Fleur Spin-Spiral Dispersion workchain

  • Current version: 0.1.0
  • Class: FleurSSDispConvWorkChain
  • String to pass to the WorkflowFactory(): fleur.ssdisp_conv
  • Workflow type: Scientific workchain, self-consistent subgroup
  • Aim: Calculate spin-spiral energy dispersion over given q-points.

Import Example:

from aiida_fleur.workflows.ssdisp_conv import FleurSSDispConvWorkChain
#or
WorkflowFactory('fleur.ssdisp_conv')

Description/Purpose

This workchain calculates spin spiral energy dispersion over a given set of q-points. Charge density is converged for all given q-points which means a FleurScfWorkChain is submitted for each q-point. This requires more computational cost than FleurMaeWorkChain but gives more accurate results.

Input nodes

  • fleur: Code - Fleur code using the fleur.fleur plugin
  • inpgen, optional: Code - Inpgen code using the fleur.inpgen plugin
  • wf_parameters: Dict, optional - Settings of the workflow behavior
  • structure: StructureData, optional: Crystal structure data node.
  • calc_parameters: Dict, optional - FLAPW parameters, used by inpgen
  • options: Dict, optional - AiiDA options (queues, cpus)

Returns nodes

  • out (ParameterData): Information of workflow results like success, last result node, list with convergence behavior

Default inputs

Workflow parameters.

wf_parameters_dict = {
    'fleur_runmax': 10,
    'beta': {'all' : 1.57079},
    'q_vectors': {'label': [0.0, 0.0, 0.0],
                  'label2': [0.125, 0.0, 0.0]
                 },
    'alpha_mix': 0.05,
    'density_converged': 0.00005,
    'serial': False,
    'itmax_per_run': 30,
    'soc_off': [],
    'inpxml_changes': [],
}

Layout

Still has to be documented

Example usage

Still has to be documented

Output node example

Still has to be documented

Error handling

Still has to be documented