def get_dynamics(atoms, mcfm_pot, T=300):
# ------ Set up logfiles
traj_interval = 10
thermoPrintstatus_log = open("log_thermoPrintstatus.log", "w")
outputTrajectory = open("log_trajectory.xyz", "w")
mcfmError_log = open("log_mcfmError.log", "w")
# ------ Let optimiser use the base potential and relax the per atom energies
mcfm_pot.qm_cluster.flagging_module.ema_parameter = 0.1
mcfm_pot.qm_cluster.flagging_module.qm_flag_potential_energies =\
np.ones((len(atoms), 2), dtype=float) * 1001
# ------ Minimize positions
opt = FIRE(atoms)
optimTrajectory = open("log_optimizationTrajectory.xyz", "w")
opt.attach(trajectory_writer, 1, atoms, optimTrajectory, writeResults=True)
opt.run(fmax=0.05, steps=1000)
# ------ Define ASE dyamics
sim_T = T * units.kB
MaxwellBoltzmannDistribution(atoms, 2 * sim_T)
timestep = 5e-1 * units.fs
friction = 1e-2
dynamics = Langevin(atoms, timestep, sim_T, friction, fixcm=False)
dynamics.attach(mcfm_thermo_printstatus, 100, 100, dynamics,
atoms, mcfm_pot, logfile=thermoPrintstatus_log)
dynamics.attach(trajectory_writer, traj_interval, atoms, outputTrajectory, writeResults=False)
dynamics.attach(mcfm_error_logger, 100, 100, dynamics, atoms, mcfm_pot, logfile=mcfmError_log)
return dynamics
def minimize_energy(atoms, nstep, pressure_interval=10):
bulkmodulus = 140e9 / 1e5 # Bulk modulus of typical metal (Cu), in bar.
dyn = FIRE(atoms)
unstress = Inhomogeneous_NPTBerendsen(atoms, 50*units.fs, 0,
taup=5000*units.fs,
compressibility=1/bulkmodulus)
dyn.attach(unstress.scale_positions_and_cell, interval=10)
dyn.run(steps=nstep)
def minimize_energy(atoms, nstep, pressure_interval=10):
bulkmodulus = 140e9 / 1e5 # Bulk modulus of typical metal (Cu), in bar.
dyn = FIRE(atoms)
unstress = Inhomogeneous_NPTBerendsen(atoms,
50 * units.fs,
0,
taup=5000 * units.fs,
compressibility=1 / bulkmodulus)
dyn.attach(unstress.scale_positions_and_cell, interval=10)
dyn.run(steps=nstep)
def get_dynamics(atoms, mcfm_pot, T=300):
# ------ Set up logfiles
traj_interval = 10
thermoPrintstatus_log = open("log_thermoPrintstatus.log", "w")
outputTrajectory = open("log_trajectory.xyz", "w")
mcfmError_log = open("log_mcfmError.log", "w")
# ------ Let optimiser use the base potential and relax the per atom energies
mcfm_pot.qm_cluster.flagging_module.ema_parameter = 0.1
mcfm_pot.qm_cluster.flagging_module.qm_flag_potential_energies =\
np.ones((len(atoms), 2), dtype=float) * 1001
# ------ Minimize positions
opt = FIRE(atoms)
optimTrajectory = open("log_optimizationTrajectory.xyz", "w")
opt.attach(trajectory_writer, 1, atoms, optimTrajectory, writeResults=True)
opt.run(fmax=0.05, steps=1000)
# ------ Define ASE dyamics
sim_T = T * units.kB
MaxwellBoltzmannDistribution(atoms, 2 * sim_T)
timestep = 5e-1 * units.fs
friction = 1e-2
dynamics = Langevin(atoms, timestep, sim_T, friction, fixcm=False)
dynamics.attach(mcfm_thermo_printstatus,
100,
100,
dynamics,
atoms,
mcfm_pot,
logfile=thermoPrintstatus_log)
dynamics.attach(trajectory_writer,
traj_interval,
atoms,
outputTrajectory,
writeResults=False)
dynamics.attach(mcfm_error_logger,
100,
100,
dynamics,
atoms,
mcfm_pot,
logfile=mcfmError_log)
return dynamics
def relax_structure(atoms, relax_fmax=0.05, traj_interval=None):
"""
Relax atoms object. If it contains a 'fixed_mask' array, then run constrained relaxation
"""
arel = atoms.copy()
try:
fix_mask = atoms.get_array("fixed_mask")
print("Running relaxation with %d constrained atoms" % fix_mask.sum())
const = FixAtoms(mask=fix_mask)
arel.set_constraint(const)
except:
print("No constraints specified, running relaxation")
arel.set_calculator(calc)
opt = FIRE(arel) # LBFGS(arel) #
if traj_interval is not None:
from quippy.io import AtomsWriter
out = AtomsWriter("traj-relax_structure.xyz")
trajectory_write = lambda: out.write(QAtoms(arel, charge=None))
opt.attach(trajectory_write, interval=traj_interval)
opt.run(fmax=relax_fmax)
return arel
images.append(initial.copy())
if restart:
for j in range(1,intermediate_images+1):
nebimage=io.read('neb%d.traj' % j)
nebimage.set_initial_magnetic_moments(mag)
images.append(nebimage)
images.append(final)
if not climb:
neb = NEB(images,k=k)
if climb:
neb = NEB(images,climb=True,k=k)
m.set_neb(neb)
#only for first step, linear interpolation here.
