Jagota Milind, Scheinfeld Isaac
Stanford University, Stanford, California 94305, USA.
Phys Rev E. 2020 Jan;101(1-1):012304. doi: 10.1103/PhysRevE.101.012304.
Films made from random nanowire arrays are an attractive choice for electronics requiring flexible transparent conductive films. However, thus far there has been no unified theory for predicting their electrical conductivity. In particular, the effects of orientation distribution on network conductivity remain poorly understood. We present a simplified analytical model for random nanowire network electrical conductivity that accurately captures the effects of arbitrary nanowire orientation distributions on conductivity. Our model is an upper bound and converges to the true conductivity as nanowire density grows. The model replaces Monte Carlo sampling with an asymptotically faster computation and in practice can be computed much more quickly than standard computational models. The success of our approximation provides theoretical insight into how nanowire orientation affects electrical conductivity.
由随机纳米线阵列制成的薄膜对于需要柔性透明导电薄膜的电子产品来说是一个有吸引力的选择。然而,到目前为止,还没有用于预测其电导率的统一理论。特别是,取向分布对网络电导率的影响仍然知之甚少。我们提出了一个用于随机纳米线网络电导率的简化分析模型,该模型准确地捕捉了任意纳米线取向分布对电导率的影响。我们的模型是一个上限,并且随着纳米线密度的增加收敛到真实电导率。该模型用渐近更快的计算取代了蒙特卡罗采样,并且在实践中可以比标准计算模型更快地计算出来。我们近似方法的成功为纳米线取向如何影响电导率提供了理论见解。