def make_super_cell_pymatgen (jdata) :
make_unit_cell(jdata)
out_dir = jdata['out_dir']
path_uc = os.path.join(out_dir, global_dirname_02)
from_path = path_uc
from_file = os.path.join(from_path, 'POSCAR.unit')
ss = Structure.from_file(from_file)
all_millers = jdata['millers']
path_sc = os.path.join(out_dir, global_dirname_02)
z_min = jdata['z_min']
super_cell = jdata['super_cell']
cwd = os.getcwd()
path_work = (path_sc)
path_work = os.path.abspath(path_work)
pcpy_cmd = os.path.join(cwd, 'tools')
pcpy_cmd = os.path.join(pcpy_cmd, 'poscar_copy.py')
os.chdir(path_work)
for miller in all_millers:
miller_str=""
for ii in miller :
miller_str += str(ii)
path_cur_surf = create_path('surf-'+miller_str)
os.chdir(path_cur_surf)
slabgen = SlabGenerator(ss, miller, z_min, 1e-3)
all_slabs = slabgen.get_slabs()
print("Miller %s: The slab has %s termination, use the first one" %(str(miller), len(all_slabs)))
all_slabs[0].to('POSCAR', 'POSCAR')
if super_cell[0] > 1 or super_cell[1] > 1 :
sp.check_call(pcpy_cmd + ' -n %d %d %d POSCAR POSCAR ' % (super_cell[0], super_cell[1], 1),
shell = True)
os.chdir(path_work)
os.chdir(cwd)
def make_super_cell_pymatgen(jdata):
make_unit_cell(jdata)
out_dir = jdata['out_dir']
path_uc = os.path.join(out_dir, global_dirname_02)
from_path = path_uc
from_file = os.path.join(from_path, 'POSCAR.unit')
ss = Structure.from_file(from_file)
# ase only support X type element
for i in range(len(ss)):
ss[i] = 'X'
ss = AseAtomsAdaptor.get_atoms(ss)
all_millers = jdata['millers']
path_sc = os.path.join(out_dir, global_dirname_02)
#z_min = jdata['z_min']
layer_numb = jdata['layer_numb']
super_cell = jdata['super_cell']
cwd = os.getcwd()
path_work = (path_sc)
path_work = os.path.abspath(path_work)
os.chdir(path_work)
for miller in all_millers:
miller_str = ""
for ii in miller:
miller_str += str(ii)
path_cur_surf = create_path('surf-' + miller_str)
os.chdir(path_cur_surf)
#slabgen = SlabGenerator(ss, miller, z_min, 1e-3)
slab = general_surface.surface(ss,
indices=miller,
vacuum=1e-3,
layers=layer_numb)
#all_slabs = slabgen.get_slabs()
dlog.info(os.getcwd())
#dlog.info("Miller %s: The slab has %s termination, use the first one" %(str(miller), len(all_slabs)))
#all_slabs[0].to('POSCAR', 'POSCAR')
slab.write('POSCAR', vasp5=True)
if super_cell[0] > 1 or super_cell[1] > 1:
st = Structure.from_file('POSCAR')
st.make_supercell([super_cell[0], super_cell[1], 1])
st.to('POSCAR', 'POSCAR')
os.chdir(path_work)
os.chdir(cwd)
def make_surface(file, facet=(1, 1, 1), verbose=True):
# read in structure
st = Structure.from_file(file)
# generate slabs with the given facet
slabgen = SlabGenerator(st, facet, 6, 16, center_slab=True)
all_slabs = slabgen.get_slabs(symmetrize=True)
if verbose:
print("The slab has %s termination." % (len(all_slabs)))
# save surfaces
for i, slab in enumerate(all_slabs):
slab.to('POSCAR', 'POSCAR_SURF_' + str(i).zfill(2))
def make_super_cell_pymatgen(jdata):
make_unit_cell(jdata)
out_dir = jdata['out_dir']
path_uc = os.path.join(out_dir, global_dirname_02)
from_path = path_uc
from_file = os.path.join(from_path, 'POSCAR.unit')
ss = Structure.from_file(from_file)
all_millers = jdata['millers']
path_sc = os.path.join(out_dir, global_dirname_02)
