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Computational Investigation of the Morphology Efficiency and Properties of Silver Nano Wires Networks in Transparent Conductive Film

机译:透明导电膜中银纳米线网络的形态效率和性能的计算研究

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摘要

Random networks of silver nano wires have been considered for use in transparent conductive films as an alternative to Indium Tin Oxide (ITO), which is unsuitable for flexible devices. However, the random distribution of nano wires makes such conductive films non-uniform. As electrical conductivity is achieved through a percolation process, understanding the scale-dependency of the macroscopic properties (like electrical conductivity) and the exact efficiency of the network (the proportion of nano wires that participate in electrical conduction) is essential for optimizing the design. In this paper, we propose a computational method for identifying the representative volume element (RVE) of nano wire networks. This defines the minimum pixel size in devices using such transparent electrodes. The RVE is used to compute the macroscopic properties of films and to quantify the electrically conducting efficiency of networks. Then, the sheet resistance and transparency of networks are calculated based on the predicted RVEs, in order to analyze the effects of nano wire networks on the electrical and optical properties of conductive films. The results presented in this paper provide insights that help optimizing random nano wire networks in transparent conductive films for achieving better efficiencies.
机译:已经考虑将银纳米线的随机网络用于透明导电膜中,以替代氧化铟锡(ITO),后者不适用于柔性器件。然而,纳米线的无规分布使得这种导电膜不均匀。由于通过渗透过程实现了电导率,因此了解宏观性能(如电导率)的尺度依赖性和网络的确切效率(参与导电的纳米线比例)对于优化设计至关重要。在本文中,我们提出了一种用于识别纳米线网络的代表性体积元素(RVE)的计算方法。这定义了使用这种透明电极的设备中的最小像素大小。 RVE用于计算薄膜的宏观特性并量化网络的导电效率。然后,基于预测的RVE计算薄层电阻和网络的透明度,以分析纳米线网络对导电膜的电学和光学性质的影响。本文介绍的结果提供了有助于优化透明导电膜中的随机纳米线网络以实现更高效率的见解。

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