bandstructure.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "https://wiki.fysik.dtu.dk/gpaw/tutorials/bandstructures/bandstructures.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "from ase.build import bulk\n",
    "from gpaw import GPAW, PW, FermiDirac"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Perform standard ground state calculation (with plane wave basis)\n",
    "si = bulk('Si', 'diamond', 5.43)\n",
    "calc = GPAW(mode=PW(200),\n",
    "            xc='PBE',\n",
    "            kpts=(8, 8, 8),\n",
    "            random=True,  # random guess (needed if many empty bands required)\n",
    "            occupations=FermiDirac(0.01),\n",
    "            txt='Si_gs.txt')\n",
    "si.calc = calc\n",
    "si.get_potential_energy()\n",
    "calc.write('Si_gs.gpw')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "  ___ ___ ___ _ _ _  \n",
      " |   |   |_  | | | | \n",
      " | | | | | . | | | | \n",
      " |__ |  _|___|_____|  19.8.1\n",
      " |___|_|             \n",
      "\n",
      "User:   jovyan@jupyter-jan-2djanssen-2dgpaw-2dexample-2dpqzidpti\n",
      "Date:   Tue Apr  7 18:01:16 2020\n",
      "Arch:   x86_64\n",
      "Pid:    151\n",
      "Python: 3.7.3\n",
      "gpaw:   /srv/conda/envs/notebook/lib/python3.7/site-packages/gpaw\n",
      "_gpaw:  /srv/conda/envs/notebook/lib/python3.7/site-packages/\n",
      "        _gpaw.cpython-37m-x86_64-linux-gnu.so\n",
      "ase:    /srv/conda/envs/notebook/lib/python3.7/site-packages/ase (version 3.18.0)\n",
      "numpy:  /srv/conda/envs/notebook/lib/python3.7/site-packages/numpy (version 1.17.2)\n",
      "scipy:  /srv/conda/envs/notebook/lib/python3.7/site-packages/scipy (version 1.3.1)\n",
      "libxc:  4.3.4\n",
      "units:  Angstrom and eV\n",
      "cores:  1\n",
      "\n",
      "Reading from Si_gs.gpw\n",
      "Read dipole, energy, free_energy\n",
      "Reading input parameters:\n",
      "  kpts: [8 8 8]\n",
      "  mode: {ecut: 200.0,\n",
      "         gammacentered: False,\n",
      "         name: pw}\n",
      "  occupations: {name: fermi-dirac,\n",
      "                width: 0.01}\n",
      "  random: True\n",
      "  xc: PBE\n",
      "\n",
      "Initialize ...\n",
      "\n",
      "Si-setup:\n",
      "  name: Silicon\n",
      "  id: ee77bee481871cc2cb65ac61239ccafa\n",
      "  Z: 14\n",
      "  valence: 4\n",
      "  core: 10\n",
      "  charge: 0.0\n",
      "  file: /home/jovyan/gpaw-setups-0.9.20000/Si.PBE.gz\n",
      "  compensation charges: gauss, rc=0.33, lmax=2\n",
      "  cutoffs: 1.86(filt), 2.06(core),\n",
      "  valence states:\n",
      "                energy  radius\n",
      "    3s(2.00)   -10.812   1.058\n",
      "    3p(2.00)    -4.081   1.058\n",
      "    *s          16.399   1.058\n",
      "    *p          23.130   1.058\n",
      "    *d           0.000   1.058\n",
      "\n",
      "  Using partial waves for Si as LCAO basis\n",
      "\n",
      "Reference energy: -15772.688500\n",
      "\n",
      "Spin-paired calculation\n",
      "\n",
      "Occupation numbers:\n",
      "  Fermi-Dirac: width=0.0100 eV\n",
      "\n",
      "Convergence criteria:\n",
      "  Maximum total energy change: 0.0005 eV / electron\n",
      "  Maximum integral of absolute density change: 0.0001 electrons\n",
      "  Maximum integral of absolute eigenstate change: 4e-08 eV^2\n",
      "  Maximum number of iterations: 333\n",
      "\n",
      "Symmetries present (total): 24\n",
      "\n",
      "  ( 1  0  0)  ( 1  0  0)  ( 1  0 -1)  ( 1  0 -1)  ( 1 -1  0)  ( 1 -1  0)\n",
      "  ( 0  1  0)  ( 0  0  1)  ( 0  1 -1)  ( 0  0 -1)  ( 0 -1  1)  ( 0 -1  0)\n",
      "  ( 0  0  1)  ( 0  1  0)  ( 0  0 -1)  ( 0  1 -1)  ( 0 -1  0)  ( 0 -1  1)\n",
      "\n",
      "  ( 0  1  0)  ( 0  1  0)  ( 0  1 -1)  ( 0  1 -1)  ( 0  0  1)  ( 0  0  1)\n",
      "  ( 1  0  0)  ( 0  0  1)  ( 1  0 -1)  ( 0  0 -1)  ( 1  0  0)  ( 0  1  0)\n",
      "  ( 0  0  1)  ( 1  0  0)  ( 0  0 -1)  ( 1  0 -1)  ( 0  1  0)  ( 1  0  0)\n",
      "\n",