z_min = jdata['z_min']
super_cell = jdata['super_cell']
cwd = os.getcwd()
path_work = (path_sc)
path_work = os.path.abspath(path_work)
os.chdir(path_work)
for miller in all_millers:
miller_str = ""
for ii in miller:
miller_str += str(ii)
path_cur_surf = create_path('surf-' + miller_str)
os.chdir(path_cur_surf)
slabgen = SlabGenerator(ss, miller, z_min, 1e-3)
all_slabs = slabgen.get_slabs()
dlog.info(os.getcwd())
dlog.info("Miller %s: The slab has %s termination, use the first one" %
(str(miller), len(all_slabs)))
all_slabs[0].to('POSCAR', 'POSCAR')
if super_cell[0] > 1 or super_cell[1] > 1:
st = Structure.from_file('POSCAR')
st.make_supercell([super_cell[0], super_cell[1], 1])
st.to('POSCAR', 'POSCAR')
os.chdir(path_work)
os.chdir(cwd)
def make_vasp(jdata, conf_dir, max_miller=2, relax_box=False, static=False):
fp_params = jdata['vasp_params']
ecut = fp_params['ecut']
ediff = fp_params['ediff']
npar = fp_params['npar']
kpar = fp_params['kpar']
kspacing = fp_params['kspacing']
kgamma = fp_params['kgamma']
min_slab_size = jdata['min_slab_size']
min_vacuum_size = jdata['min_vacuum_size']
pert_xz = jdata['pert_xz']
# get conf poscar
# conf_path = os.path.abspath(conf_dir)
# conf_poscar = os.path.join(conf_path, 'POSCAR')
equi_path = re.sub('confs', global_equi_name, conf_dir)
equi_path = os.path.join(equi_path, 'vasp-k%.2f' % kspacing)
equi_path = os.path.abspath(equi_path)
equi_contcar = os.path.join(equi_path, 'CONTCAR')
assert os.path.exists(
equi_contcar), "Please compute the equilibrium state using vasp first"
task_path = re.sub('confs', global_task_name, conf_dir)
task_path = os.path.abspath(task_path)
if static:
task_path = os.path.join(task_path, 'vasp-static-k%.2f' % kspacing)
else:
task_path = os.path.join(task_path, 'vasp-k%.2f' % kspacing)
os.makedirs(task_path, exist_ok=True)
cwd = os.getcwd()
os.chdir(task_path)
if os.path.isfile('POSCAR'):
os.remove('POSCAR')
os.symlink(os.path.relpath(equi_contcar), 'POSCAR')
os.chdir(cwd)
task_poscar = os.path.join(task_path, 'POSCAR')
ptypes = vasp.get_poscar_types(task_poscar)
# gen strcture
ss = Structure.from_file(task_poscar)
# gen slabs
all_slabs = generate_all_slabs(ss, max_miller, min_slab_size,
min_vacuum_size)
# gen incar
if static:
fc = vasp.make_vasp_static_incar(ecut,
ediff,
npar=npar,
kpar=kpar,
kspacing=kspacing,
kgamma=kgamma)
else:
fc = vasp.make_vasp_relax_incar(ecut,
ediff,
True,
relax_box,
False,
npar=npar,
kpar=kpar,
kspacing=kspacing,
kgamma=kgamma)
with open(os.path.join(task_path, 'INCAR'), 'w') as fp:
fp.write(fc)
# gen potcar
with open(task_poscar, 'r') as fp:
lines = fp.read().split('\n')
ele_list = lines[5].split()
potcar_map = jdata['potcar_map']
potcar_list = []
for ii in ele_list:
assert os.path.exists(os.path.abspath(
potcar_map[ii])), "No POTCAR in the potcar_map of %s" % (ii)
potcar_list.append(os.path.abspath(potcar_map[ii]))
with open(os.path.join(task_path, 'POTCAR'), 'w') as outfile:
for fname in potcar_list:
with open(fname) as infile:
outfile.write(infile.read())
# gen tasks
cwd = os.getcwd()
for ii in range(len(all_slabs)):
slab = all_slabs[ii]
miller_str = "m%d.%d.%dm" % (
slab.miller_index[0], slab.miller_index[1], slab.miller_index[2])
