Electron density and transport in top-gated graphene nanoribbon devices: First-principles Green function algorithms for systems containing large number of atoms
Denis A. Areshkin, Branislav K. Nikolic

TL;DR
This paper develops efficient algorithms to enable first-principles quantum transport simulations of large graphene nanoribbon devices with thousands of atoms, facilitating detailed analysis of electron density and conductance under gating.
Contribution
It introduces a combination of two algorithms that extend NEGF-DFT methods to large-scale systems, allowing for accurate modeling of graphene nanoribbon devices with around 7000 atoms.
Findings
Large gate voltage may be needed to switch the device from insulating to conducting state.
The algorithms successfully simulate charge transfer and conductance in large GNR devices.
Self-consistent modeling predicts band gap tuning via gate voltage.
Abstract
The recent fabrication of graphene nanoribbon (GNR) field-effect transistors poses a challenge for first-principles modeling of carbon nanoelectronics due to many thousand atoms present in the device. The state of the art quantum transport algorithms, based on the nonequilibrium Green function formalism combined with the density functional theory (NEGF-DFT), were originally developed to calculate self-consistent electron density in equilibrium and at finite bias voltage (as a prerequisite to obtain conductance or current-voltage characteristics, respectively) for small molecules attached to metallic electrodes where only a few hundred atoms are typically simulated. Here we introduce combination of two numerically efficient algorithms which make it possible to extend the NEGF-DFT framework to device simulations involving large number of atoms. We illustrate fusion of these two algorithms…
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