The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Thermally Conductive Graphene-Polymer Composites: Size, Percolation, and Synergy Effects
Abstract
The rapidly increasing device densities in electronics dictate the need for efficient thermal management. If successfully exploited, graphene, which possesses extraordinary thermal properties, can be commercially utilized in polymer composites with ultrahigh thermal conductivity (TC). The total potential of graphene to enhance TC, however, is restricted by the large interfacial thermal resistance between the polymer mediated graphene boundaries. We report a facile and scalable dispersion of commercially available graphene nanoplatelets (GnPs) in a polymer matrix, which formed composite with an ultrahigh TC of 12.4 W/m K (vs 0.2 W/m K for neat polymer). This ultrahigh TC was achieved by applying high compression forces during the dispersion that resulted in the closure of gaps between adjacent GnPs with large lateral dimensions and low defect densities. We also found strong evidence for the existence of a thermal percolation threshold. Finally, the addition of electrically insulating boron-nitride nanoparticles to the thermally conductive GnP-polymer composite significantly reduces its electrical conductivity (to avoid short circuit) and synergistically increases the TC. The efficient dispersion of commercially available GnPs in polymer matrix provides the ideal framework for substantial progress toward the large-scale production and commercialization of GnP-based thermally conductive composites.
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
Superior Thermal Conductivity of Single-Layer Graphene
Balandin, A. A., Ghosh, S., Bao, W., Calizo, I., Teweldebrhan, D., Miao, F., & Lau, C. N. (2008) · Nano Letters · doi:10.1021/nl0731872 · Cited by 13,823
Graphene–Multilayer Graphene Nanocomposites as Highly Efficient Thermal Interface Materials
Shahil, K. M. F., & Balandin, A. A. (2012) · Nano Letters · doi:10.1021/nl203906r · Cited by 1,467
Thermal Conductivity and Phonon Transport in Suspended Few-Layer Hexagonal Boron Nitride
Jo, I., Pettes, M. T., Kim, J., Watanabe, K., Taniguchi, T., Yao, Z., & Shi, L. (2013) · Nano Letters · doi:10.1021/nl304060g · Cited by 770
Cited by
Shen, X., Wang, Z., Wu, Y., Liu, X., He, Y.-B., & Kim, J.-K. (2016) · Nano Letters · doi:10.1021/acs.nanolett.6b00722 · Cited by 382
Lian, G., Tuan, C.-C., Li, L., Jiao, S., Wang, Q., Moon, K.-S., Cui, D., & Wong, C.-P. (2016) · Chemistry of Materials · doi:10.1021/acs.chemmater.6b01595 · Cited by 382
Liu, J., Xu, Z., Cheng, Z., Xu, S., & Wang, X. (2015) · ACS Applied Materials & Interfaces · doi:10.1021/acsami.5b08578 · Cited by 57
Metadata
- Authors
- Shtein, M., Nadiv, R., Buzaglo, M., Kahil, K., & Regev, O.
- Venue
- Chemistry of Materials
- Publisher
- American Chemical Society (ACS)
- Published
- 2015-03-10
- Volume
- 27
- Issue
- 6
- Pages
- 2100-2106
- ISSN
- 0897-4756 (ISSN-L)
- 1520-5002
- OpenAlex
- W2322572553
- Cited by
- 606
- References
- 3
- FWCI
- 21.32
- 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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: Thermally Conductive Graphene-Polymer Composites: Size, Percolation, and Synergy Effects. https://app.cochat.ai/papers/10.1021/cm504550e
- The paper
- Shtein, M., Nadiv, R., Buzaglo, M., Kahil, K., & Regev, O. (2015). Thermally Conductive Graphene-Polymer Composites: Size, Percolation, and Synergy Effects. Chemistry of Materials. https://doi.org/10.1021/cm504550e
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.