Publication date: Jul 05, 2024
We develop an accurate nanoelectronic modeling approach for realistic three-dimensional topological insulator nanostructures and investigate their low-energy surface-state spectrum. Starting from the commonly considered four-band k·p bulk model Hamiltonian for the Bi₂Se₃ family of topological insulators, we derive new parameter sets for Bi₂Se₃, Bi₂Te₃ and Sb₂Te₃. We consider a fitting strategy applied to ab initio band structures around the Γ point that ensures a quantitatively accurate description of the low-energy bulk and surface states, while avoiding the appearance of unphysical low-energy states at higher momenta, something that is not guaranteed by the commonly considered perturbative approach. We analyze the effects that arise in the low-energy spectrum of topological surface states due to band anisotropy and electron-hole asymmetry, yielding Dirac surface states that naturally localize on different side facets. In the thin-film limit, when surface states hybridize through the bulk, we resort to a thin-film model and derive thickness-dependent model parameters from ab initio calculations that show good agreement with experimentally resolved band structures, unlike the bulk model that neglects relevant many-body effects in this regime. Our versatile modeling approach offers a reliable starting point for accurate simulations of realistic topological material-based nanoelectronic devices. This dataset contains the data used in the corresponding publication.
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File name | Size | Description |
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README.md
MD5md5:0664106485de9fcd8a34562150ebce23
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2.1 KiB | Description of the dataset |
DFT_plots_paper.ipynb
MD5md5:c63b5d8a255fa5d78c4a10217ba4274d
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856.4 KiB | Plotting scripts for DFT part |
requirements_DFT_AiiDA.txt
MD5md5:ba62ccd489b84e11a2b3c920eb9943c9
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5.2 KiB | Requirements file for Python environment used in DFT part |
export_DFT.aiida
MD5md5:31b60118aaa0ca8ab6aa3eebbbb4de72
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4.2 GiB | AiiDA export file containing the DFT data |
fit_ab_initio.zip
MD5md5:edd1929c3ebf8bdd7fe8c983d8f90922
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8.7 MiB | Fitting of DFT data |
2024.106 (version v1) [This version] | Jul 05, 2024 | DOI10.24435/materialscloud:mx-bn |