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Title: Thermal conductivity characterization of three dimensional carbon nanotube network using freestanding sensor-based 3ω technique
Authors: Kong, Qinyu
Qiu, Lin
Lim, Yu Dian
Tan, Chong Wei
Liang, Kun
Lu, Congxiang
Tay, Beng Kang
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2018
Source: Kong, Q., Qiu, L., Lim, Y. D., Tan, C. W., Liang, K., Lu, C., & Tay, B. K. (2018). Thermal conductivity characterization of three dimensional carbon nanotube network using freestanding sensor-based 3ω technique. Surface and Coatings Technology, 345, 105-112. doi:10.1016/j.surfcoat.2018.03.090
Journal: Surface and Coatings Technology
Abstract: A novel three-dimensional (3D) carbon nanotube (CNT) network, composed of vertically aligned CNT array (primary CNT) bridged with randomly oriented secondary CNT, is synthesized in this work. We report the first data for the thermal properties of this new structure using freestanding sensor-based 3ω technique. Introducing freestanding sensor to conventional 3ω system enables the nondestructive characterization for samples with rough surfaces. The thermal conductivities of CNT films, as well as the contact resistance between the sensor and sample surfaces, are extracted numerically by a finite-element thermal model. The thermal conductivities of 3D CNT network under different array densities range from 9.3 to 19.8 W/mK. It is found that at lower CNT array density of 5.6 × 108/cm2, the growth of secondary CNT enhances the thermal conductivity of primary CNT array by 55.9%. This significant improvement in thermal conductivity can be attributed to the additional thermal pathway provided by the secondary CNTs in the primary CNT forest. However as the density of primary CNT array increases beyond 7.2 × 108/cm2, the growth of secondary CNTs on primary CNT forest reduces its thermal conductivity. This reduction in thermal conductivity can possibly be caused by the excessive thermal resistance from the CNT-CNT connection points within 3D CNT network.
ISSN: 0257-8972
DOI: 10.1016/j.surfcoat.2018.03.090
Rights: © 2018 Elsevier B.V. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
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