The DOI matches its Crossref record; 6 of the 6 references it cites were found in a registry or an index.
Thermal conductivity of graphene with defects induced by electron beam irradiation
Open accessAbstract
We investigate the thermal conductivity of suspended graphene as a function of the density of defects, ND, introduced in a controllable way. High-quality graphene layers are synthesized using chemical vapor deposition, transferred onto a transmission electron microscopy grid, and suspended over ∼7.5 μm size square holes. Defects are induced by irradiation of graphene with the low-energy electron beam (20 keV) and quantified by the Raman D-to-G peak intensity ratio. As the defect density changes from 2.0 × 10(10) cm(-2) to 1.8 × 10(11) cm(-2) the thermal conductivity decreases from ∼(1.8 ± 0.2) × 10(3) W mK(-1) to ∼(4.0 ± 0.2) × 10(2) W mK(-1) near room temperature. At higher defect densities, the thermal conductivity reveals an intriguing saturation-type behavior at a relatively high value of ∼400 W mK(-1). The thermal conductivity dependence on the defect density is analyzed using the Boltzmann transport equation and molecular dynamics simulations. The results are important for understanding phonon - point defect scattering in two-dimensional systems and for practical applications of graphene in thermal management.
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
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
Self-citationThermal properties of graphene and nanostructured carbon materials
Balandin, A. A. (2011) · Nature Materials · doi:10.1038/nmat3064 · Cited by 6,244
Self-citationTwo-Dimensional Phonon Transport in Supported Graphene
Seol, J. H., Jo, I., Moore, A. L., Lindsay, L., Aitken, Z. H., Pettes, M. T., Li, X., Yao, Z., Huang, R., Broido, D., et al. (2010) · Science · doi:10.1126/science.1184014 · Cited by 1,926
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
Self-citationVallabhaneni, A. K., Singh, D., Bao, H., Murthy, J., & Ruan, X. (2016) · Physical Review B · doi:10.1103/physrevb.93.125432 · Cited by 134
Cited by
High thermal conductivity of high-quality monolayer boron nitride and its thermal expansion
Cai, Q., Scullion, D., Gan, W., Falin, A., Zhang, S., Watanabe, K., Taniguchi, T., Chen, Y., Santos, E. J. G., & Li, L. H. (2019) · Science Advances · doi:10.1126/sciadv.aav0129 · Cited by 607
Qiu, L., Zhu, N., Feng, Y., Michaelides, E. E., Żyła, G., Jing, D., Zhang, X., Norris, P. M., Markides, C. N., & Mahian, O. (2020) · Physics Reports · doi:10.1016/j.physrep.2019.12.001 · Cited by 523
Phonons and thermal transport in graphene and graphene-based materials
Nika, D. L., & Balandin, A. A. (2017) · Reports on Progress in Physics · doi:10.1088/1361-6633/80/3/036502 · Cited by 359
Self-citationZhang, X., Xu, Y., Wang, M., Liu, E., Zhao, N., Shi, C., Lin, D., Zhu, F., & He, C. (2020) · Nature Communications · doi:10.1038/s41467-020-16490-4 · Cited by 355
Tunable Optical Properties of 2D Materials and Their Applications
Ma, Q., Ren, G., Xu, K., & Ou, J. Z. (2021) · Advanced Optical Materials · doi:10.1002/adom.202001313 · Cited by 269
Metadata
- Authors
- Malekpour, H., Ramnani, P., Srinivasan, S., Balasubramanian, G., Nika, D. L., Mulchandani, A., Lake, R. K., & Balandin, A. A.
- Venue
- Nanoscale
- Publisher
- Royal Society of Chemistry (RSC)
- Published
- 2016
- Volume
- 8
- Issue
- 30
- Pages
- 14608-14616
- ISSN
- 2040-3364 (ISSN-L)
- 2040-3372
- OpenAlex
- W2470675431
- Cited by
- 251
- References
- 6
- FWCI
- 13.24
- Type
- journal article
- Language
- en
- Open access
- hybrid
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: Thermal conductivity of graphene with defects induced by electron beam irradiation. https://app.cochat.ai/papers/10.1039/c6nr03470e
- The paper
- Malekpour, H., Ramnani, P., Srinivasan, S., Balasubramanian, G., Nika, D. L., Mulchandani, A., Lake, R. K., & Balandin, A. A. (2016). Thermal conductivity of graphene with defects induced by electron beam irradiation. Nanoscale. https://doi.org/10.1039/c6nr03470e
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.