new_contents: 
  StructureData = DataFactory('structure')
  ParameterData = DataFactory('parameter')
  
  import numpy as np
  
  
  cell = [[ 3.987594, 0.000000, 0.000000],
          [-1.993797, 3.453358, 0.000000],
          [ 0.000000, 0.000000, 6.538394]]
  
  symbols=['Ar'] * 2
  scaled_positions = [(0.33333,  0.66666,  0.25000),
                      (0.66667,  0.33333,  0.75000)]
  
  structure = StructureData(cell=cell)
  positions = np.dot(scaled_positions, cell)
  
  for i, scaled_position in enumerate(scaled_positions):
      structure.append_atom(position=np.dot(scaled_position, cell).tolist(),
                            symbols=symbols[i])
  
  structure.store()
  
  # Example LJ parameters for Argon. These may not be accurate at all
  potential ={'pair_style': 'lennard_jones',
              #                 epsilon,  sigma, cutoff
              'data': {'1  1':  '0.01029    3.4    5.0',
                       #'2  2':   '1.0      1.0    2.5',
                       #'1  2':   '1.0      1.0    2.5'
                       }}
  
  
  lammps_machine = {
      'num_machines': 1,
      'parallel_env': 'mpi*',
      'tot_num_mpiprocs': 16}
  
  
  parameters_opt = {'relaxation': 'tri',  # iso/aniso/tri
                    'pressure': 0.0,  # bars
                    'vmax': 0.000001,  # Angstrom^3
                    'energy_tolerance': 1.0e-25,  # eV
                    'force_tolerance': 1.0e-25,  # eV angstrom
                    'max_evaluations': 1000000,
                    'max_iterations': 500000}
  
  # Cluster information
  machine_dict = {
      'num_machines': 1,
      'parallel_env':'mpi*',
      'tot_num_mpiprocs' : 16}
  
  
  # Phonopy input parameters
  ph_dict = ParameterData(dict={'supercell': [[3,0,0],
                                              [0,3,0],
                                              [0,0,3]],
                                'primitive': [[1.0, 0.0, 0.0],
                                              [0.0, 1.0, 0.0],
                                              [0.0, 0.0, 1.0]],
                                'distance': 0.01,
                                'mesh' : [50, 50, 50]}
                         ).store()
  
  
  # Collect workflow input data
  wf_parameters = {
       'structure': structure,
       'phonopy_input': ph_dict,
       'input_force': {'code': 'lammps_force@boston',
                        'potential': potential,
                        'resources': lammps_machine},
       'input_optimize': {'code': 'lammps_optimize@boston',
                           'potential': potential,
                           'parameters': parameters_opt,
                           'resources': lammps_machine},
      }
  
  #Submit workflow
  from aiida.workflows.wf_gruneisen import WorkflowGruneisen
  wf = WorkflowGruneisen(params=wf_parameters)
  
  wf.label = 'Gruneisen LJ Ar'
  wf.start()
  print ('pk: {}'.format(wf.pk))
  
subject: Add gruneisen lauch example