nandigana, V. V. R., & Radenovic, A. (2019) · Nature Reviews Materials · doi:10.1038/s41578-019-0126-z · Cited by 426
Multilayer Nanoporous Graphene Membranes for Water Desalination
Cohen-Tanugi, D., Lin, L.-C., & Grossman, J. C. (2016) · Nano Letters · doi:10.1021/acs.nanolett.5b04089 · Cited by 401
Metadata
- Authors
- Huang, L., Zhang, M., Li, C., & Shi, G.
- Venue
- The Journal of Physical Chemistry Letters
- Publisher
- American Chemical Society (ACS)
- Published
- 2015-07-08
- Volume
- 6
- Issue
- 14
- Pages
- 2806-2815
- ISSN
- 1948-7185 (ISSN-L)
- OpenAlex
- W2377810852
- Cited by
- 391
- References
- 62
- FWCI
- 47.08
- Type
- journal article
- Language
- en
- Open access
- hybrid
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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