Skip to main content

Utility to construct and operate on Hamiltonians from the Projections of DFT wfc on Atomic Orbital bases (PAO)

Project description

PAOFLOW

Utility to construct and operate on Hamiltonians from the Projections of DFT wfc on Atomic Orbital bases (PAO)

Copyright 2016-2020 - Marco BUONGIORNO NARDELLI (mbn@unt.edu)

PAOFLOW 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.

This program 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.

You should have received a copy of the GNU General Public License along with this program. If not, see http://www.gnu.org/licenses/.

PAOFLOW's capabilities:

  • Construction of PAO Hamiltonians from the DFT wavefunctions onto pseudo atomic orbitals
  • Hamiltonian data for further processing (ACBN0, PAOtransport, etc.)
  • External fields and non scf ACBN0 correction
  • Spin orbit correction of non SO calculations
  • Bands along standard paths in the BZ
  • Interpolation of Hamiltonians on arbitrary Monkhorst and Pack k-meshes
  • Adaptive smearing for BZ and Fermi surface integration
  • Density of states (and projected DOS)
  • Fermi surfaces and spin textures
  • Boltzmann transport (conductivity, Seebeck coefficient, electronic contribution to thermal conductivity
  • dielectric function (absorption coefficients and EELS)
  • Berry curvature and anomalous Hall conductivity (including magnetic circular dichroism spectra)
  • spin Berry curvature and spin Hall conductivity (including spin circular dichroism spectra)
  • Band topology (Z2 invariants, Berry and spin Berry curvature along standard paths in BZ, critical points

Example code for PAOFLOW is available on GitHub: https://github.com/marcobn/PAOFLOW/examples/

Use of PAOFLOW should reference:

M. Buongiorno Nardelli, F. T. Cerasoli, M. Costa, S Curtarolo,R. De Gennaro, M. Fornari, L. Liyanage, A. Supka and H. Wang, PAOFLOW: A utility to construct and operate on ab initio Hamiltonians from the Projections of electronic wavefunctions on Atomic Orbital bases, including characterization of topological materials, Comp. Mat. Sci. vol. 143, 462 (2018).

PAOFLOW is integrated in AFLOW𝛑:

A.R. Supka, T.E. Lyons, L. Liyanage, P. D'Amico, R. Al Rahal Al Orabi, S. Mahatara, P. Gopal, C. Toher, D. Ceresoli, A. Calzolari, S. Curtarolo, M. Buongiorno Nardelli, and M. Fornari, AFLOW𝛑: A minimalist approach to high-throughput ab initio calculations including the generation of tight-binding hamiltonians, Computational Materials Science, 136 (2017) 76-84. doi:10.1016/j.commatsci.2017.03.055 also at www.aflow.org/src/aflowpi

Contributions to PAOFLOW were made by the following developers: Frank Cerasoli, Andrew Supka, Marcio Costa, Laalitha Liyanage, Haihang Wang, Anooja Jayaraj, Jagoda Slawinska, Priya Gopal, Ilaria Siloi

Other references:

Luis A. Agapito, Andrea Ferretti, Arrigo Calzolari, Stefano Curtarolo and Marco Buongiorno Nardelli, Effective and accurate representation of extended Bloch states on finite Hilbert spaces, Phys. Rev. B 88, 165127 (2013).

Luis A. Agapito, Sohrab Ismail-Beigi, Stefano Curtarolo, Marco Fornari and Marco Buongiorno Nardelli, Accurate Tight-Binding Hamiltonian Matrices from Ab-Initio Calculations: Minimal Basis Sets, Phys. Rev. B 93, 035104 (2016).

Luis A. Agapito, Marco Fornari, Davide Ceresoli, Andrea Ferretti, Stefano Curtarolo and Marco Buongiorno Nardelli, Accurate Tight-Binding Hamiltonians for 2D and Layered Materials, Phys. Rev. B 93, 125137 (2016).

Pino D'Amico, Luis Agapito, Alessandra Catellani, Alice Ruini, Stefano Curtarolo, Marco Fornari, Marco Buongiorno Nardelli, and Arrigo Calzolari, Accurate ab initio tight-binding Hamiltonians: Effective tools for electronic transport and optical spectroscopy from first principles, Phys. Rev. B 94 165166 (2016).

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

PAOFLOW-2.0.5.tar.gz (78.4 kB view details)

Uploaded Source

Built Distributions

PAOFLOW-2.0.5-py3.7.egg (265.8 kB view details)

Uploaded Source

PAOFLOW-2.0.5-py3-none-any.whl (118.3 kB view details)

Uploaded Python 3

File details

Details for the file PAOFLOW-2.0.5.tar.gz.

File metadata

  • Download URL: PAOFLOW-2.0.5.tar.gz
  • Upload date:
  • Size: 78.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/49.1.0 requests-toolbelt/0.9.1 tqdm/4.42.1 CPython/3.7.6

File hashes

Hashes for PAOFLOW-2.0.5.tar.gz
Algorithm Hash digest
SHA256 2103ca4ef4ac3d7c03424d1d1ac6adff8408ba7534a33de57b1a20a8b743bb75
MD5 71fcf5b1221a040924ea94f182b9a55a
BLAKE2b-256 d6e0e40450449b2beb2dded4cd6d2cdbec12aa04f3b56156da61822680db3a30

See more details on using hashes here.

File details

Details for the file PAOFLOW-2.0.5-py3.7.egg.

File metadata

  • Download URL: PAOFLOW-2.0.5-py3.7.egg
  • Upload date:
  • Size: 265.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/45.2.0.post20200210 requests-toolbelt/0.9.1 tqdm/4.42.1 CPython/3.7.6

File hashes

Hashes for PAOFLOW-2.0.5-py3.7.egg
Algorithm Hash digest
SHA256 6b820b5981a1b2ec9a12331a8da48aad0bda184bad9a67c84078365b38c0d41e
MD5 2d1fb9ed5ce56e05c68f860aab081ef8
BLAKE2b-256 105c350b81d3154eee22f1164dc72fcbc6ab960ea4439f7d7a5202700033a2a5

See more details on using hashes here.

File details

Details for the file PAOFLOW-2.0.5-py3-none-any.whl.

File metadata

  • Download URL: PAOFLOW-2.0.5-py3-none-any.whl
  • Upload date:
  • Size: 118.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.2.0 pkginfo/1.5.0.1 requests/2.22.0 setuptools/49.1.0 requests-toolbelt/0.9.1 tqdm/4.42.1 CPython/3.7.6

File hashes

Hashes for PAOFLOW-2.0.5-py3-none-any.whl
Algorithm Hash digest
SHA256 251390d9adfbd36b79d185507f5249cf8bda5b16c3eb8626e58133215e38bdd5
MD5 921cd2f583b5c0eb78658a268891dae7
BLAKE2b-256 a3c7af189ebf1822c8f062f035060d0e375899a6c5e41a8e573b297ac6238902

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page