Multiscale modeling of screening effects on conductivity of graphene in weakly bonded graphene-dielectric heterostructures
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Graphene is often surrounded by different dielectric materials when integrated into realistic devices. The absence of dangling bonds allows graphene to bond weakly via the van der Waals interaction with the adjacent material surfaces and to retain its peculiar linear band structure. In such weakly bonded systems, however, the electronic properties of graphene are affected by the dielectric screening due to the long-range Coulomb interaction with the surrounding materials. Including the surrounding materials in the first principles density functional theory (DFT) calculations is computationally very demanding due to the large supercell size required to model heterogeneous interfaces. Here, we employ a multiscale approach combining DFT and the classical image-potential model to investigate the effects of screening from the surrounding materials (hBN, SiC, SiO2, Al2O3, and HfO2) on the dielectric function and charged impurity scattering limited conductivity of graphene. In this approach, the graphene layer is modeled using DFT and the screening from the surrounding materials is incorporated by introducing an effective dielectric function. The dielectric function and conductivity of graphene calculated using the simplified two-band Dirac model are compared with DFT calculations. The two-band Dirac model is found to significantly overestimate the dielectric screening and charged impurity scattering limited conductivity of graphene. The multiscale approach presented here can also be used to study screening effects in weakly bonded heterostructures of other emerging two-dimensional materials such as metal dichalcogenides.
KeywordsGraphene Non-local screening van der Waals interaction 2D layered materials DFT
This work was supported in part by New York State Focus Center and in part by the NSF PetaApps grant number 0749140, and an anonymous gift from Rensselaer. The work was partly supported by Army Research Laboratory under the cooperative agreement number W911NF-12-2-0023. Computing resources of the Computational Center for Nanotechnology Innovations at Rensselaer partly funded by State of New York and of nanoHUB.org funded by the NSF have been used for this work.
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