Abstract It is well-known that the morphology of nanostructured networks is closely linked to network properties. However, controlling and characterizing the morphology of networks of 2D nanosheets has not been explored. In this work, we use networks of liquid-exfoliated graphene nanosheets as a model system to examine the relationship between network morphology and conductivity in nanosheet networks. We use a combination of heat and pressure to controllably alter the morphology of the network, resulting in the annihilation of large pores (>40 nm) and improved nanosheet alignment within the sample. Such compression can result in a tenfold increase in network conductivity. Analysis shows both in-plane and out-of-plane conductivities to scale with porosity in line with percolation theory. The conductivity anisotropy was ∼3000 at low-porosity and was projected to fall to 1 in the limit of high porosity. Computational studies link the conductivity increase to an increase in network connectivity and a reduction in junction resistance as the porosity is decreased.

中文翻译：

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纳米片网络形貌与电导率的关系

摘要 众所周知，纳米结构网络的形态与网络性质密切相关。然而，尚未探索控制和表征二维纳米片网络的形态。在这项工作中，我们使用液体剥离的石墨烯纳米片网络作为模型系统来检查纳米片网络中网络形态和电导率之间的关系。我们使用热量和压力的组合来可控地改变网络的形态，从而消除大孔（> 40 nm）并改善样品内的纳米片排列。这种压缩可导致网络电导率增加十倍。分析显示面内和面外电导率与渗透理论一致，与孔隙率成比例。低孔隙度下的电导率各向异性约为 3000，预计在高孔隙度时降至 1。计算研究将电导率的增加与网络连通性的增加和结电阻的降低联系起来，因为孔隙率降低。