The DOI matches its Crossref record; 40 of the 40 references it cites were found in a registry or an index.
Polymer Composite with Improved Thermal Conductivity by Constructing a Hierarchically Ordered Three-Dimensional Interconnected Network of BN
Abstract
In this work, we report a fabrication of epoxy resin/ordered three-dimensional boron nitride (3D-BN) network composites through combination of ice-templating self-assembly and infiltration methods. The polymer composites possess much higher thermal conductivity up to 4.42 W m –1 K –1 at relatively low loading 34 vol % than that of random distribution composites (1.81 W m –1 K –1 for epoxy/random 3D-BN composites, 1.16 W m –1 K –1 for epoxy/random BN composites) and exhibit a high glass transition temperature (178.9–229.2 °C) and dimensional stability (22.7 ppm/K). We attribute the increased thermal conductivity to the unique oriented 3D-BN thermally conducive network, in which the much higher thermal conductivity along the in-plane direction of BN microplatelets is most useful. This study paves the way for thermally conductive polymer composites used as thermal interface materials for next-generation electronic packaging and 3D integration circuits.
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
Thermal properties of graphene and nanostructured carbon materials
Balandin, A. A. (2011) · Nature Materials · doi:10.1038/nmat3064 · Cited by 6,244
Thermal conductivity of carbon nanotubes and their polymer nanocomposites: A review
Han, Z., & Fina, A. (2011) · Progress in Polymer Science · doi:10.1016/j.progpolymsci.2010.11.004 · Cited by 2,603
Emerging challenges and materials for thermal management of electronics
Moore, A. L., & Shi, L. (2014) · Materials Today · doi:10.1016/j.mattod.2014.04.003 · Cited by 2,106
Thermal conductivity of polymer-based composites: Fundamentals and applications
Chen, H., Ginzburg, V. V., Yang, J., Yang, Y., Liu, W., Huang, Y., Du, L., & Chen, B. (2016) · Progress in Polymer Science · doi:10.1016/j.progpolymsci.2016.03.001 · Cited by 2,049
Self-citationEffective thermal conductivity of particulate composites with interfacial thermal resistance
Nan, C.-W., Birringer, R., Clarke, D. R., & Gleiter, H. (1997) · Journal of Applied Physics · doi:10.1063/1.365209 · Cited by 2,009
Freezing as a Path to Build Complex Composites
Deville, S., Saiz, E., Nalla, R. K., & Tomsia, A. P. (2006) · Science · doi:10.1126/science.1120937 · Cited by 1,900
Zhi, C., Bando, Y., Tang, C., Kuwahara, H., & Golberg, D. (2009) · Advanced Materials · doi:10.1002/adma.200900323 · Cited by 1,756
Review of thermal conductivity in composites: Mechanisms, parameters and theory
Burger, N., Laachachi, A., Ferriol, M., Lutz, M., Toniazzo, V., & Ruch, D. (2016) · Progress in Polymer Science · doi:10.1016/j.progpolymsci.2016.05.001 · Cited by 1,357
Strong, tough and stiff bioinspired ceramics from brittle constituents
Bouville, F., Maire, E., Meille, S., Van de Moortèle, B., Stevenson, A. J., & Deville, S. (2014) · Nature Materials · doi:10.1038/nmat3915 · Cited by 959
Chen, J., Huang, X., Zhu, Y., & Jiang, P. (2017) · Advanced Functional Materials · doi:10.1002/adfm.201604754 · Cited by 756
Cited by
Shao, G., Hanaor, D. A. H., Shen, X., & Gurlo, A. (2020) · Advanced Materials · doi:10.1002/adma.201907176 · Cited by 871
Cheng, P., Chen, X., Gao, H., Zhang, X., Tang, Z., Li, A., & Wang, G. (2021) · Nano Energy · doi:10.1016/j.nanoen.2021.105948 · Cited by 348
Yang, J., Tang, L.-S., Bai, L., Bao, R.-Y., Liu, Z.-Y., Xie, B.-H., Yang, M.-B., & Yang, W. (2019) · Materials Horizons · doi:10.1039/c8mh01219a · Cited by 269
Yang, J., Tang, L.-S., Bai, L., Bao, R.-Y., Liu, Z., Xie, B.-H., Yang, M.-B., & Yang, W. (2018) · ACS Sustainable Chemistry & Engineering · doi:10.1021/acssuschemeng.8b00565 · Cited by 105
Metadata
- Authors
- Hu, J., Huang, Y., Yao, Y., Pan, G., Sun, J., Zeng, X., Sun, R., Xu, J.-B., Song, B., & Wong, C.-P.
- Venue
- ACS Applied Materials & Interfaces
- Publisher
- American Chemical Society (ACS)
- Published
- 2017-04-05
- Volume
- 9
- Issue
- 15
- Pages
- 13544-13553
- ISSN
- 1944-8244 (ISSN-L)
- 1944-8252
- OpenAlex
- W2601470361
- Cited by
- 499
- References
- 40
- FWCI
- 20.89
- 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.
