def test_turbomole_au13():
from ase.cluster.cubic import FaceCenteredCubic
from ase.calculators.turbomole import Turbomole
surfaces = [(1, 0, 0), (1, 1, 0), (1, 1, 1)]
layers = [1, 2, 1]
atoms = FaceCenteredCubic('Au', surfaces, layers, latticeconstant=4.08)
params = {
'title': 'Au13-',
'task': 'energy',
'basis set name': 'def2-SV(P)',
'total charge': -1,
'multiplicity': 1,
'use dft': True,
'density functional': 'pbe',
'use resolution of identity': True,
'ri memory': 1000,
'use fermi smearing': True,
'fermi initial temperature': 500,
'fermi final temperature': 100,
'fermi annealing factor': 0.9,
'fermi h**o-lumo gap criterion': 0.09,
'fermi stopping criterion': 0.002,
'scf energy convergence': 1.e-4,
'scf iterations': 250
}
calc = Turbomole(**params)
atoms.calc = calc
calc.calculate(atoms)
# use the get_property() method
print(calc.get_property('energy'))
print(calc.get_property('dipole'))
# test restart
params = {'task': 'gradient', 'scf energy convergence': 1.e-6}
calc = Turbomole(restart=True, **params)
assert calc.converged
calc.calculate()
print(calc.get_property('energy'))
print(calc.get_property('forces'))
print(calc.get_property('dipole'))
if use_asap:
from asap3 import EMT
size = 4
else:
from ase.calculators.emt import EMT
size = 2
# Set up a nanoparticle
atoms = FaceCenteredCubic('Cu',
surfaces=[[1, 0, 0], [1, 1, 0], [1, 1, 1]],
layers=(size, size, size),
vacuum=4)
# Describe the interatomic interactions with the Effective Medium Theory
atoms.calc = EMT()
# Do a quick relaxation of the cluster
qn = QuasiNewton(atoms)
qn.run(0.001, 10)
# Set the momenta corresponding to T=1200K
MaxwellBoltzmannDistribution(atoms, temperature_K=1200)
Stationary(atoms) # zero linear momentum
ZeroRotation(atoms) # zero angular momentum
# We want to run MD using the VelocityVerlet algorithm.
# Save trajectory:
dyn = VelocityVerlet(atoms, 5 * units.fs, trajectory='moldyn4.traj')