def gen_super(self, grain=None, rbt=None, sup_v=6, sup_bxv=2, rcut=2.0):
""" :method:`gen_super` Creates a :class:SubGrainBoundary super cell according to
conventions described in Rittner and Seidman (PRB 54 6999).
Args:
grain(:class:`ase.Atoms`): atoms object passed from gen_super_rbt.
rbt (list): rigid body translation as fractional translations of the supercell.
sup_v(int): Size of supercell along v.
sup_bxv(int): Size of supercell along boundary_plane_normal crossed with v.
rcut(float): Atom deletion criterion in angstrom.
"""
io = ImeallIO()
if rbt == None:
x = Atoms('{0}.xyz'.format(os.path.join(self.grain_dir, self.gbid)))
else:
x = Atoms(grain)
struct_dir = os.path.join(self.grain_dir, 'structs')
self.name = '{0}_v{1}bxv{2}_tv{3}bxv{4}_d{5}z'.format(self.gbid,
str(sup_v), str(sup_bxv), '0.0', '0.0', str(rcut))
#TODO fix this so it is more transparent.
#if rcut = 0 then only a super cell is generated with no deletion of atoms.
if rcut > 0.0:
x.set_cutoff(2.4)
x.calc_connect()
x.calc_dists()
rem = []
u = np.zeros(3)
for i in range(x.n):
for n in range(x.n_neighbours(i)):
j = x.neighbour(i, n, distance=3.0, diff=u)
if x.distance_min_image(i,j) < rcut and j != i:
rem.append(sorted([j,i]))
rem = list(set([a[0] for a in rem]))
if len(rem) > 0:
x.remove_atoms(rem)
else:
print 'No duplicate atoms in list.'
else:
x = x*(sup_v, sup_bxv, 1)
x.set_scaled_positions(x.get_scaled_positions())
if rbt == None:
self.struct_file = self.name
self.subgrain_dir = io.make_dir(self.calc_dir, self.name)
try:
with open('{0}/subgb.json'.format(self.subgrain_dir), 'r') as f:
j_dict = json.load(f)
except IOError:
j_dict = {}
j_dict['name'] = self.name
j_dict['param_file'] = self.param_file
j_dict['rbt'] = [0.0, 0.0]
j_dict['rcut'] = rcut
with open('{0}/subgb.json'.format(self.subgrain_dir), 'w') as f:
json.dump(j_dict, f, indent=2)
else:
return sup_v, sup_bxv, x
def del_atoms(x=None):
rcut = 2.0
#x = Atoms('crack.xyz')
if x == None:
x = Atoms('1109337334_frac.xyz')
else:
pass
x.set_cutoff(3.0)
x.calc_connect()
x.calc_dists()
rem=[]
r = farray(0.0)
u = fzeros(3)
print len(x)
for i in frange(x.n):
for n in frange(x.n_neighbours(i)):
j = x.neighbour(i, n, distance=3.0, diff=u)
if x.distance_min_image(i, j) < rcut and j!=i:
rem.append(sorted([j,i]))
if i%10000==0: print i
rem = list(set([a[0] for a in rem]))
if len(rem) > 0:
print rem
x.remove_atoms(rem)
else:
print 'No duplicate atoms in list.'
x.write('crack_nodup.xyz')
return x
def delete_atoms(self, grain=None, rcut=2.0):
"""
Delete atoms below a certain distance threshold.
Args:
grain(:class:`quippy.Atoms`): Atoms object of the grain.
rcut(float): Atom deletion criterion.
Returns:
:class:`quippy.Atoms` object with atoms nearer than deletion criterion removed.
"""
io = ImeallIO()
if grain == None:
x = Atoms('{0}.xyz'.format(os.path.join(self.grain_dir,
self.gbid)))
else:
x = Atoms(grain)
x.set_cutoff(2.4)
x.calc_connect()
x.calc_dists()
rem = []
u = fzeros(3)
for i in frange(x.n):
for n in frange(x.n_neighbours(i)):
j = x.neighbour(i, n, distance=3.0, diff=u)
if x.distance_min_image(i, j) < rcut and j != i:
rem.append(sorted([j, i]))
rem = list(set([a[0] for a in rem]))
if len(rem) > 0:
x.remove_atoms(rem)
else:
print 'No duplicate atoms in list.'
