Fleur equation of states (eos) workflow 

Current version: 0.3.5
Class: FleurEosWorkChain
String to pass to the WorkflowFactory(): fleur.eos
Workflow type: Technical
Aim: Vary the cell volume, to fit an equation of states, (Bulk modulus, …)

Contents

Fleur equation of states (eos) workflow

Import Example:

from aiida_fleur.workflows.eos import fleur_eos_wc
#or
WorkflowFactory('fleur.eos')

Description/Purpose 

Calculates equation of states for a given crystal structure.

First, an input structure is scaled and a list of scaled structures is constructed. Then, total energies of all the scaled structures are calculated via FleurScfWorkChain (SCF). Finally, resulting total energies are fitted via the Birch–Murnaghan equation of state and the cell volume corresponding to the lowest energy is evaluated. Other fit options are also available.

Input nodes 

The FleurEosWorkChain employs exposed feature of the AiiDA-core, thus inputs for the SCF sub-workchain should be passed in the namespace called scf (see example of usage). Please note that the structure input node is excluded from the scf namespace since the EOS workchain should process input structure before performing energy calculations.

name	type	description	required
scf	namespace	inputs for nested SCF WorkChain. structure input is excluded	no
wf_parameters	`Dict`	Settings of the workchain	no
structure	`StructureData`	input structure	no

Returns nodes 

name	type	comment
output_eos_wc_para	`Dict`	results of the workchain
output_eos_wc_structure	`StructureData`	Crystal structure with the volume of the lowest total energy

Layout 

Database Node graph 

from aiida_fleur.tools.graph_fleur import draw_graph

draw_graph(49670)

Plot_fleur visualization 

Single node

from aiida_fleur.tools.plot import plot_fleur

plot_fleur(49670)

Multi node

from aiida_fleur.tools.plot import plot_fleur

plot_fleur(eos_pk_list)

Example usage 

# -*- coding: utf-8 -*-
from aiida_fleur.workflows.ssdisp import FleurSSDispWorkChain
from aiida.orm import Dict, load_node

fleur_code = load_node(FLEUR_PK)
inpgen_code = load_node(INPGEN_PK)
structure = load_node(STRUCTURE_PK)

wf_para = Dict(dict={'points': 9,
                     'step': 0.002,
                     'guess': 1.00
                     })


wf_para_scf = Dict(dict={'fleur_runmax': 2,
                        'itmax_per_run': 120,
                        'density_converged': 0.2,
                        'mode': 'density'
               })


options_scf = Dict(dict={'resources': {'num_machines': 1, 'num_mpiprocs_per_machine': 8},
                         'queue_name': 'devel',
                         'custom_scheduler_commands': '',
                         'max_wallclock_seconds':  60*60})

inputs = {'scf': {
                  'wf_parameters': wf_para_scf,
                  'calc_parameters': parameters,
                  'options': options_scf,
                  'inpgen': inpgen_code,
                  'fleur': fleur_code
                 },
          'wf_parameters': wf_para,
          'structure': structure
}

SCF_workchain = submit(FleurSSDispWorkChain,
                       fleur=fleur_code,
                       inpgen=inpgen_code,
                       calc_parameters=calc_parameters,
                       structure=structure,
                       wf_parameters=wf_para,
                       options=options)

Output node example 

# -*- coding: utf-8 -*-
{
  'bulk_deriv': -612.513884563477,
  'bulk_modulus': 29201.4098068761,
  'bulk_modulus_units': 'GPa',
  'calculations': [],
  'distance_charge': [
    4.4141e-06,
    4.8132e-06,
    1.02898e-05,
    1.85615e-05
  ],
  'distance_charge_units': 'me/bohr^3',
  'errors': [],
  'guess': 1.0,
  'info': [
    'Consider refining your basis set.'
  ],
  'initial_structure': 'd6985712-7eca-4730-991f-1d924cbd1062',
  'natoms': 1,
  'nsteps': 4,
  'residuals': [],
  'scaling': [
    0.998,
    1.0,
    1.002,
    1.004
  ],
  'scaling_gs': 1.00286268683922,
  'scf_wfs': [],
  'stepsize': 0.002,
  'structures': [
    'f7fddbb5-51af-4dac-a4ba-021d1bf5795b',
    '28e9ed28-837c-447e-aae7-371b70454dc4',
    'fc340850-1a54-4be4-abed-576621b3015f',
    '77fd128b-e88c-4d7d-9aea-d909166926cb'
  ],
  'successful': true,
  'total_energy': [
    -439902.565469453,
    -439902.560450163,
    -439902.564547518,
    -439902.563105211
  ],
  'total_energy_units': 'Htr',
  'volume_gs': 16.2724654374658,
  'volume_units': 'A^3',
  'volumes': [
    16.1935634057491,
    16.2260154366224,
    16.2584674674955,
    16.290919498369
  ],
  'warnings': [
    'Abnormality in Total energy list detected. Check entr(ies) [1].'
  ],
  'workflow_name': 'fleur_eos_wc',
  'workflow_version': '0.3.3'
}

Error handling 

Total energy check:

The workflow quickly checks the behavior of the total energy for outliers. Which might occur, because the chosen FLAPW parameters might not be good for all volumes. Also local Orbital setup and so on might matter.

Not enough points for fit
Some calculations did not converge
Volume ground state does not lie in the calculated interval, interval refinement

Exit codes 

A list of implemented exit codes:

Code	Meaning
230	Invalid workchain parameters