      "  ( 0  0 -1)  ( 0  0 -1)  ( 0 -1  1)  ( 0 -1  1)  ( 0 -1  0)  ( 0 -1  0)\n",
      "  ( 1  0 -1)  ( 0  1 -1)  ( 1 -1  0)  ( 0 -1  0)  ( 1 -1  0)  ( 0 -1  1)\n",
      "  ( 0  1 -1)  ( 1  0 -1)  ( 0 -1  0)  ( 1 -1  0)  ( 0 -1  1)  ( 1 -1  0)\n",
      "\n",
      "  (-1  1  0)  (-1  1  0)  (-1  0  1)  (-1  0  1)  (-1  0  0)  (-1  0  0)\n",
      "  (-1  0  1)  (-1  0  0)  (-1  1  0)  (-1  0  0)  (-1  1  0)  (-1  0  1)\n",
      "  (-1  0  0)  (-1  0  1)  (-1  0  0)  (-1  1  0)  (-1  0  1)  (-1  1  0)\n",
      "Note: your k-points are not as symmetric as your crystal!\n",
      "\n",
      "512 k-points: 8 x 8 x 8 Monkhorst-Pack grid\n",
      "60 k-points in the irreducible part of the Brillouin zone\n",
      "       k-points in crystal coordinates                weights\n",
      "   0:     0.06250000    0.06250000   -0.06250000          6/512\n",
      "   1:     0.06250000    0.06250000    0.06250000          2/512\n",
      "   2:     0.18750000   -0.06250000   -0.06250000          6/512\n",
      "   3:     0.18750000    0.06250000   -0.18750000         12/512\n",
      "   4:     0.18750000    0.06250000   -0.06250000         12/512\n",
      "   5:     0.18750000    0.06250000    0.06250000          6/512\n",
      "   6:     0.18750000    0.18750000   -0.18750000          6/512\n",
      "   7:     0.18750000    0.18750000   -0.06250000          6/512\n",
      "   8:     0.18750000    0.18750000    0.06250000          6/512\n",
      "   9:     0.18750000    0.18750000    0.18750000          2/512\n",
      "          ...\n",
      "  59:     0.43750000    0.43750000    0.43750000          2/512\n",
      "\n",
      "Wave functions: Plane wave expansion\n",
      "  Cutoff energy: 200.000 eV\n",
      "  Number of coefficients (min, max): 251, 271\n",
      "  Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n",
      "  Using FFTW library\n",
      "  ScaLapack parameters: grid=1x1, blocksize=None\n",
      "  Wavefunction extrapolation:\n",
      "    Improved wavefunction reuse through dual PAW basis \n",
      "\n",
      "Eigensolver\n",
      "   Davidson(niter=2, smin=None, normalize=True) \n",
      "\n",
      "Densities:\n",
      "  Coarse grid: 14*14*14 grid\n",
      "  Fine grid: 28*28*28 grid\n",
      "  Total Charge: 0.000000 \n",
      "\n",
      "Density mixing:\n",
      "  Method: separate\n",
      "  Backend: pulay\n",
      "  Linear mixing parameter: 0.05\n",
      "  Mixing with 5 old densities\n",
      "  Damping of long wave oscillations: 50 \n",
      "\n",
      "Hamiltonian:\n",
      "  XC and Coulomb potentials evaluated on a 28*28*28 grid\n",
      "  Using the PBE Exchange-Correlation functional\n",
      " \n",
      "\n",
      "XC parameters: PBE with 2 nearest neighbor stencil\n",
      "\n",
      "Memory estimate:\n",
      "  Process memory now: 117.42 MiB\n",
      "  Calculator: 5.63 MiB\n",
      "    Density: 1.03 MiB\n",
      "      Arrays: 0.54 MiB\n",
      "      Localized functions: 0.27 MiB\n",
      "      Mixer: 0.21 MiB\n",
      "    Hamiltonian: 0.36 MiB\n",
      "      Arrays: 0.36 MiB\n",
      "      XC: 0.00 MiB\n",
      "      Poisson: 0.00 MiB\n",
      "      vbar: 0.01 MiB\n",
      "    Wavefunctions: 4.24 MiB\n",
      "      Arrays psit_nG: 1.98 MiB\n",
      "      Eigensolver: 0.06 MiB\n",
      "      Projections: 0.19 MiB\n",
      "      Projectors: 1.65 MiB\n",
      "      PW-descriptor: 0.35 MiB\n",
      "\n",
      "Total number of cores used: 1\n",
      "\n",
      "Number of atoms: 2\n",
      "Number of atomic orbitals: 8\n",
      "Number of bands in calculation: 8\n",
      "Bands to converge: occupied states only\n",
      "Number of valence electrons: 8\n",
      "\n",
      "... initialized\n",
      "\n",
      "Input parameters:\n",
      "  convergence: {bands: 8}\n",
      "  fixdensity: True\n",
      "  kpts: {npoints: 60,\n",
      "         path: GXWKL}\n",
      "  nbands: 16\n",
      "  symmetry: off\n",
      "\n",
      "Initialize ...\n",
      "\n",
