The DOI matches its Crossref record; 46 of the 46 references it cites were found in a registry or an index.
Thermal transport across Twin Grain Boundaries in Polycrystalline Graphene from Nonequilibrium Molecular Dynamics Simulations
Abstract
We have studied the thermal conductance of tilt grain boundaries in graphene using nonequilibrium molecular dynamics simulations. When a constant heat flux is allowed to flow, we observe sharp jumps in temperature at the boundaries, characteristic of interfaces between materials of differing thermal properties. On the basis of the magnitude of these jumps, we have computed the boundary conductance of twin grain boundaries as a function of their misorientation angles. We find the boundary conductance to be in the range 1.5 × 10(10) to 4.5 × 10(10) W/(m(2) K), which is significantly higher than that of any other thermoelectric interfaces reported in the literature. Using the computed values of boundary conductances, we have identified a critical grain size of 0.1 μm below which the contribution of the tilt boundaries to the conductivity becomes comparable to that of the contribution from the grains themselves. Experiments to test the predictions of our simulations are proposed.
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
Geim, A. K., & Novoselov, K. S. (2007) · Nature Materials · doi:10.1038/nmat1849 · Cited by 39,979
The electronic properties of graphene
Castro Neto, A. H., Guinea, F., Peres, N. M. R., Novoselov, K. S., & Geim, A. K. (2009) · Reviews of Modern Physics · doi:10.1103/revmodphys.81.109 · Cited by 24,803
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
Graphene: Status and Prospects
Geim, A. K. (2009) · Science · doi:10.1126/science.1158877 · Cited by 13,942
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
Experimental 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
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
Self-citationLarge-scale pattern growth of graphene films for stretchable transparent electrodes
Kim, K. S., Zhao, Y., Jang, H., Lee, S. Y., Kim, J. M., Kim, K. S., Ahn, J.-H., Kim, P., Choi, J.-Y., & Hong, B. H. (2009) · Nature · doi:10.1038/nature07719 · Cited by 10,452
Holman, J. P. (1976) · Cited by 9,157
Cited by
Structure of graphene and its disorders: a review
Yang, G., Li, L., Lee, W. B., & Ng, M. C. (2018) · Science and Technology of Advanced Materials · doi:10.1080/14686996.2018.1494493 · Cited by 759
Mao, J., Liu, Z., Zhou, J., Zhu, H., Zhang, Q., Chen, G., & Ren, Z. (2018) · Advances in Physics · doi:10.1080/00018732.2018.1551715 · Cited by 592
Polycrystalline graphene and other two-dimensional materials
Yazyev, O. V., & Chen, Y. P. (2014) · Nature Nanotechnology · doi:10.1038/nnano.2014.166 · Cited by 502
Various defects in graphene: a review
Bhatt, M. D., Kim, H., & Kim, G. (2022) · RSC Advances · doi:10.1039/d2ra01436j · Cited by 386
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
Thermal and Thermoelectric Properties of Graphene
Xu, Y., Li, Z., & Duan, W. (2014) · Small · doi:10.1002/smll.201303701 · Cited by 300
Measurement of the intrinsic strength of crystalline and polycrystalline graphene
Rasool, H. I., Ophus, C., Klug, W. S., Zettl, A., & Gimzewski, J. K. (2013) · Nature Communications · doi:10.1038/ncomms3811 · Cited by 296
Dong, H., Wen, B., & Melnik, R. (2014) · Scientific Reports · doi:10.1038/srep07037 · Cited by 228
Metadata
- Authors
- Bagri, A., Kim, S.-P., Ruoff, R. S., & Shenoy, V. B.
- Venue
- Nano Letters
- Publisher
- American Chemical Society (ACS)
- Published
- 2011-08-25
- Volume
- 11
- Issue
- 9
- Pages
- 3917-3921
- ISSN
- 1530-6984 (ISSN-L)
- 1530-6992
- OpenAlex
- W2040162537
- Cited by
- 349
- References
- 46
- FWCI
- 11.77
- 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.