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Title: Novel three-dimensional carbon nanotube networks as high performance thermal interface materials
Authors: Kong, Qinyu
Bodelot, Laurence
Lebental, Bérengère
Lim, Yu Dian
Shiau, Li Lynn
Gusarov, Boris
Tan, Chong Wei
Liang, Kun
Lu, Congxiang
Tan, Chuan Seng
Tay, Beng Kang
Coquet, Philippe
Keywords: DRNTU::Engineering::Electrical and electronic engineering
3D CNT Network
In-plane Thermal Conductivity
Issue Date: 2018
Source: Kong, Q., Bodelot, L., Lebental, B., Lim, Y. D., Shiau, L. L., Gusarov, B., ... Tay, B. K. (2018). Novel three-dimensional carbon nanotube networks as high performance thermal interface materials. Carbon, 132359-369. doi:10.1016/j.carbon.2018.02.052
Series/Report no.: Carbon
Abstract: Vertically aligned carbon nanotube (VACNT) arrays are considered as promising thermal interface materials (TIMs) due to their superior out-of-plane thermal conductivities. However the air gaps between adjacent CNTs within the CNT array hinder the in-plane heat transfer, thus significantly degrading the thermal performance of VACNT-based TIMs. To improve the in-plane thermal conduction of VACNT arrays, we propose a novel three dimensional CNT (3D CNT) network structure, where VACNTs are cross-linked by randomly-oriented secondary CNTs. Three different catalyst preparation methods for the secondary CNT growth are compared in terms of their ability to produce a dense network of secondary CNTs. The 3D CNT network grown using the chemical impregnation method shows a denser network structure, and thus is chosen for further thermal characterization. The temperature fields of the corresponding 3D CNT network under different heating powers are recorded using a 15 μm-resolution infrared thermal imaging system. The in-plane thermal conductivity is then derived from these fields using numerical fitting with a 3D heat diffusion model. We find that the in-plane thermal conductivity of the 3D CNT network is 5.40 ± 0.92 W/mK, at least 30 times higher than the thermal conductivity of the primary VACNT array used to grow the 3D CNT network.
ISSN: 0008-6223
DOI: 10.1016/j.carbon.2018.02.052
Rights: © 2018 Elsevier. This is the author created version of a work that has been peer reviewed and accepted for publication by Carbon, Elsevier. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: [].
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:EEE Journal Articles

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