# make dir
struct_path = os.path.join(task_path,
'struct-%03d-%s' % (ii, miller_str))
os.makedirs(struct_path, exist_ok=True)
os.chdir(struct_path)
for jj in ['POSCAR', 'POTCAR', 'INCAR']:
if os.path.isfile(jj):
os.remove(jj)
print("# %03d generate " % ii, struct_path,
" \t %d atoms" % len(slab.sites))
# make conf
slab.to('POSCAR', 'POSCAR.tmp')
vasp.regulate_poscar('POSCAR.tmp', 'POSCAR')
vasp.sort_poscar('POSCAR', 'POSCAR', ptypes)
vasp.perturb_xz('POSCAR', 'POSCAR', pert_xz)
# record miller
np.savetxt('miller.out', slab.miller_index, fmt='%d')
# link incar, potcar, kpoints
os.symlink(os.path.relpath(os.path.join(task_path, 'INCAR')), 'INCAR')
os.symlink(os.path.relpath(os.path.join(task_path, 'POTCAR')),
'POTCAR')
cwd = os.getcwd()
def make_lammps(jdata,
conf_dir,
max_miller=2,
static=False,
relax_box=False,
task_type='wrong-task'):
kspacing = jdata['vasp_params']['kspacing']
fp_params = jdata['lammps_params']
model_dir = fp_params['model_dir']
type_map = fp_params['type_map']
model_dir = os.path.abspath(model_dir)
model_name = fp_params['model_name']
if not model_name and task_type == 'deepmd':
models = glob.glob(os.path.join(model_dir, '*pb'))
model_name = [os.path.basename(ii) for ii in models]
assert len(model_name) > 0, "No deepmd model in the model_dir"
else:
models = [os.path.join(model_dir, ii) for ii in model_name]
model_param = {
'model_name': fp_params['model_name'],
'param_type': fp_params['model_param_type']
}
ntypes = len(type_map)
min_slab_size = jdata['min_slab_size']
min_vacuum_size = jdata['min_vacuum_size']
# get equi poscar
# conf_path = os.path.abspath(conf_dir)
# conf_poscar = os.path.join(conf_path, 'POSCAR')
equi_path = re.sub('confs', global_equi_name, conf_dir)
equi_path = os.path.join(equi_path, 'vasp-k%.2f' % kspacing)
equi_path = os.path.abspath(equi_path)
equi_contcar = os.path.join(equi_path, 'CONTCAR')
assert os.path.exists(
equi_contcar), "Please compute the equilibrium state using vasp first"
task_path = re.sub('confs', global_task_name, conf_dir)
task_path = os.path.abspath(task_path)
if static:
task_path = os.path.join(task_path, task_type + '-static')
else:
task_path = os.path.join(task_path, task_type)
os.makedirs(task_path, exist_ok=True)
cwd = os.getcwd()
os.chdir(task_path)
if os.path.isfile('POSCAR'):
os.remove('POSCAR')
os.symlink(os.path.relpath(equi_contcar), 'POSCAR')
os.chdir(cwd)
task_poscar = os.path.join(task_path, 'POSCAR')
# gen strcture
ss = Structure.from_file(task_poscar)
# gen slabs
all_slabs = generate_all_slabs(ss, max_miller, min_slab_size,
min_vacuum_size)
# make lammps.in
if task_type == 'deepmd':
if static:
fc = lammps.make_lammps_eval('conf.lmp', ntypes,
lammps.inter_deepmd, model_name)
else:
fc = lammps.make_lammps_equi('conf.lmp',
ntypes,
lammps.inter_deepmd,
model_name,
change_box=relax_box)
elif task_type == 'meam':
if static:
fc = lammps.make_lammps_eval('conf.lmp', ntypes, lammps.inter_meam,
model_param)
else:
fc = lammps.make_lammps_equi('conf.lmp',
ntypes,
lammps.inter_meam,
model_param,
change_box=relax_box)
f_lammps_in = os.path.join(task_path, 'lammps.in')
with open(f_lammps_in, 'w') as fp:
fp.write(fc)
cwd = os.getcwd()
if task_type == 'deepmd':
os.chdir(task_path)
for ii in model_name:
