Thermal conductivity model for nanofiber networks
Abstract
Understanding thermal transport in nanofiber networks is essential for their applications in thermal management, which are used extensively as mechanically sturdy thermal insulation or high thermal conductivity materials. In this study, using the statistical theory and Fourier's law of heat conduction while accounting for both the inter-fiber contact thermal resistance and the intrinsic thermal resistance of nanofibers, an analytical model is developed to predict the thermal conductivity of nanofiber networks as a function of their geometric and thermal properties. A scaling relation between the thermal conductivity and the geometric properties including volume fraction and nanofiber length of the network is revealed. This model agrees well with both numerical simulations and experimental measurements found in the literature. This model may prove useful in analyzing the experimental results and designing nanofiber networks for both high and low thermal conductivity applications.
- Authors:
-
- Univ. of Colorado, Boulder, CO (United States)
- Univ. of Colorado, Boulder, CO (United States); China Univ. of Mining and Technology, Xuzhou (China)
- Univ. of Colorado, Boulder, CO (United States); National Renewable Energy Lab. (NREL), Golden, CO (United States)
- Publication Date:
- Research Org.:
- National Renewable Energy Laboratory (NREL), Golden, CO (United States)
- Sponsoring Org.:
- USDOE Advanced Research Projects Agency - Energy (ARPA-E)
- OSTI Identifier:
- 1432440
- Alternate Identifier(s):
- OSTI ID: 1422261
- Report Number(s):
- NREL/JA-5500-71269
Journal ID: ISSN 0021-8979; TRN: US1802659
- Grant/Contract Number:
- AC36-08GO28308; AR0000743
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Journal of Applied Physics
- Additional Journal Information:
- Journal Volume: 123; Journal Issue: 8; Journal ID: ISSN 0021-8979
- Publisher:
- American Institute of Physics (AIP)
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 77 NANOSCIENCE AND NANOTECHNOLOGY; thermal transport; nanofibers; thermal insulation; thermal conductivity
Citation Formats
Zhao, Xinpeng, Huang, Congliang, Liu, Qingkun, Smalyukh, Ivan I., and Yang, Ronggui. Thermal conductivity model for nanofiber networks. United States: N. p., 2018.
Web. doi:10.1063/1.5008582.
Zhao, Xinpeng, Huang, Congliang, Liu, Qingkun, Smalyukh, Ivan I., & Yang, Ronggui. Thermal conductivity model for nanofiber networks. United States. https://doi.org/10.1063/1.5008582
Zhao, Xinpeng, Huang, Congliang, Liu, Qingkun, Smalyukh, Ivan I., and Yang, Ronggui. Thu .
"Thermal conductivity model for nanofiber networks". United States. https://doi.org/10.1063/1.5008582. https://www.osti.gov/servlets/purl/1432440.
@article{osti_1432440,
title = {Thermal conductivity model for nanofiber networks},
author = {Zhao, Xinpeng and Huang, Congliang and Liu, Qingkun and Smalyukh, Ivan I. and Yang, Ronggui},
abstractNote = {Understanding thermal transport in nanofiber networks is essential for their applications in thermal management, which are used extensively as mechanically sturdy thermal insulation or high thermal conductivity materials. In this study, using the statistical theory and Fourier's law of heat conduction while accounting for both the inter-fiber contact thermal resistance and the intrinsic thermal resistance of nanofibers, an analytical model is developed to predict the thermal conductivity of nanofiber networks as a function of their geometric and thermal properties. A scaling relation between the thermal conductivity and the geometric properties including volume fraction and nanofiber length of the network is revealed. This model agrees well with both numerical simulations and experimental measurements found in the literature. This model may prove useful in analyzing the experimental results and designing nanofiber networks for both high and low thermal conductivity applications.},
doi = {10.1063/1.5008582},
journal = {Journal of Applied Physics},
number = 8,
volume = 123,
place = {United States},
year = {Thu Feb 22 00:00:00 EST 2018},
month = {Thu Feb 22 00:00:00 EST 2018}
}
Web of Science
Figures / Tables:
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