vib = Vibrations(atoms, indices=vibrateatoms, delta=0.03)
vib.run()
vib.summary(method='standard')
# Make trajectory files to visualize the modes.
for mode in range(len(vibrateatoms) * 3):
vib.write_mode(mode)
# Calculate free energy
vib_energies = vib.get_energies()
thermo = IdealGasThermo(vib_energies=vib_energies,
electronicenergy=energy,
atoms=atoms,
geometry='linear',
symmetrynumber=2,
spin=0)
# At 300K and 101325 Pa
# change for your operating conditions
freeenergy = thermo.get_gibbs_energy(temperature=300, pressure=101325)
f = open(name + '.energy', 'w')
f.write('Potential energy: ' + str(energy) + '\n' + 'Free energy: ' +
str(freeenergy) + '\n')
f.close
ens = BEEF_Ensemble(calc)
ens_e = ens.get_ensemble_energies()
ens.write('ensemble.bee')
pickle.dump(ens_e, open('ensemble.pkl', 'w'))
# number of steps
numsteps = 40
# for loop that changes the distance between the atoms, fixes it, and performs
# a structural optimization. results writen out as i*.traj files
for step, delta in enumerate(xrange(0,30,1)):
if atoms.get_distance(atom1, atom2) < threshold:
break
if step < numsteps:
atoms.set_distance(atom1, atom2, d, fix=0.5)
qn = QuasiNewton(atoms, trajectory='i'+str(delta)+'.traj')
qn.run(fmax=0.05)
e = atoms.get_potential_energy()
print d, e
print >> f, d, e
f.flush()
d -= 0.1
f.close()
# ensemble
ens = BEEF_Ensemble(calc)
ens.get_ensemble_energies()
ens.write('fbl.bee')
del sys, calc, ens
sigma=0.1,
psppath='/home/vossj/suncat/psp/gbrv1.5pbe', #pseudopotential path
convergence= {'energy':1e-5, #convergence parameters
'mixing':0.1,
'nmix':10,
'mix':4,
'maxsteps':500,
'diag':'david'
},
dipole={'status':True}, #dipole correction to account for periodicity in z
beefensemble = True,
printensemble =True,
outdir='calcdir') #output directory for Quantum Espresso files
# attach the espresso calculator to the surface
atoms.set_calculator(calc)
# optimize the structure until the maximum force is
# at most 0.05 eV/AA
# output will be written to "qn.traj" with optimization log
# written to "qn.log"
qn = QuasiNewton(atoms, trajectory='qn.traj', logfile='qn.log')
qn.run(fmax=0.05)
#relevant commands for saving the BEEF error ensemble
#useful if you choose to perform error analysis
ens = BEEF_Ensemble(calc)
ens_e = ens.get_ensemble_energies()
ens.write('ensemble.bee')
pickle.dump(ens_e,open('ensemble.pkl','w'))
import_str = 'from ase.optimize import ' + self.optimizer + ' as QN'
exec(import_str)
kwargs = dict(trajectory=self.name + '.traj',
logfile=self.name + '_qn.log',
restart=self.name + '_qn.pkl')
kwargs.update(self.optimizer_kwargs)
dyn = QN(self.atoms, **kwargs)
dyn.run(**self.task_parameters)
barrier()
opt.converged_text = str(self.atoms.get_potential_energy())
opt.make_converged_file()
################################################################################
# End class definitions. Search EOCD to skip to here #
################################################################################
opt = GeometryOptimization('.')
opt.calculator = calc
opt.get_atoms()
opt.prepare_atoms()
opt.prepare_calculator()
opt.prepare_directory()
opt.run()
# ensemble
ens = BEEF_Ensemble(calc)
ens.get_ensemble_energies()
ens.write('qn.bee')
del sys, calc, ens
# number of steps
numsteps = 40
# for loop that changes the distance between the atoms, fixes it, and performs
# a structural optimization. results writen out as i*.traj files
for step, delta in enumerate(xrange(0, 30, 1)):
if atoms.get_distance(atom1, atom2) < threshold:
break
if step < numsteps:
atoms.set_distance(atom1, atom2, d, fix=0.5)
qn = QuasiNewton(atoms, trajectory='i' + str(delta) + '.traj')
qn.run(fmax=0.05)
e = atoms.get_potential_energy()
print d, e
print >> f, d, e
f.flush()
d -= 0.1
f.close()
# ensemble
ens = BEEF_Ensemble(calc)
ens.get_ensemble_energies()
ens.write('fbl.bee')
del sys, calc, ens
