Han Fei, Maloth Thirupathi, Lubineau Gilles, Yaldiz Recep, Tevtia Amit
King Abdullah University of Science and Technology (KAUST), Physical Science and Engineering Division, COHMAS Laboratory, Thuwal, 23955-6900, Saudi Arabia.
SABIC (Saudi Basic Industries Corporation), P.O. Box 319, 6160 AH, Geleen, The Netherlands.
Sci Rep. 2018 Nov 30;8(1):17494. doi: 10.1038/s41598-018-35456-7.
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.
银纳米线的随机网络已被考虑用于透明导电薄膜，以替代不适用于柔性器件的氧化铟锡（ITO）。然而，纳米线的随机分布使得这种导电薄膜不均匀。由于电导率是通过渗流过程实现的，了解宏观性质（如电导率）的尺度依赖性以及网络的确切效率（参与导电的纳米线比例）对于优化设计至关重要。在本文中，我们提出了一种计算方法来识别纳米线网络的代表性体积单元（RVE）。这定义了使用这种透明电极的器件中的最小像素尺寸。RVE用于计算薄膜的宏观性质并量化网络的导电效率。然后，基于预测的RVE计算网络的薄层电阻和透明度，以便分析纳米线网络对导电薄膜电学和光学性质的影响。本文给出的结果提供了有助于优化透明导电薄膜中的随机纳米线网络以实现更高效率的见解。
