Data from: Choosing tight-binding models for accurate optoelectronic responses
Data files
Feb 23, 2026 version files 363.16 KB
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Dryad_Data.zip
359.95 KB
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README.md
3.20 KB
Abstract
Tight-binding models provide great insight and are a low-cost alternative to ab initio methods for the calculation of a material’s electronic structure. These models are used to calculate optical responses, including nonlinear optical effects such as the shift current bulk photovoltaic effect. The validity of tight-binding models is often evaluated by comparing their band structures to those calculated with density functional theory. However, we find that band structure agreement is a necessary but not sufficient condition for accurate optical response calculations. We compute the shift current response and dielectric tensor using a variety of tight-binding models of MoS2, including both Slater-Koster and Wannier tight-binding models that treat the Mo 4d orbitals and/or S 3p orbitals. We also truncate hoppings in the Wannier function models to next-nearest-neighbor, as is common in tight-binding methods, in order to gauge the effect on optical response. By examining discrepancies in energies and optical matrix elements, we determine the interpolation quality of the different tight-binding models and establish that agreement in both band structure and wave functions is required to accurately model optical response.
Dataset DOI: 10.5061/dryad.3r2280gwt
Description of the data and file structure
This data was collected using the following techniques. For more information, consult the paper.
- Quantum Espresso - used for electronic structure calculations
- Wannier90 - used for Wannierization
- PythTB - used to generate tight-binding models
The data shown here is the final data that is plotted/shown in figures in the paper. All data should be viewable by a text editor, except for the Brillouin Zone data, which are .npy files.
Files and variables
File: Dryad_Data.zip
Description: Attached is the data for the article Choosing tight-binding models for accurate optoelectronic responses (https://journals.aps.org/prb/abstract/10.1103/PhysRevB.111.125203) in PRB. These data were used to generate the figures in the paper. The zipped data is organized into folders as follows:
- shiftcurrent- contains the shift current data for the DFT (one folder, files with .dat extensions) and tight-binding models (one folder for five band, one folder for eleven band, files with .txt extensions). One column is the photon energy in eV, the other column is the shift current tensor in A/V 2
- dielectric- contains the dielectric tensor data for the models mentioned above (one folder for DFT, one folder for five band, one folder for eleven band). The same file extensions were used as above. One column is the photon energy, the other column is the dielectric tensor (unitless)
- bz- contains the velocity matrix data (magnitude of the interband velocity between the highest valence band and lowest conduction band in m/s) on 40 x 40 grids of the Brillouin zone in Cartesian coordinates. These data are in .npy files since these are arrays. These are only for the tight-binding models, as these quantities were not computed for DFT.
- bandstructure- the data for the DFT band structure shown in the paper along a high symmetry path. This file is in a Quantum Espresso .gnu output that can be plotted in gnuplot. Energies are in eV.
- PDOS- the projected density of states shown in the paper. One file is the summed (total) DOS for the system, and the other files are orbital-specific projections. The orbital-specific files are named like MoS2_pdos.dat.pdos_atm#(atom)_wfc#(orbital type). These are formatted by Quantum Espresso. The columns are E (eV), ldos(E), and 2l+1 pdos(E) columns for an orbital of angular momentum quantum number l (so for p orbitals this is 3, for d orbitals this is 5). Energy values (in electron volts). ldos(E): represents the total density of states at each energy. It is the sum over all atoms and orbitals.
Code/software
All of the data here can be viewed with Python immediately, except for the .gnu file for the band structure. That can be viewed with gnuplot, or alternatively with Python, using a script like in the tutorial link here (https://pranabdas.github.io/espresso/hands-on/bands/).