The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.
Atomistic understandings of reduced graphene oxide as an ultrathin-film nanoporous membrane for separations
Open accessAbstract
The intrinsic defects in reduced graphene oxide (rGO) formed during reduction processes can act as nanopores, making rGO a promising ultrathin-film membrane candidate for separations. To assess the potential of rGO for such applications, molecular dynamics techniques are employed to understand the defect formation in rGO and their separation performance in water desalination and natural gas purification. We establish the relationship between rGO synthesis parameters and defect sizes, resulting in a potential means to control the size of nanopores in rGO. Furthermore, our results show that rGO membranes obtained under properly chosen synthesis conditions can achieve effective separations and provide significantly higher permeate fluxes than currently available membranes.
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
Fast Parallel Algorithms for Short-Range Molecular Dynamics
Plimpton, S. (1995) · Journal of Computational Physics · doi:10.1006/jcph.1995.1039 · Cited by 44,721
The missing term in effective pair potentials
Berendsen, H. J. C., Grigera, J. R., & Straatsma, T. P. (1987) · The Journal of Physical Chemistry · doi:10.1021/j100308a038 · Cited by 13,345
Large-Area Synthesis of High-Quality and Uniform Graphene Films on Copper Foils
Li, X., Cai, W., An, J., Kim, S., Nah, J., Yang, D., Piner, R., Velamakanni, A., Jung, I., Tutuc, E., et al. (2009) · Science · doi:10.1126/science.1171245 · Cited by 11,220
Roll-to-roll production of 30-inch graphene films for transparent electrodes
Bae, S., Kim, H., Lee, Y., Xu, X., Park, J.-S., Zheng, Y., Balakrishnan, J., Lei, T., Ri Kim, H., Song, Y. I., et al. (2010) · Nature Nanotechnology · doi:10.1038/nnano.2010.132 · Cited by 8,136
DREIDING: a generic force field for molecular simulations
Mayo, S. L., Olafson, B. D., & Goddard, W. A. (1990) · The Journal of Physical Chemistry · doi:10.1021/j100389a010 · Cited by 6,585
Joung, I. S., & Cheatham, T. E. (2008) · The Journal of Physical Chemistry B · doi:10.1021/jp8001614 · Cited by 3,483
Charge equilibration for molecular dynamics simulations
Rappe, A. K., & Goddard, W. A. (1991) · The Journal of Physical Chemistry · doi:10.1021/j100161a070 · Cited by 3,465
Unimpeded Permeation of Water Through Helium-Leak–Tight Graphene-Based Membranes
Nair, R. R., Wu, H. A., Jayaram, P. N., Grigorieva, I. V., & Geim, A. K. (2012) · Science · doi:10.1126/science.1211694 · Cited by 3,073
ReaxFF Reactive Force Field for Molecular Dynamics Simulations of Hydrocarbon Oxidation
Chenoweth, K., van Duin, A. C. T., & Goddard, W. A. (2008) · The Journal of Physical Chemistry A · doi:10.1021/jp709896w · Cited by 2,697
Water Desalination across Nanoporous Graphene
Cohen-Tanugi, D., & Grossman, J. C. (2012) · Nano Letters · doi:10.1021/nl3012853 · Cited by 2,204
Self-citationVapor–liquid equilibria of mixtures containing alkanes, carbon dioxide, and nitrogen
Potoff, J. J., & Siepmann, J. I. (2001) · AIChE Journal · doi:10.1002/aic.690470719 · Cited by 2,073
Nanofiltration membranes review: Recent advances and future prospects
Mohammad, A. W., Teow, Y. H., Ang, W. L., Chung, Y. T., Oatley-Radcliffe, D. L., & Hilal, N. (2015) · Desalination · doi:10.1016/j.desal.2014.10.043 · Cited by 1,996
Structural evolution during the reduction of chemically derived graphene oxide
Bagri, A., Mattevi, C., Acik, M., Chabal, Y. J., Chhowalla, M., & Shenoy, V. B. (2010) · Nature Chemistry · doi:10.1038/nchem.686 · Cited by 1,819
Water desalination using nanoporous single-layer graphene
Surwade, S. P., Smirnov, S. N., Vlassiouk, I. V., Unocic, R. R., Veith, G. M., Dai, S., & Mahurin, S. M. (2015) · Nature Nanotechnology · doi:10.1038/nnano.2015.37 · Cited by 1,692
Power plant post-combustion carbon dioxide capture: An opportunity for membranes
Merkel, T. C., Lin, H., Wei, X., & Baker, R. (2010) · Journal of Membrane Science · doi:10.1016/j.memsci.2009.10.041 · Cited by 1,657
Bai, J., Zhong, X., Jiang, S., Huang, Y., & Duan, X. (2010) · Nature Nanotechnology · doi:10.1038/nnano.2010.8 · Cited by 1,378
Ultrathin, Molecular-Sieving Graphene Oxide Membranes for Selective Hydrogen Separation
Li, H., Song, Z., Zhang, X., Huang, Y., Li, S., Mao, Y., Ploehn, H. J., Bao, Y., & Yu, M. (2013) · Science · doi:10.1126/science.1236686 · Cited by 1,360
Selective molecular sieving through porous graphene
Koenig, S. P., Wang, L., Pellegrino, J., & Bunch, J. S. (2012) · Nature Nanotechnology · doi:10.1038/nnano.2012.162 · Cited by 1,183