if grain == None:
self.name = '{0}_d{1}'.format(self.gbid, str(rcut))
self.subgrain_dir = io.make_dir(self.calc_dir, self.name)
self.struct_file = gbid + '_' + 'n' + str(
len(rem)) + 'd' + str(rcut)
x.write('{0}.xyz'.format(
os.path.join(self.subgrain_dir, self.struct_file)))
return len(rem)
else:
return x
s_system = list(x)
s_system.extend(y)
name = ''.join(map(str, s_system)).replace('-', '')
print x, y, z
disloc = Dislocation(x=x, y=y, z=z, name=name)
disloc.gen_edge_dislocation()
POT_DIR = '/Users/lambert/pymodules/imeall/imeall/potentials'
eam_pot = os.path.join(POT_DIR, 'Fe_Mendelev.xml')
print 'Open Atoms'
at = Atoms('e{0}.xyz'.format(name))
at.set_cutoff(3.0)
at.calc_connect()
print 'Delete atoms'
at = gbr.delete_atoms(grain=at, rcut=1.5)
at.info['OrigHeight'] = at.positions[:, 1].max() - at.positions[:, 1].min()
r_scale = 1.00894848312
rem = []
for atom in at:
if atom.position[0] <= 0.00 and atom.position[1] <= 100.0:
rem.append(atom.index + 1)
print 'Removing ', len(rem), ' atoms.'
if len(rem) > 0:
at.remove_atoms(rem)
else:
print 'No atoms displaced from unitcell'
pot = Potential('IP EAM_ErcolAd do_rescale_r=T r_scale={0}'.format(r_scale),
def pp_nye_tensor(at, rr=15.0, dis_type='edge'):
# Post Processing routine to append nye tensor information
# to atoms object.
# Load reference slab and calculate connectivity
ref_slab = Atoms('./ref_slab.xyz')
at.set_cutoff(3.0)
at.calc_connect()
ref_slab.set_cutoff(3.0)
ref_slab.calc_connect()
core = np.zeros(3)
# To save time it is possible to only
# calculate the nye tensor for a 'core' region
# determined by cutting out a cluster:
if dis_type in ['edge','screw']:
try:
core = at.info['core']
except:
sys.exit('No Core Info')
print '\t Core Position: ', core
elif dis_type == 'crack':
core = at.info['CrackPos']
print '\t Crack Position: ', core
fixed_mask = (np.sqrt((at.positions[:,0]-core[0])**2 + (at.positions[:,1]-core[1])**2) < rr)
if dis_type in ['edge','screw']:
at.add_property('edgex', 0.0)
at.add_property('edgey', 0.0)
at.add_property('screw', 0.0)
#Going to append full nye tensor to the crack tip:
elif dis_type == 'crack':
at.add_property('nye', 0.0, n_cols=9, overwrite=True)
cl = at.select(mask=fixed_mask, orig_index=True)
print '\t Size of cluster: ', len(cl)
# Append screw and edge information
# Probably should just pass an array at this stage?
alpha = calc_nye_tensor(cl, ref_slab, 3, 3, cl.n)
cl.edgex = alpha[2,0,:]
cl.edgey = alpha[2,1,:]
cl.screw = alpha[2,2,:]
# Update quantum region according to the
# position of the dislocation core:
if dis_type in ['edge', 'screw']:
if dis_type == 'screw':
defect_pos = cl.screw
elif dis_type == 'edge':
defect_pos = cl.edgex
total_def = 0.
c = np.array([0.,0.,0.])
for i in range(len(cl)):
total_def = total_def + defect_pos[i]
c[0] = c[0] + cl.positions[i,0]*defect_pos[i]
c[1] = c[1] + cl.positions[i,1]*defect_pos[i]
c[0] = c[0]/total_def
c[1] = c[1]/total_def
c[2] = cl.lattice[2,2]/2.
core[:] = c.copy()
if dis_type in ['edge', 'screw']:
for index, screw, edgex, edgey in zip(cl.orig_index, cl.screw, cl.edgex, cl.edgey):
# Now thread atoms back in looks like select will have indices in the fortran convention.
at.screw[index-1] = screw
at.edgex[index-1] = edgex
at.edgey[index-1] = edgey
elif dis_type == 'crack':
for orig_index, index in zip(cl.orig_index, range(len(cl))):
at.nye[:, orig_index-1] = alpha[:,:,index].T.reshape(9)
return core
defect.info['OrigHeight'] = orig_height
strain_atoms = fix_edges_defect(defect)
xpos = defect.positions[:,0]
ypos = defect.positions[:,1]
seed = 0.0
tip = 0.0
if False:
strain = G_to_strain(initial_G, E, nu, orig_height)
print 'Applied strain: ', strain*100., '%'
defect.info['strain'] = strain
defect.info['G'] = initial_G
defect.positions[:,1] += thin_strip_displacement_y(xpos, ypos, strain, seed, tip)
defect.set_cutoff(3.0)
defect.calc_connect()
xlen = defect.positions[:,0].max() - defect.positions[:,0].min()
ylen = defect.positions[:,2].max() - defect.positions[:,2].min()
defect_object = {}
defect_object['x'] = x
defect_object['y'] = y
defect_object['z'] = z
defect_object['T'] = sim_T/units.kB
defect_json(**defect_object)
if run_dyn:
# Load atoms and set potential
# If tight-binding need to re-initialize potential
# with new defect atoms object.
def pp_nye_tensor(at, rr=15.0, dis_type='edge'):
