The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Optimizing the Reinforcement of Polymer-Based Nanocomposites by Graphene
Abstract
The stress transfer between the internal layers of multilayer graphene within polymer-based nanocomposites has been investigated from the stress-induced shifts of the 2D Raman band. This has been undertaken through the study of the deformation of an ideal composite system where the graphene flakes were placed upon the surface of a polymer beam and then coated with an epoxy polymer. It is found that the rate of band shift per unit strain for a monolayer graphene flake is virtually independent of whether it has one or two polymer interfaces (i.e., with or without an epoxy top coating). In contrast, the rate of band shift is lower for an uncoated bilayer specimen than a coated one, indicating relatively poor stress transfer between the graphene layers. Mapping of the strain in the coated bilayer regions has shown that there is strain continuity between adjacent monolayer and bilayer regions, indicating that they give rise to similar levels of reinforcement. Strain-induced Raman band shifts have also been evaluated for separate flakes of graphene with different numbers of layers, and it is found that the band shift rate tends to decrease with an increase in the number of layers, indicating poor stress transfer between the inner graphene layers. This behavior has been modeled in terms of the efficiency of stress transfer between the inner graphene layers. Taking into account the packing geometry of polymer-based graphene nanocomposites and the need to accommodate the polymer coils, these findings enable the optimum number of graphene layers for the best reinforcement to be determined. It is demonstrated that, in general, multilayer graphene will give rise to higher levels of reinforcement than monolayer material, with the optimum number of layers depending upon the separation of the graphene flakes in the nanocomposite.
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
Two-dimensional gas of massless Dirac fermions in graphene
Novoselov, K. S., Geim, A. K., Morozov, S. V., Jiang, D., Katsnelson, M. I., Grigorieva, I. V., Dubonos, S. V., & Firsov, A. A. (2005) · Nature · doi:10.1038/nature04233 · Cited by 21,611
Self-citationExperimental observation of the quantum Hall effect and Berry's phase in graphene
Zhang, Y., Tan, Y.-W., Stormer, H. L., & Kim, P. (2005) · Nature · doi:10.1038/nature04235 · Cited by 13,435
Fine Structure Constant Defines Visual Transparency of Graphene
Nair, R. R., Blake, P., Grigorenko, A. N., Novoselov, K. S., Booth, T. J., Stauber, T., Peres, N. M. R., & Geim, A. K. (2008) · Science · doi:10.1126/science.1156965 · Cited by 9,084
Self-citation
Cited by
Mechanical properties of graphene and graphene-based nanocomposites
Papageorgiou, D. G., Kinloch, I. A., & Young, R. J. (2017) · Progress in Materials Science · doi:10.1016/j.pmatsci.2017.07.004 · Cited by 2,579
Self-citationThe mechanics of graphene nanocomposites: A review
Young, R. J., Kinloch, I. A., Gong, L., & Novoselov, K. S. (2012) · Composites Science and Technology · doi:10.1016/j.compscitech.2012.05.005 · Cited by 1,294
Self-citationRaman spectroscopy of carbon materials and their composites: Graphene, nanotubes and fibres
Li, Z., Deng, L., Kinloch, I. A., & Young, R. J. (2023) · Progress in Materials Science · doi:10.1016/j.pmatsci.2023.101089 · Cited by 1,117
Self-citationRecent Progress in Graphene/Polymer Nanocomposites
Sun, X., Huang, C., Wang, L., Liang, L., Cheng, Y., Fei, W., & Li, Y. (2021) · Advanced Materials · doi:10.1002/adma.202001105 · Cited by 490
Mechanisms of mechanical reinforcement by graphene and carbon nanotubes in polymer nanocomposites
Papageorgiou, D. G., Li, Z., Liu, M., Kinloch, I. A., & Young, R. J. (2020) · Nanoscale · doi:10.1039/c9nr06952f · Cited by 423
Self-citationChen, D., Yang, J., & Kitipornchai, S. (2017) · Composites Science and Technology · doi:10.1016/j.compscitech.2017.02.008 · Cited by 388
The Worldwide Graphene Flake Production
Kauling, A. P., Seefeldt, A. T., Pisoni, D. P., Pradeep, R. C., Bentini, R., Oliveira, R. V. B., Novoselov, K. S., & Castro Neto, A. H. (2018) · Advanced Materials · doi:10.1002/adma.201803784 · Cited by 367
Self-citationReview of functionalization, structure and properties of graphene/polymer composite fibers
Ji, X., Xu, Y., Zhang, W., Cui, L., & Liu, J. (2016) · Composites Part A: Applied Science and Manufacturing · doi:10.1016/j.compositesa.2016.04.011 · Cited by 351
Graphene Reinforced Metal Matrix Composite (GRMMC): A Review
Kumar, H. G. P., & Xavior, M. A. (2014) · Procedia Engineering · doi:10.1016/j.proeng.2014.12.381 · Cited by 272
Holistic utilization of waste plastics through a tandem process
Dai, L., Karakas, O., Lata, S., Cobb, K., Lei, H., He, C., Cheng, Y., Chen, P., & Ruan, R. (2023) · Journal of Environmental Chemical Engineering · doi:10.1016/j.jece.2023.110547 · Cited by 12
Metadata
- Authors
- Gong, L., Young, R. J., Kinloch, I. A., Riaz, I., Jalil, R., & Novoselov, K. S.
- Venue
- ACS Nano
- Publisher
- American Chemical Society (ACS)
- Published
- 2012-03-02
- Volume
- 6
- Issue
- 3
- Pages
- 2086-2095
- ISSN
- 1936-0851 (ISSN-L)
- 1936-086X
- OpenAlex
- W2152094983
- Cited by
- 297
- References
- 3
- FWCI
- 10.28
- Type
- journal article
- Language
- en
- Open access
- closed
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.