      "Si-setup:\n",
      "  name: Silicon\n",
      "  id: ee77bee481871cc2cb65ac61239ccafa\n",
      "  Z: 14\n",
      "  valence: 4\n",
      "  core: 10\n",
      "  charge: 0.0\n",
      "  file: /home/jovyan/gpaw-setups-0.9.20000/Si.PBE.gz\n",
      "  compensation charges: gauss, rc=0.33, lmax=2\n",
      "  cutoffs: 1.86(filt), 2.06(core),\n",
      "  valence states:\n",
      "                energy  radius\n",
      "    3s(2.00)   -10.812   1.058\n",
      "    3p(2.00)    -4.081   1.058\n",
      "    *s          16.399   1.058\n",
      "    *p          23.130   1.058\n",
      "    *d           0.000   1.058\n",
      "\n",
      "  Using partial waves for Si as LCAO basis\n",
      "\n",
      "Reference energy: -15772.688500\n",
      "\n",
      "Spin-paired calculation\n",
      "\n",
      "Occupation numbers:\n",
      "  Fixed Fermi level\n",
      "  Fermi-Dirac: width=0.0100 eV\n",
      "\n",
      "Convergence criteria:\n",
      "  Maximum total energy change: 0.0005 eV / electron\n",
      "  Maximum integral of absolute density change: 0.0001 electrons\n",
      "  Maximum integral of absolute eigenstate change: 4e-08 eV^2\n",
      "  Maximum number of iterations: 333\n",
      "\n",
      "Symmetries present (total): 1\n",
      "\n",
      "  ( 1  0  0)\n",
      "  ( 0  1  0)\n",
      "  ( 0  0  1)\n",
      "\n",
      "60 k-points\n",
      "60 k-points in the irreducible part of the Brillouin zone\n",
      "       k-points in crystal coordinates                weights\n",
      "   0:     0.00000000    0.00000000    0.00000000       0.01666667\n",
      "   1:     0.02173913    0.00000000    0.02173913       0.01666667\n",
      "   2:     0.04347826    0.00000000    0.04347826       0.01666667\n",
      "   3:     0.06521739    0.00000000    0.06521739       0.01666667\n",
      "   4:     0.08695652    0.00000000    0.08695652       0.01666667\n",
      "   5:     0.10869565    0.00000000    0.10869565       0.01666667\n",
      "   6:     0.13043478    0.00000000    0.13043478       0.01666667\n",
      "   7:     0.15217391    0.00000000    0.15217391       0.01666667\n",
      "   8:     0.17391304    0.00000000    0.17391304       0.01666667\n",
      "   9:     0.19565217    0.00000000    0.19565217       0.01666667\n",
      "          ...\n",
      "  59:     0.50000000    0.50000000    0.50000000       0.01666667\n",
      "\n",
      "Wave functions: Plane wave expansion\n",
      "  Cutoff energy: 200.000 eV\n",
      "  Number of coefficients (min, max): 246, 267\n",
      "  Pulay-stress correction: 0.000000 eV/Ang^3 (de/decut=0.000000)\n",
      "  Using FFTW library\n",
      "  ScaLapack parameters: grid=1x1, blocksize=None\n",
      "  Wavefunction extrapolation:\n",
      "    Improved wavefunction reuse through dual PAW basis \n",
      "\n",
      "Eigensolver\n",
      "   Davidson(niter=2, smin=None, normalize=True) \n",
      "\n",
      "No density mixing\n",
      "\n",
      "XC parameters: PBE with 2 nearest neighbor stencil\n",
      "\n",
      "Memory estimate:\n",
      "  Process memory now: 118.19 MiB\n",
      "  Calculator: 7.80 MiB\n",
      "    Density: 1.03 MiB\n",
      "      Arrays: 0.54 MiB\n",
      "      Localized functions: 0.27 MiB\n",
      "      Mixer: 0.21 MiB\n",
      "    Hamiltonian: 0.36 MiB\n",
      "      Arrays: 0.36 MiB\n",
      "      XC: 0.00 MiB\n",
      "      Poisson: 0.00 MiB\n",
      "      vbar: 0.01 MiB\n",
      "    Wavefunctions: 6.41 MiB\n",
      "      Arrays psit_nG: 3.91 MiB\n",
      "      Eigensolver: 0.13 MiB\n",
      "      Projections: 0.38 MiB\n",
      "      Projectors: 1.65 MiB\n",
      "      PW-descriptor: 0.35 MiB\n",
      "\n",
      "Total number of cores used: 1\n",
      "\n",
      "Number of atoms: 2\n",
      "Number of atomic orbitals: 8\n",
      "Number of bands in calculation: 16\n",
      "Bands to converge: 8 lowest bands\n",
      "Number of valence electrons: 8\n",
      "\n",
      "... initialized\n",
      "\n",