Highly Permeable Zeolite Imidazolate Framework-8 Membranes for CO2/CH4 Separation
Venna, S. R., & Carreon, M. A. (2010) · Journal of the American Chemical Society · doi:10.1021/ja909263x · Cited by 956
Selective Ionic Transport through Tunable Subnanometer Pores in Single-Layer Graphene Membranes
O’Hern, S. C., Boutilier, M. S. H., Idrobo, J.-C., Song, Y., Kong, J., Laoui, T., Atieh, M., & Karnik, R. (2014) · Nano Letters · doi:10.1021/nl404118f · Cited by 820
Graphene-based materials: Synthesis and gas sorption, storage and separation
Gadipelli, S., & Guo, Z. X. (2015) · Progress in Materials Science · doi:10.1016/j.pmatsci.2014.10.004 · Cited by 734
Rufford, T. E., Smart, S., Watson, G. C. Y., Graham, B. F., Boxall, J., Diniz da Costa, J. C., & May, E. F. (2012) · Journal of Petroleum Science and Engineering · doi:10.1016/j.petrol.2012.06.016 · Cited by 676
Electron beam nanosculpting of suspended graphene sheets
Fischbein, M. D., & Drndić, M. (2008) · Applied Physics Letters · doi:10.1063/1.2980518 · Cited by 607
Understanding Water Permeation in Graphene Oxide Membranes
Wei, N., Peng, X., & Xu, Z. (2014) · ACS Applied Materials & Interfaces · doi:10.1021/am500777b · Cited by 487
Scalable enhancement of graphene oxide properties by thermally driven phase transformation
Kumar, P. V., Bardhan, N. M., Tongay, S., Wu, J., Belcher, A. M., & Grossman, J. C. (2014) · Nature Chemistry · doi:10.1038/nchem.1820 · Cited by 384
Self-citationQuantifying the potential of ultra-permeable membranes for water desalination
Cohen-Tanugi, D., McGovern, R. K., Dave, S. H., Lienhard, J. H., & Grossman, J. C. (2014) · Energy Environ. Sci. · doi:10.1039/c3ee43221a · Cited by 341
Self-citationKumar, P. V., Bernardi, M., & Grossman, J. C. (2013) · ACS Nano · doi:10.1021/nn305507p · Cited by 287
Self-citationMechanical Strength of Nanoporous Graphene as a Desalination Membrane
Cohen-Tanugi, D., & Grossman, J. C. (2014) · Nano Letters · doi:10.1021/nl502399y · Cited by 273
Self-citationOrigin of Anomalous Water Permeation through Graphene Oxide Membrane
Boukhvalov, D. W., Katsnelson, M. I., & Son, Y.-W. (2013) · Nano Letters · doi:10.1021/nl4020292 · Cited by 256
Yuan, W., Chen, J., & Shi, G. (2014) · Materials Today · doi:10.1016/j.mattod.2014.01.021 · Cited by 201
Selective Gas Diffusion in Graphene Oxides Membranes: A Molecular Dynamics Simulations Study
Jiao, S., & Xu, Z. (2015) · ACS Applied Materials & Interfaces · doi:10.1021/am509048k · Cited by 178
Surface Energy Modification by Spin-Cast, Large-Area Graphene Film for Block Copolymer Lithography
Kim, B. H., Kim, J. Y., Jeong, S., Hwang, J. O., Lee, D. H., Shin, D. O., Choi, S., & Kim, S. O. (2010) · ACS Nano · doi:10.1021/nn101491g · Cited by 140
Selectivity trend of gas separation through nanoporous graphene
Liu, H., Chen, Z., Dai, S., et al. (2014) · Journal of Solid State Chemistry · doi:10.1016/j.jssc.2014.01.030 · Cited by 106
First, E. L., Hasan, M. M. F., & Floudas, C. A. (2014) · AIChE Journal · doi:10.1002/aic.14441 · Cited by 103
The Thinnest Molecular Separation Sheet by Graphene Gates of Single-Walled Carbon Nanohorns
Ohba, T. (2014) · ACS Nano · doi:10.1021/nn504162s · Cited by 29
Cited by
Fei, H., Dong, J., Feng, Y., Allen, C. S., Wan, C., Volosskiy, B., Li, M., Zhao, Z., Wang, Y., Sun, H., et al. (2018) · Nature Catalysis · doi:10.1038/s41929-017-0008-y · Cited by 1,973
Atomic-level tuning of Co–N–C catalyst for high-performance electrochemical H2O2 production
Jung, E., Shin, H., Lee, B.-H., Efremov, V., Lee, S., Lee, H. S., Kim, J., Hooch Antink, W., Park, S., Lee, K.-S., et al. (2020) · Nature Materials · doi:10.1038/s41563-019-0571-5 · Cited by 1,247
Large-area graphene-nanomesh/carbon-nanotube hybrid membranes for ionic and molecular nanofiltration
Yang, Y., Yang, X., Liang, L., Gao, Y., Cheng, H., Li, X., Zou, M., Ma, R., Yuan, Q., & Duan, X. (2019) · Science · doi:10.1126/science.aau5321 · Cited by 648
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
Self-citationGated CO2 permeation across dynamic graphene pores
Bondaz, L., Ronghe, A., Ganapathy Ayappa, K., & Agrawal, K. V. (2025) · Nature Communications · doi:10.1038/s41467-025-61518-2 · Cited by 12
Metadata
- Authors
- Lin, L.-C., & Grossman, J. C.
- Venue
- Nature Communications
- Published
- 2015-09-23
- Volume
- 6
- Issue
- 1
- Pages
- 8335-8335
- ISSN
- 2041-1723 (ISSN-L)
- OpenAlex
- W2266028782
- Cited by
- 264
- References
- 35
- FWCI
- 10.22
- Type
- journal article
- Language
- en
- Open access
- gold
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.