Computational Investigation of Electronic Properties and Transmission Coefficient in AA-Stacked Bilayer Graphene Using the Nearest-Neighbour Tight-Binding Model

AA-stacked bilayer graphene has gained prominence in materials science because of its exceptional electronic properties arising from enhanced π orbital overlaps and a stabilised band structure compared to that of monolayer graphene. This study employed a tailored nearest-neighbour tight-binding (NNT...

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Bibliographic Details
Main Authors: Yuki Wong, Nurul Ezaila Alias, Tian Swee Tan, Cheng Siong Lim, Michael Loong Peng Tan
Format: Article
Language:English
Published: Wiley 2025-01-01
Series:Journal of Nanotechnology
Online Access:http://dx.doi.org/10.1155/jnt/8555554
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Summary:AA-stacked bilayer graphene has gained prominence in materials science because of its exceptional electronic properties arising from enhanced π orbital overlaps and a stabilised band structure compared to that of monolayer graphene. This study employed a tailored nearest-neighbour tight-binding (NNTB) model for comprehensively investigating these electronic characteristics. Key properties, including the E-K dispersion relation, density of states (DOS) and transmission coefficients across various lattice dimensions, are explored using a MATLAB-based simulator integrating the NNTB approximation and nonequilibrium Green’s function equations. Electronic attributes of the zigzag- and armchair-edge configurations were analysed, which reveals that the zigzag variant behaves as a metal without a discernible bandgap, while the armchair variant exhibits semiconducting characteristics in the 3n−1 and 3n series and metallic characteristics in the 3n+1 series. Our findings confirm that DOS increases with both the system width and length for both edge types. The transmission coefficient shows a tendency to increase with device width but decrease with device length in both variants. These insights significantly contribute to advancing our understanding of the electronic dynamics of bilayer graphene, which is crucial for optimising the design and functionality of graphene-based devices.
ISSN:1687-9511