if os.path.exists(ii):
os.remove(ii)
for (ii, jj) in zip(models, model_name):
os.symlink(os.path.relpath(ii), jj)
share_models = glob.glob(os.path.join(task_path, '*pb'))
else:
share_models = models
for ii in range(len(all_slabs)):
slab = all_slabs[ii]
miller_str = "m%d.%d.%dm" % (
slab.miller_index[0], slab.miller_index[1], slab.miller_index[2])
# make dir
struct_path = os.path.join(task_path,
'struct-%03d-%s' % (ii, miller_str))
os.makedirs(struct_path, exist_ok=True)
os.chdir(struct_path)
for jj in ['conf.lmp', 'lammps.in'] + model_name:
if os.path.isfile(jj):
os.remove(jj)
print("# %03d generate " % ii, struct_path,
" \t %d atoms" % len(slab.sites))
# make conf
slab.to('POSCAR', 'POSCAR')
vasp.regulate_poscar('POSCAR', 'POSCAR')
lammps.cvt_lammps_conf('POSCAR', 'conf.lmp')
ptypes = vasp.get_poscar_types('POSCAR')
lammps.apply_type_map('conf.lmp', type_map, ptypes)
# record miller
np.savetxt('miller.out', slab.miller_index, fmt='%d')
# link lammps.in
os.symlink(os.path.relpath(f_lammps_in), 'lammps.in')
# link models
for (ii, jj) in zip(share_models, model_name):
os.symlink(os.path.relpath(ii), jj)
cwd = os.getcwd()
def make_deepmd_lammps(jdata, conf_dir, max_miller = 2, static = False, relax_box = False, task_name = 'wrong-task') :
fp_params = jdata['vasp_params']
kspacing = fp_params['kspacing']
deepmd_model_dir = jdata['deepmd_model_dir']
deepmd_type_map = jdata['deepmd_type_map']
ntypes = len(deepmd_type_map)
deepmd_model_dir = os.path.abspath(deepmd_model_dir)
deepmd_models = glob.glob(os.path.join(deepmd_model_dir, '*pb'))
deepmd_models_name = [os.path.basename(ii) for ii in deepmd_models]
min_slab_size = jdata['min_slab_size']
min_vacuum_size = jdata['min_vacuum_size']
# get equi poscar
# conf_path = os.path.abspath(conf_dir)
# conf_poscar = os.path.join(conf_path, 'POSCAR')
equi_path = re.sub('confs', global_equi_name, conf_dir)
equi_path = os.path.join(equi_path, 'vasp-k%.2f' % kspacing)
equi_path = os.path.abspath(equi_path)
equi_contcar = os.path.join(equi_path, 'CONTCAR')
task_path = re.sub('confs', global_task_name, conf_dir)
task_path = os.path.abspath(task_path)
task_path = os.path.join(task_path, task_name)
os.makedirs(task_path, exist_ok=True)
cwd = os.getcwd()
os.chdir(task_path)
if os.path.isfile('POSCAR') :
os.remove('POSCAR')
os.symlink(os.path.relpath(equi_contcar), 'POSCAR')
os.chdir(cwd)
task_poscar = os.path.join(task_path, 'POSCAR')
# gen strcture
ss = Structure.from_file(task_poscar)
# gen slabs
all_slabs = generate_all_slabs(ss, max_miller, min_slab_size, min_vacuum_size)
# make lammps.in
if static :
fc = lammps.make_lammps_eval('conf.lmp',
ntypes,
lammps.inter_deepmd,
deepmd_models_name)
else :
fc = lammps.make_lammps_equi('conf.lmp',
ntypes,
lammps.inter_deepmd,
deepmd_models_name,
change_box = relax_box)
f_lammps_in = os.path.join(task_path, 'lammps.in')
with open(f_lammps_in, 'w') as fp :
fp.write(fc)
cwd = os.getcwd()
for ii in range(len(all_slabs)) :
slab = all_slabs[ii]
miller_str = "m%d.%d.%dm" % (slab.miller_index[0], slab.miller_index[1], slab.miller_index[2])
# make dir
struct_path = os.path.join(task_path, 'struct-%03d-%s' % (ii, miller_str))
os.makedirs(struct_path, exist_ok=True)