# Post Processing routine to append nye tensor information
# to atoms object.
# Load reference slab and calculate connectivity
ref_slab = Atoms('./ref_slab.xyz')
at.set_cutoff(3.0)
at.calc_connect()
ref_slab.set_cutoff(3.0)
ref_slab.calc_connect()
core = np.zeros(3)
# To save time it is possible to only
# calculate the nye tensor for a 'core' region
# determined by cutting out a cluster:
if dis_type in ['edge', 'screw']:
try:
core = at.info['core']
except:
sys.exit('No Core Info')
print '\t Core Position: ', core
elif dis_type == 'crack':
core = at.info['CrackPos']
print '\t Crack Position: ', core
fixed_mask = (np.sqrt((at.positions[:, 0] - core[0])**2 +
(at.positions[:, 1] - core[1])**2) < rr)
if dis_type in ['edge', 'screw']:
at.add_property('edgex', 0.0)
at.add_property('edgey', 0.0)
at.add_property('screw', 0.0)
#Going to append full nye tensor to the crack tip:
elif dis_type == 'crack':
at.add_property('nye', 0.0, n_cols=9, overwrite=True)
cl = at.select(mask=fixed_mask, orig_index=True)
print '\t Size of cluster: ', len(cl)
# Append screw and edge information
# Probably should just pass an array at this stage?
alpha = calc_nye_tensor(cl, ref_slab, 3, 3, cl.n)
cl.edgex = alpha[2, 0, :]
cl.edgey = alpha[2, 1, :]
cl.screw = alpha[2, 2, :]
# Update quantum region according to the
# position of the dislocation core:
if dis_type in ['edge', 'screw']:
if dis_type == 'screw':
defect_pos = cl.screw
elif dis_type == 'edge':
defect_pos = cl.edgex
total_def = 0.
c = np.array([0., 0., 0.])
for i in range(len(cl)):
total_def = total_def + defect_pos[i]
c[0] = c[0] + cl.positions[i, 0] * defect_pos[i]
c[1] = c[1] + cl.positions[i, 1] * defect_pos[i]
c[0] = c[0] / total_def
c[1] = c[1] / total_def
c[2] = cl.lattice[2, 2] / 2.
core[:] = c.copy()
if dis_type in ['edge', 'screw']:
for index, screw, edgex, edgey in zip(cl.orig_index, cl.screw,
cl.edgex, cl.edgey):
# Now thread atoms back in looks like select will have indices in the fortran convention.
at.screw[index - 1] = screw
at.edgex[index - 1] = edgex
at.edgey[index - 1] = edgey
elif dis_type == 'crack':
for orig_index, index in zip(cl.orig_index, range(len(cl))):
at.nye[:, orig_index - 1] = alpha[:, :, index].T.reshape(9)
return core
strain_atoms = fix_edges_defect(defect)
xpos = defect.positions[:, 0]
ypos = defect.positions[:, 1]
seed = 0.0
tip = 0.0
if False:
strain = G_to_strain(initial_G, E, nu, orig_height)
print 'Applied strain: ', strain * 100., '%'
defect.info['strain'] = strain
defect.info['G'] = initial_G
defect.positions[:, 1] += thin_strip_displacement_y(
xpos, ypos, strain, seed, tip)
defect.set_cutoff(3.0)
defect.calc_connect()
xlen = defect.positions[:, 0].max() - defect.positions[:, 0].min()
ylen = defect.positions[:, 2].max() - defect.positions[:, 2].min()
defect_object = {}
defect_object['x'] = x
defect_object['y'] = y
defect_object['z'] = z
defect_object['T'] = sim_T / units.kB
defect_json(**defect_object)
if run_dyn:
# Load atoms and set potential
# If tight-binding need to re-initialize potential
# with new defect atoms object.
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)
ats.info['adsorbate_info']=None
with open('crack_info.pckl','r') as f:
crack_dict= pickle.load(f)
print 'G: {}, H_d: {}, sim_T {}'.format(crack_dict['initial_G']*(units.m**2/units.J),
crack_dict['H_d'], crack_dict['sim_T']/units.kB)
h_list = hydrify.hydrogenate_gb(ats, mode='CrackTip', d_H=crack_dict['H_d'][0], tetrahedral=True, crackpos_fix=ats.params['CrackPos'])
for h in h_list:
ats.add_atoms(h,1)
#ats.wrap()
ats.write('crackH.xyz')
ats = None
ats = Atoms('crackH.xyz')
ats.set_cutoff(2.4)
ats.calc_connect()
ats.calc_dists()
filter_mask = (ats.get_atomic_numbers()==1)
h_atoms = ats.select(filter_mask, orig_index=True)
rem=[]
u = np.zeros(3)
for i in h_atoms.orig_index:
print 'hindex', i
print 'nneighbs', ats.n_neighbours(i)
for n in range(ats.n_neighbours(i)):
j = ats.neighbour(i, n+1, distance=2.4, diff=u)
print 'neighb index', j
if ats.distance_min_image(i,j) < 1.1 and j!=i:
rem.append(i)
rem = list(set(rem))
if len(rem) > 0:
