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预测基于碳纳米管的纳米流体的有效热导率。

Predicting the effective thermal conductivity of carbon nanotube based nanofluids.

作者信息

Venkata Sastry N N, Bhunia Avijit, Sundararajan T, Das Sarit K

机构信息

Department of Mechanical Engineering, Indian Institute of Technology, Madras, Chennai 600 036, India.

出版信息

Nanotechnology. 2008 Feb 6;19(5):055704. doi: 10.1088/0957-4484/19/05/055704. Epub 2008 Jan 14.

Abstract

Adding a small volume fraction of carbon nanotubes (CNTs) to a liquid enhances the thermal conductivity significantly. Recent experimental findings report an anomalously wide range of enhancement values that continue to perplex the research community and remain unexplained. In this paper we present a theoretical model based on three-dimensional CNT chain formation (percolation) in the base liquid and the corresponding thermal resistance network. The model considers random CNT orientation and CNT-CNT interaction forming the percolating chain. Predictions are in good agreement with almost all available experimental data. Results show that the enhancement critically depends on the CNT geometry (length), volume fraction, thermal conductivity of the base liquid and the nanofluid (CNT-liquid suspension) preparation technique. Based on the physical mechanism of heat conduction in the nanofluid, we introduce a new dimensionless parameter that alone characterizes the nanofluid thermal conductivity with reasonable accuracy (∼ ± 5%).

摘要

向液体中添加少量体积分数的碳纳米管(CNT)可显著提高其热导率。最近的实验结果报告了异常广泛的增强值范围,这继续困扰着研究界且仍未得到解释。在本文中,我们提出了一个基于基础液体中三维碳纳米管链形成(渗流)及相应热阻网络的理论模型。该模型考虑了形成渗流链的随机碳纳米管取向和碳纳米管 - 碳纳米管相互作用。预测结果与几乎所有现有实验数据都吻合良好。结果表明,增强效果关键取决于碳纳米管的几何形状(长度)、体积分数、基础液体的热导率以及纳米流体(碳纳米管 - 液体悬浮液)的制备技术。基于纳米流体中热传导的物理机制,我们引入了一个新的无量纲参数,该参数能以合理的精度(约±5%)单独表征纳米流体的热导率。

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