      "Initializing position-dependent things.\n",
      "\n",
      "Creating initial wave functions:\n",
      "  8 bands from LCAO basis set\n",
      "  8 bands from random numbers\n",
      "\n",
      "                    \n",
      "                    \n",
      "                    \n",
      "                    \n",
      "           Si       \n",
      "                    \n",
      "       Si           \n",
      "                    \n",
      "                    \n",
      "                    \n",
      "                    \n",
      "\n",
      "Positions:\n",
      "   0 Si     0.000000    0.000000    0.000000    ( 0.0000,  0.0000,  0.0000)\n",
      "   1 Si     1.357500    1.357500    1.357500    ( 0.0000,  0.0000,  0.0000)\n",
      "\n",
      "Unit cell:\n",
      "           periodic     x           y           z      points  spacing\n",
      "  1. axis:    yes    0.000000    2.715000    2.715000    14     0.2239\n",
      "  2. axis:    yes    2.715000    0.000000    2.715000    14     0.2239\n",
      "  3. axis:    yes    2.715000    2.715000    0.000000    14     0.2239\n",
      "\n",
      "  Lengths:   3.839590   3.839590   3.839590\n",
      "  Angles:   60.000000  60.000000  60.000000\n",
      "\n",
      "Effective grid spacing dv^(1/3) = 0.2443\n",
      "\n",
      "                     log10-error:    total        iterations:\n",
      "           time      wfs    density  energy       fermi  poisson\n",
      "iter:   1  18:01:54  +0.99          -10.226500    10            \n",
      "iter:   2  18:02:24  -0.52          -10.230231    10            \n",
      "iter:   3  18:02:50  -2.00          -10.230271    10            \n",
      "iter:   4  18:03:20  -3.50          -10.230272    10            \n",
      "iter:   5  18:03:50  -5.01          -10.230273    10            \n",
      "iter:   6  18:04:20  -6.55          -10.230273    10            \n",
      "iter:   7  18:04:53  -8.06          -10.230273    10            \n",
      "\n",
      "Converged after 7 iterations.\n",
      "\n",
      "Dipole moment: (-2.923917, -2.923917, -2.923917) |e|*Ang\n",
      "\n",
      "Energy contributions relative to reference atoms: (reference = -15772.688500)\n",
      "\n",
      "Kinetic:        +16.238408\n",
      "Potential:      -13.753300\n",
      "External:        +0.000000\n",
      "XC:             -12.665327\n",
      "Entropy (-ST):   -0.000000\n",
      "Local:           -0.050054\n",
      "--------------------------\n",
      "Free energy:    -10.230273\n",
      "Extrapolated:   -10.230273\n",
      "\n",
      "Fixed Fermi level: 5.83663\n",
      "\n",
      "Showing only first 2 kpts\n",
      " Kpt  Band  Eigenvalues  Occupancy\n",
      "  0     2      5.31705    0.03333\n",
      "  0     3      5.31705    0.03333\n",
      "  0     4      7.87649    0.00000\n",
      "  0     5      7.87649    0.00000\n",
      "\n",
      "  1     2      5.28120    0.03333\n",
      "  1     3      5.28120    0.03333\n",
      "  1     4      7.85600    0.00000\n",
      "  1     5      7.92258    0.00000\n",
      "\n",
      "\n",
      "Gap: 0.571 eV\n",
      "Transition (v -> c):\n",
      "  (s=0, k=0, n=3, [0.00, 0.00, 0.00]) -> (s=0, k=19, n=4, [0.41, 0.00, 0.41])\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "-10.230272532078548"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Restart from ground state and fix potential:\n",
    "calc = GPAW('Si_gs.gpw',\n",
    "            nbands=16,\n",
    "            fixdensity=True,\n",
    "            symmetry='off',\n",
    "            kpts={'path': 'GXWKL', 'npoints': 60},\n",
    "            convergence={'bands': 8})\n",
    "\n",
    "calc.get_potential_energy()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.axes._subplots.AxesSubplot at 0x7ff9ff1d3470>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "bs = calc.band_structure()\n",
    "bs.plot(filename='bandstructure.png', show=True, emax=10.0)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}