The DOI matches its Crossref record.
Anomalous thermal conductivity enhancement in nanotube suspensions
Abstract
We have produced nanotube-in-oil suspensions and measured their effective thermal conductivity. The measured thermal conductivity is anomalously greater than theoretical predictions and is nonlinear with nanotube loadings. The anomalous phenomena show the fundamental limits of conventional heat conduction models for solid/liquid suspensions. We have suggested physical concepts for understanding the anomalous thermal behavior of nanotube suspensions. In comparison with other nanostructured materials dispersed in fluids, the nanotubes provide the highest thermal conductivity enhancement, opening the door to a wide range of nanotube applications.
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
Cited by
Thermal properties of graphene and nanostructured carbon materials
Balandin, A. A. (2011) · Nature Materials · doi:10.1038/nmat3064 · Cited by 6,244
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
Interfacial Heat Flow in Carbon Nanotube Suspensions
Huxtable, S. T., Cahill, D. G., Shenogin, S., Xue, L., Ozisik, R., Barone, P., Usrey, M., Strano, M. S., Siddons, G., Shim, M., et al. (2003) · Nature Materials · doi:10.1038/nmat996 · Cited by 1,023
Sharma, R. K., Ganesan, P., Tyagi, V. V., Metselaar, H. S. C., & Sandaran, S. C. (2016) · Applied Thermal Engineering · doi:10.1016/j.applthermaleng.2016.01.130 · Cited by 265
Nourani, M., Hamdami, N., Keramat, J., Moheb, A., & Shahedi, M. (2016) · Renewable Energy · doi:10.1016/j.renene.2015.11.043 · Cited by 199
Metadata
- Authors
- Choi, S. U. S., Zhang, Z. G., Yu, W., Lockwood, F. E., & Grulke, E. A.
- Venue
- Applied Physics Letters
- Publisher
- AIP Publishing
- Published
- 2001-10-01
- Volume
- 79
- Issue
- 14
- Pages
- 2252-2254
- ISSN
- 0003-6951 (ISSN-L)
- 1077-3118
- OpenAlex
- W2062409798
- Cited by
- 2,769
- References
- 0
- FWCI
- 9.86
- 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: Anomalous thermal conductivity enhancement in nanotube suspensions. https://app.cochat.ai/papers/10.1063/1.1408272
- The paper
- Choi, S. U. S., Zhang, Z. G., Yu, W., Lockwood, F. E., & Grulke, E. A. (2001). Anomalous thermal conductivity enhancement in nanotube suspensions. Applied Physics Letters. https://doi.org/10.1063/1.1408272
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.