os.chdir(struct_path)
for jj in ['conf.lmp', 'lammps.in'] + deepmd_models_name :
if os.path.isfile(jj):
os.remove(jj)
print("# %03d generate " % ii, struct_path, " \t %d atoms" % len(slab.sites))
# make conf
slab.to('POSCAR', 'POSCAR')
vasp.regulate_poscar('POSCAR', 'POSCAR')
lammps.cvt_lammps_conf('POSCAR', 'conf.lmp')
ptypes = vasp.get_poscar_types('POSCAR')
lammps.apply_type_map('conf.lmp', deepmd_type_map, ptypes)
# record miller
np.savetxt('miller.out', slab.miller_index, fmt='%d')
# link lammps.in
os.symlink(os.path.relpath(f_lammps_in), 'lammps.in')
# link models
for (ii,jj) in zip(deepmd_models, deepmd_models_name) :
os.symlink(os.path.relpath(ii), jj)
cwd = os.getcwd()
# Import the neccesary tools to generate surfaces
from pymatgen.core.surface import SlabGenerator, generate_all_slabs, Structure, Lattice
# Import the neccesary tools for making a Wulff shape
from pymatgen.analysis.wulff import WulffShape
import os
lattice = Lattice.cubic(3.508)
Ni = Structure(lattice, ["Ni", "Ni", "Ni", "Ni"],
[[0, 0, 0], [0, 0.5, 0], [0.5, 0, 0], [0, 0, 0.5]])
slabgen = SlabGenerator(Ni, (1, 1, 1), 10, 10)
lattice = Lattice.cubic(5.46873)
Si = Structure(lattice, ["Si", "Si", "Si", "Si", "Si", "Si", "Si", "Si"],
[[0.00000, 0.00000, 0.50000], [0.75000, 0.75000, 0.75000],
[0.00000, 0.50000, 0.00000], [0.75000, 0.25000, 0.25000],
[0.50000, 0.00000, 0.00000], [0.25000, 0.75000, 0.25000],
[0.50000, 0.50000, 0.50000], [0.25000, 0.25000, 0.75000]])
slabgen = SlabGenerator(Si, (1, 1, 1), 10, 10)
print("Notice now there are actually now %s terminations that can be \
generated in the (111) direction for diamond Si" % (len(slabgen.get_slabs())))
}
Adsorbant_1 = {
'M': 24,
'X': 48,
'Y': 2,
'Area': 77.14,
'Energy': -609.24,
'Label': '1 Species'
}
data = [Adsorbant_1]
Surface_111_1 = wulff.calculate_surface_energy(stoich, data, SE, adsorbant,
thermochem, 298, 0)
#Declare the lattic paramter
lattice = Lattice.cubic(5.411)
ceo = Structure(lattice, ["Ce", "O"], [[0, 0, 0], [0.25, 0.25, 0.25]])
surface_energies_ceo = {
(1, 1, 1): np.amin(Surface_111_1),
(1, 1, 0): np.amin(Surface_110_1),
(1, 0, 0): np.amin(Surface_100_1)
}
miller_list = surface_energies_ceo.keys()
e_surf_list = surface_energies_ceo.values()
# We can now construct a Wulff shape with an accuracy up to a max Miller index of 3
wulffshape = WulffShape(ceo.lattice, miller_list, e_surf_list)
# Let's get some useful information from our wulffshape object
print("shape factor: %.3f, anisotropy: \
%.3f, weighted surface energy: %.3f J/m^2" %
# Input parameters, following behavior of SlabGenerator in pymatgen
filname = sys.argv[1]
outname = filname.split('.')
outname = outname[0].split('/')
outname = outname[-1:]
print("Reading atomic coordinates from: ", filname)
# remaining input parameters
miller = sys.argv[2].split(',')
slabsize = int(sys.argv[3])
vacsize = int(sys.argv[4])
# Read structure from PWscf file, xsf format
structure = Structure.from_file(filname)
# make slab
if len(miller) == 3:
miller = tuple(map(int, miller)) # no list in py2
slabgen = SlabGenerator(structure,
miller,
slabsize,
vacsize,
center_slab=True)
slabs = slabgen.get_slabs()
print("Generated %d slabs in %s direction" % (
len(slabs),
str(miller),
))