1. Overview

_images/graphical_abstract.webp

1.1. Features

Main
  • Pythonic implementation of density functional theory

  • Customizable workflows and developer-friendly code

  • Minimal dependencies and large platform support

  • Comparable and reproducible calculations

  • Example notebooks showcasing educational usage

Functionals
  • LDA
  • GGA
  • meta-GGA
  • Libxc
Potentials
  • All-electron Coulomb
  • GTH
SCF
  • Steepest descent
  • Line minimization
  • Conjugate gradient
  • Customizable schemes
Orbitals
  • Kohn-Sham
  • Fermi
  • Fermi-Löwdin
  • Wannier
  • SCDM
Properties
  • Energy contributions
  • Dipole moments
  • Ionization potentials
  • Orbital spreads
  • Centers of mass
  • Field properties
SIC
  • Fixed density SIC
  • FLO-SIC
  • PyCOM
Visualization
  • Molecules
  • Orbitals
  • Densities
  • Grids
  • Files
  • Contours
  • Brillouin zones
  • Band structures
Files
  • XYZ
  • TRAJ
  • CUBE
  • POSCAR
  • PDB
  • JSON
Domains
  • Spherical
  • Cuboidal
  • Isovalue

1.2. Workflow

The following code samples show the workflow of how a bandstructure of a silicon crystal can be created.

Create the unit cell and display it.

from eminus import Cell, SCF
from eminus.extras import plot_bandstructure

cell = Cell("Si", "diamond", ecut=10, a=10.2631, bands=8)
cell.view()
_images/cell.png

Run the DFT calculation.

scf = SCF(cell)
scf.run()

Define the band path and display the Brillouin zone.

scf.kpts.path = "LGXU,KG"
scf.kpts.Nk = 25
scf.kpts.build().view()
_images/bz.png

Calculate the eigenenergies and plot the band structure.

scf.converge_bands()
plot_bandstructure(scf)
_images/band_structure.png

Find this example with more comments in the examples section.