The DOI matches its Crossref record; 35 of the 35 references it cites were found in a registry or an index.
Wet-spinning assembly of continuous, neat and macroscopic graphene fibers
Open accessAbstract
Graphene is now the most attractive carbon-based material. Integration of 2D graphene sheets into macroscopic architectures such as fibers illuminates the direction to translate the excellent properties of individual graphene into advanced hierarchical ensembles for promising applications in new graphene-based nanodevices. However, the lack of effective, low-cost and convenient assembly strategy has blocked its further development. Herein, we demonstrate that neat and macroscopic graphene fibers with high mechanical strength and electrical conductivity can be fluidly spun from the common graphene oxide (GO) suspensions in large scale followed with chemical reduction. The curliness-fold formation mechanism of GO fiber has been proposed. This wet-spinning technique presented here facilitates the multifunctionalization of macroscopic graphene-based fibers with various organic or inorganic components by an easy-handle in situ or post-synthesis approach, which builds the solid foundation to access a new family of advanced composite materials for the next practical applications.
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Cites
Electric Field Effect in Atomically Thin Carbon Films
Novoselov, K. S., Geim, A. K., Morozov, S. V., Jiang, D., Zhang, Y., Dubonos, S. V., Grigorieva, I. V., & Firsov, A. A. (2004) · Science · doi:10.1126/science.1102896 · Cited by 66,834
Geim, A. K., & Novoselov, K. S. (2007) · Nature Materials · doi:10.1038/nmat1849 · Cited by 39,979
Graphene: Status and Prospects
Geim, A. K. (2009) · Science · doi:10.1126/science.1158877 · Cited by 13,942
Synthesis of graphene-based nanosheets via chemical reduction of exfoliated graphite oxide
Stankovich, S., Dikin, D. A., Piner, R. D., Kohlhaas, K. A., Kleinhammes, A., Jia, Y., Wu, Y., Nguyen, S. T., & Ruoff, R. S. (2007) · Carbon · doi:10.1016/j.carbon.2007.02.034 · Cited by 13,878
Graphene-Based Ultracapacitors
Stoller, M. D., Park, S., Zhu, Y., An, J., & Ruoff, R. S. (2008) · Nano Letters · doi:10.1021/nl802558y · Cited by 8,373
Poly(N-isopropylacrylamide): experiment, theory and application
Schild, H. G. (1992) · Progress in Polymer Science · doi:10.1016/0079-6700(92)90023-r · Cited by 5,147
Huang, X., Qi, X., Boey, F., & Zhang, H. (2012) · Chem. Soc. Rev. · doi:10.1039/c1cs15078b · Cited by 3,837
Self-Assembled Graphene Hydrogel via a One-Step Hydrothermal Process
Xu, Y., Sheng, K., Li, C., & Shi, G. (2010) · ACS Nano · doi:10.1021/nn101187z · Cited by 3,251
Chemical oxidation of multiwalled carbon nanotubes
Datsyuk, V., Kalyva, M., Papagelis, K., Parthenios, J., Tasis, D., Siokou, A., Kallitsis, I., & Galiotis, C. (2008) · Carbon · doi:10.1016/j.carbon.2008.02.012 · Cited by 2,747
Reduced Graphene Oxide Molecular Sensors
Robinson, J. T., Perkins, F. K., Snow, E. S., Wei, Z., & Sheehan, P. E. (2008) · Nano Letters · doi:10.1021/nl8013007 · Cited by 1,772
Cited by
Yu, D., Goh, K., Wang, H., Wei, L., Jiang, W., Zhang, Q., Dai, L., & Chen, Y. (2014) · Nature Nanotechnology · doi:10.1038/nnano.2014.93 · Cited by 1,436
Graphene for batteries, supercapacitors and beyond
El-Kady, M. F., Shao, Y., & Kaner, R. B. (2016) · Nature Reviews Materials · doi:10.1038/natrevmats.2016.33 · Cited by 1,262
Superstructured Assembly of Nanocarbons: Fullerenes, Nanotubes, and Graphene
Li, Z., Liu, Z., Sun, H., & Gao, C. (2015) · Chemical Reviews · doi:10.1021/acs.chemrev.5b00102 · Cited by 554
3D Graphene Materials: From Understanding to Design and Synthesis Control
Sun, Z., Fang, S., & Hu, Y. H. (2020) · Chemical Reviews · doi:10.1021/acs.chemrev.0c00083 · Cited by 543
Cheng, C., Li, S., Thomas, A., Kotov, N. A., & Haag, R. (2017) · Chemical Reviews · doi:10.1021/acs.chemrev.6b00520 · Cited by 527
Metadata
- Authors
- Cong, H.-P., Ren, X.-C., Wang, P., & Yu, S.-H.
- Venue
- Scientific Reports
- Published
- 2012-08-30
- Volume
- 2
- Issue
- 1
- Pages
- 613-613
- ISSN
- 2045-2322 (ISSN-L)
- OpenAlex
- W2055890241
- Cited by
- 296
- References
- 35
- FWCI
- 13.90
- Type
- journal article
- Language
- en
- Open access
- gold
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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).
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