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BandUPpy: Python Package for Band Unfolding of Plane-wave Based First-Principles Calculations.

Project description

BandUPpy: Python Package for Band Unfolding of Plane-wave Based First-Principles Calculations

Note: This is a Python version to the BandUP code (not to be confused with bandupy - the interface and plotting tool of BandUP), made in order to restore support for modern versions of QuantumEspresso and other codes. In order ot read the wavefunctions stored by ab-initio codes, the routines of irrep are used.

Unfolded band structure - flatband mode (Si0.5Ge0.5, Red: unfolded, gray: folded) Unfolded band structure - density mode (Si0.5Ge0.5) Band structures overlay (Si0.5Ge0.5: Red, pure Si: black, pure Ge: blue)
Band centers and band width (Si0.5Ge0.5) Band centers (Al0.84Ga0.16N) SCF fitting of good band centers (Al0.84Ga0.16N5)

Developers and contributors

BandUPpy Package Developer/Maintainer: Stepan S. Tsirkin, Badal Mondal

BandUPpy Contributors: Contributors

  • We sincerely thank each and every contributor for their valuable input and support.

Contact us: Email developer/maintainer team

  • If you would like to contribute to the development of BandUPpy or request new functionality, please get in touch with us or open a pull request. We appreciate and respect our users' views and are committed to providing the best experience possible. Your feedback is highly valued. We will be happy to support your request ASAP.

Special mention: BandUPpy originated from the ideas and implementation developed in the original BandUP code. BandUP was originally developed by Paulo V. C. Medeiros (then at Linköping University, presently at the Swedish Meteorological and Hydrological Institute), Jonas Björk (Linköping University), and Stepan S. Tsirkin.

Installation

1. Requirements

    1. python>=3.7
    2. collections
    3. numpy
    4. pickle
    5. scipy>=1.0
    6. irrep>=2.6.3
    7. matplotlib
    8. ase (optional)

2. Installation using pip [*recommended]

    pip install banduppy

3. Installation from github repository

    git clone https://github.com/band-unfolding/banduppy.git
    cd banduppy
    pip install .  

Or, without cloning

    pip install git+https://github.com/band-unfolding/banduppy.git #@specific_branch

Plane-wave codes currently supported by BandUPpy

At the moment, BandUPpy can parse wavefunctions generated by:

Usage

Documentation: here

The detailed documentation is available here. Explore the tutorial folder for example tutorials. Below are quick snippets showcasing what you can achieve with BandUPpy:

banduppy package:
    1. Unfolding class 
        1.1 propose_maximum_minimum_folding()
        1.2 generate_SC_Kpts_from_pc_kpts()
        1.3 generate_SC_Kpts_from_pc_k_path()
        1.3 Unfold()
        1.4 plot_ebs() [Note: Similar to Plotting class but can not plot band centers]
    2. Properties class
        2.1 collect_bandstr_data_only_in_energy_window()
        2.2 band_centers_broadening_bandstr()
        2.3 calculate_effecfive_mass()
        2.4 effective_mass_fit_functions()
        2.5 calculate_alloy_scattering_potential()
        2.6 alloy_scattering_lifetime_function()
    3. SaveBandStructuredata class
        3.1 save_unfolded_pc_kpts()
        3.2 save_unfolded_bandstucture()
        3.3 save_merge_unfolded_kp_bd_data()
        3.4 save_unfolded_bandcenter()
    4. Plotting class
        4.1 plot_ebs()
        4.2 plot_scf()
        4.3 save_plot_figure()
    5. HighLevelProperties class
        5.1 scf_refine_effecfive_mass_calculator()
        5.2 calculate_effective_masses()
        5.3 merge_zero_weight_2_sc_kpoint_file()

Tips and tricks:

FAQs: here

You can find a list of common user issues encountered while using this software here. We appreciate and respect our users' views and are committed to providing the best experience possible. Your feedback is highly valued.

Citations and references:

If you use BandUPpy in your work, please:

  • State EXPLICITLY that you have used the BandUPpy code (or a modified version of it, if this is the case), for instance, adding a sentence like:

     "The unfolding has been performed using the BandUPpy code"
    
  • How to cite the package: (use appropriate version number and doi corresponding to your installed banduppy)

  1. <author_list>, "band-unfolding/banduppy: version-0.3.5 (v0.3.5))". Zenodo, 2026. doi:10.5281/zenodo.XXXXX
  2. Mikel Iraola, Juan L. Mañes, Barry Bradlyn, Titus Neupert, Maia G. Vergniory, Stepan S. Tsirkin, "IrRep: Symmetry eigenvalues and irreducible representations of ab initio band structures", Comput. Phys. Commun. 272, 108226 (2022)
  • Read and cite the following papers (and the appropriate references therein):
  1. Paulo V. C. Medeiros, Sven Stafström, and Jonas Björk, Phys. Rev. B 89, 041407(R) (2014)
  2. Paulo V. C. Medeiros, Stepan S. Tsirkin, Sven Stafström, and Jonas Björk, Phys. Rev. B 91, 041116(R) (2015)

If you use the band center determination or effective mass modules/functions from BandUPpy in your work, please:

  • Additionally read and cite the following papers (and the appropriate references therein):
  1. TBA

If you use the alloy scattering modules/functions from BandUPpy in your work, please:

  • Additionally read and cite the following papers (and the appropriate references therein):
  1. TBA
  2. Nick Pant, Zihao Deng, and Emmanouil Kioupakis, Appl. Phy. Lett. 117, 242105 (2020)

Bibliography file: Here is the bibliography file for your convenience.

Version release

Chekout out version release history here for the full list of updates and upgrades.

License

BandUPpy is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, either version 3 of the License, or (at your option) any later version.

BandUPpy is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License for more details: GNU General Public License v3.0

Upcoming (TBD)

  1. Inverse participation ratio implementation
  2. Orbital contribution projection implementation
  3. Set up wiki

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