论文标题
石墨烯纳米替比网络中的量子传输：通过网络删除算法降低复杂性
Quantum transport in graphene nanoribbon networks: complexity reduction by a network decimation algorithm
论文作者
论文摘要
我们在介质长度尺度上研究石墨烯纳米甲（GNR）网络中的电子量子传输。我们专注于曲折的GNR，并研究统计网络的电导属性。为此，我们使用基于密度功能的紧密结合模型来确定电子结构和量子传输理论来计算电子传输特性。然后，我们引入了一种新的高效网络分解算法，该算法降低了通用三元GNR网络中的复杂性。我们将结果与基于节点分析方法的半古典计算进行了比较，并讨论电导对网络密度和网络大小的依赖性。我们表明，节点分析模型不能很好地重现量子传输结果，也不能很好地依赖于模型参数。因此，必须通过我们的有效方法来解决量子网络，以精确地对通过GNR网络进行电子传输进行准确建模。
We study electronic quantum transport in graphene nanoribbon (GNR) networks on mesoscopic length scales. We focus on zigzag GNRs and investigate the conductance properties of statistical networks. To this end we use a density-functional-based tight-binding model to determine the electronic structure and quantum transport theory to calculate electronic transport properties. We then introduce a new efficient network decimation algorithm that reduces the complexity in generic three-diemnsional GNR networks. We compare our results to semi-classical calculations based on the nodal analysis approach and discuss the dependence of the conductance on network density and network size. We show that a nodal analysis model cannot reproduce the quantum transport results nor their dependence on model parameters well. Thus, solving the quantum network by our efficient approach is mandatory for accurate modelling the electron transport through GNR networks.
