随机纳米碳管网络及其渗流性质

The Random Network of Carbon Nanotubes and Its Percolation Properties

数值模拟了实验上构造纳米碳管网络的溶液沉积方法。与一般的随机网络模型不同,将碳管的长度计算在内,而且考虑了不同的空间相交位形。数值模拟发现网络的度分布为高斯分布,平均集聚系数约为0.11。当网络中碳管平均面密度取值在0σ=179 200根/cm2附近时,网络系综达到渗流。在临界点附近,网络的连通概率p、两极之间电导G、最大连接数S与碳管的面密度差Δσ之间都存在幂律关系。除此之外,考虑碳管之间的Kapizza接触热阻,计算出碳管网络的热阻,发现高低温热源之间的渗流热阻与导通碳管的长度的平方和成线性关系。

In this paper,we numerically simulate a solution-deposited approach to form carbon nanotube networks in experiments.Different from generally used random network models,we have taken various lengths and intersecting configurations of carbon nanotubes into account.The degree distribution of the network is found to be Gaussion type and the average clustering coefficient of it is about 0.11 by simulation.The ensemble of networks arrives at percolation when the average density of carbon nanotubes takes the values around 179 200 pieces/cm2.Near the threshold,the global connecting probability p,the conductance G between two electric poles and the maximum connected numbers of tubes all behave power-low relations with the difference of density Δσ on the two-dimensional plane.Moreover,considering Kapizza contacting thermal resistance between carbon nanotubes,we obtain the thermal resistance of the whole network.The percolation thermal resistance between the high and low heat reservoirs behaves linearly with the summation of squares of lengths of connecting carbon nanotubes.