if not restart:
neb.interpolate()
if not climb:
qn = FIRE(neb, logfile='qn.log')
if climb:
qn = FIRE(neb, logfile='qn.log')
for j in range(1,intermediate_images+1):
traj = io.PickleTrajectory('neb%d.traj' % j, 'a', images[j])
qn.attach(traj)
qn.run(fmax=0.05)
image.constraints.append(constraint)
# Displace last image:
for i in xrange(1, 8, 1):
images[-1].positions[-i] += (d / 2, -h1 / 3, 0)
write('initial.traj', images[0])
# Relax height of Ag atom for initial and final states:
for image in [images[0], images[-1]]:
QuasiNewton(image).run(fmax=0.01)
if 0:
write('initial.pckl', image[0])
write('finial.pckl', image[-1])
# Interpolate positions between initial and final states:
neb.interpolate()
for image in images:
print image.positions[-1], image.get_potential_energy()
traj = PickleTrajectory('mep.traj', 'w')
dyn = FIRE(neb, dt=0.1)
#dyn = MDMin(neb, dt=0.1)
#dyn = QuasiNewton(neb)
dyn.attach(neb.writer(traj))
dyn.run(fmax=0.01, steps=150)
for image in images:
print image.positions[-1], image.get_potential_energy()
print 'Running WITH EAM as embedded cluster'
qm_pot_file = os.path.join(pot_dir, 'PotBH_fakemod.xml')
print qm_pot_file
mm_init_args = 'IP EAM_ErcolAd do_rescale_r=T r_scale=1.01' # Classical potential
qm_pot = Potential(mm_init_args, param_filename=qm_pot_file, cutoff_skin=cutoff_skin)
qmmm_pot = set_qmmm_pot(atoms, atoms.params['CrackPos'], mm_pot, qm_pot)
strain_atoms = fix_edges(atoms)
print 'Setup dynamics'
#If input_file is crack.xyz the cell has not been thermalized yet.
#Otherwise it will recover temperature from the previous run.
print 'Attaching trajectories to dynamics'
trajectory = AtomsWriter(traj_file)
#Only wriates trajectory if the system is in the LOTFDynamicas
#Interpolation
atoms.wrap()
atoms.set_cutoff(3.0)
atoms.calc_connect()
print 'Running Crack Simulation'
RELAXATION = False
if RELAXATION:
dynamics = FIRE(atoms)
dynamics.attach(pass_trajectory_context(trajectory, dynamics), traj_interval, dynamics)
dynamics.run(fmax=0.1)
else:
dynamics = LOTFDynamics(atoms, timestep, extrapolate_steps)
dynamics.attach(pass_trajectory_context(trajectory, dynamics), traj_interval, dynamics)
nsteps = 2000
dynamics.run(nsteps)
image.constraints.append(constraint)
# Displace last image:
for i in xrange(1,8,1):
images[-1].positions[-i] += (d/2, -h1/3, 0)
write('initial.traj', images[0])
# Relax height of Ag atom for initial and final states:
for image in [images[0], images[-1]]:
QuasiNewton(image).run(fmax=0.01)
if 0:
write('initial.pckl', image[0])
write('finial.pckl', image[-1])
# Interpolate positions between initial and final states:
neb.interpolate()
for image in images:
print image.positions[-1], image.get_potential_energy()
traj = PickleTrajectory('mep.traj', 'w')
dyn = FIRE(neb, dt=0.1)
#dyn = MDMin(neb, dt=0.1)
#dyn = QuasiNewton(neb)
dyn.attach(neb.writer(traj))
dyn.run(fmax=0.01,steps=150)
for image in images:
print image.positions[-1], image.get_potential_energy()
number_of_si = 0
initial_magmom = 0
for atom in bulk_mat:
if atom.symbol == 'Fe':
initial_magmom += 2.2
else:
number_of_si += 1.0
si_concentration = number_of_si / number_of_atoms
saver = Gpw_save(calc, system_name + '.gpw')
#Check if there is an existing .traj, if so append
if os.path.isfile('./' + system_name + '.traj'):
traj = Trajectory(system_name + '.traj', 'a', bulk_mat)
else:
traj = Trajectory(system_name + '.traj', 'w', bulk_mat)
ucf = UnitCellFilter(bulk_mat)
relaxer = FIRE(ucf, logfile=system_name + '.txt')
relaxer.attach(traj)
relaxer.attach(saver)
relaxer.run(fmax=0.025)
bulk_mat.get_potential_energy()
#Save the final state of the calculations
if density_number == 5.4:
calc.write(system_name + '_final.gpw')
save_atoms(bulk_mat, e_cut, nbands, density_number, smear,
initial_magmom, si_concentration, system_id, 0, final_db)
qm_pot,
buffer_width=buff,
pbc_type=[False, False, False])
def pass_trajectory_context(trajectory, dynamics):
def traj_writer(dynamics):
trajectory.write(dynamics.atoms)
return traj_writer
#Relax atoms around the defect.
trajectory = AtomsWriter('gb_traj_ini.xyz')
opt = FIRE(gb_cell)
opt.attach(pass_trajectory_context(trajectory, opt), 1, opt)
gb_cell.set_calculator(qmmm_pot)
opt.run(fmax=args.force_tolerance)
gb_cell.write('dft_edip_H_relaxed.xyz')
#One shot calculation of forces with defect removed.
gb_cell = AtomsReader('dft_edip_H_relaxed.xyz')[-1]
#Remove defect
defect = find_h_atom(gb_cell)
gb_cell.remove_atoms([defect.index + 1])
x, y, z = gb_cell.positions.T
radius1 = np.sqrt((x - h_pos[0])**2 + (y - h_pos[1])**2 + (z - h_pos[2])**2)
qm_region_mask = (radius1 < qm_radius)
qm_buffer_mask = (radius1 < qm_radius + buff)
