The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Tunable sieving of ions using graphene oxide membranes
Open accessAbstract
Graphene oxide membranes show exceptional molecular permeation properties, with promise for many applications. However, their use in ion sieving and desalination technologies is limited by a permeation cutoff of ∼9 Å (ref. 4), which is larger than the diameters of hydrated ions of common salts. The cutoff is determined by the interlayer spacing (d) of ∼13.5 Å, typical for graphene oxide laminates that swell in water. Achieving smaller d for the laminates immersed in water has proved to be a challenge. Here, we describe how to control d by physical confinement and achieve accurate and tunable ion sieving. Membranes with d from ∼9.8 Å to 6.4 Å are demonstrated, providing a sieve size smaller than the diameters of hydrated ions. In this regime, ion permeation is found to be thermally activated with energy barriers of ∼10-100 kJ mol-1 depending on d. Importantly, permeation rates decrease exponentially with decreasing sieve size but water transport is weakly affected (by a factor of <2). The latter is attributed to a low barrier for the entry of water molecules and large slip lengths inside graphene capillaries. Building on these findings, we demonstrate a simple scalable method to obtain graphene-based membranes with limited swelling, which exhibit 97% rejection for NaCl.
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
Computer Simulation of Liquids
Allen, M. P., & Tildesley, D. J. (2017) · doi:10.1093/oso/9780198803195.001.0001 · Cited by 20,945
The chemistry of graphene oxide
Dreyer, D. R., Park, S., Bielawski, C. W., & Ruoff, R. S. (2010) · Chem. Soc. Rev. · doi:10.1039/b917103g · Cited by 11,653
Luo, J., Cote, L. J., Tung, V. C., Tan, A. T. L., Goins, P. E., Wu, J., & Huang, J. (2010) · Journal of the American Chemical Society · doi:10.1021/ja1078943 · Cited by 389
Cited by
Smith, A. T., LaChance, A. M., Zeng, S., Liu, B., & Sun, L. (2019) · Nano Materials Science · doi:10.1016/j.nanoms.2019.02.004 · Cited by 1,643
Effective ion sieving with Ti3C2Tx MXene membranes for production of drinking water from seawater
Ding, L., Li, L., Liu, Y., Wu, Y., Lu, Z., Deng, J., Wei, Y., Caro, J., & Wang, H. (2020) · Nature Sustainability · doi:10.1038/s41893-020-0474-0 · Cited by 804
Design principles of ion selective nanostructured membranes for the extraction of lithium ions
Razmjou, A., Asadnia, M., Hosseini, E., Habibnejad Korayem, A., & Chen, V. (2019) · Nature Communications · doi:10.1038/s41467-019-13648-7 · Cited by 616
Highly stable graphene-oxide-based membranes with superior permeability
Thebo, K. H., Qian, X., Zhang, Q., Chen, L., Cheng, H.-M., & Ren, W. (2018) · Nature Communications · doi:10.1038/s41467-018-03919-0 · Cited by 580
Functional Liquid Crystals towards the Next Generation of Materials
Kato, T., Uchida, J., Ichikawa, T., & Sakamoto, T. (2018) · Angewandte Chemie International Edition · doi:10.1002/anie.201711163 · Cited by 518
Metadata
- Authors
- Abraham, J., Vasu, K. S., Williams, C. D., Gopinadhan, K., Su, Y., Cherian, C. T., Dix, J., Prestat, E., Haigh, S. J., Grigorieva, I. V., Carbone, P., Geim, A. K., & Nair, R. R.
- Venue
- Nature Nanotechnology
- Published
- 2017-04-03
- Volume
- 12
- Issue
- 6
- Pages
- 546-550
- ISSN
- 1748-3387 (ISSN-L)
- 1748-3395
- OpenAlex
- W2580411523
- Cited by
- 1,875
- References
- 3
- FWCI
- 83.46
- Type
- journal article
- Language
- en
- Open access
- green
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Tunable sieving of ions using graphene oxide membranes. https://app.cochat.ai/papers/10.1038/nnano.2017.21
- The paper
- Abraham, J., Vasu, K. S., Williams, C. D., Gopinadhan, K., Su, Y., Cherian, C. T., Dix, J., Prestat, E., Haigh, S. J., Grigorieva, I. V., Carbone, P., Geim, A. K., & Nair, R. R. (2017). Tunable sieving of ions using graphene oxide membranes. Nature Nanotechnology. https://doi.org/10.1038/nnano.2017.21
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.