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.set_calculator(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.set_calculator(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, 1200 * units.kB) 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')
'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.set_calculator(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'))