def run_single_point():
logger = setup_logger(output_filename="dielectrics.log")
structure = VaspReader(input_location='./POSCAR').read_POSCAR()
vasp = Vasp(**single_point_pbe)
vasp.set_crystal(structure)
vasp.execute()
if vasp.completed:
logger.info("PBE self-consistent run completed properly.")
else:
raise Exception(
"PBE self-consistent run failed to converge, will stop proceeding")
def get_total_energies(db, dir=None):
all_zips = glob.glob(dir + "/*.zip")
for zip in all_zips:
kvp = {}
data = {}
kvp['uid'] = zip.replace(".zip", '').replace('/', '_')
archive = zipfile.ZipFile(zip)
atoms = None
total_energy = None
has_contcar = False
for name in archive.namelist():
if 'OSZICAR' in name:
oszicar = archive.read(name)
oszicar_reader = VaspReader(
file_content=str(oszicar).split('\\n'))
total_energy = oszicar_reader.get_free_energies_from_oszicar(
)[-1]
kvp['total_energy'] = total_energy
if 'CONTCAR' in name:
with open('CONTCAR_temp', 'w') as f:
for l in str(archive.read(name)).split('\\n'):
f.write(l + '\n')
has_contcar = True
if not has_contcar:
for name in archive.namelist():
if 'POSCAR' in name:
with open('CONTCAR_temp', 'w') as f:
for l in str(archive.read(name)).split('\\n'):
f.write(l + '\n')
crystal = ase.io.read('CONTCAR_temp', format='vasp')
f.close()
os.remove('CONTCAR_temp')
if (crystal is not None) and (total_energy is not None):
print(kvp['uid'], total_energy)
populate_db(db, crystal, kvp, data)
folders = glob.glob('*' + halo + '*')
_sigma_100K = []
_sigma_300K = []
_compositions = []
_sigma_ref_300K = []
for folder in ['../CsSnI_Pnma', '../CsPbI_Pnma']:
print(folder)
#if not os.path.isdir(folder): continue
os.chdir(folder)
# get the compositions
crystal = VaspReader(input_location="./phonon/POSCAR").read_POSCAR()
_d = crystal.all_atoms_count_dictionaries()
scorer = AnharmonicScore(md_frames='./vasprun_md.xml',
ref_frame='./phonon/POSCAR',
atoms=None,
unit_cell_frame='./phonon/POSCAR')
__sigmas, _ = scorer.structural_sigma(return_trajectory=True)
_sigma_ref_300K.append(__sigmas[2000:])
os.chdir(cwd)
for folder in folders:
if not os.path.isdir(folder): continue
os.chdir(folder)
# get the compositions
def __init__(self, ref_frame=None,
unit_cell_frame=None,
md_frames=None,
potim=1,
force_constants=None,
supercell=[1, 1, 1],
primitive_matrix=[[1, 0, 0], [0, 1, 0], [0, 0, 1]],
atoms=None,
include_third_order=False,
third_order_fc='./phono3py/fc3.hdf5',
include_fourth_order=False,
fourth_order_fc=None,
force_sets_filename='FORCE_SETS',
mode_resolved=False):
self.mode_resolved = mode_resolved
if isinstance(ref_frame, Crystal):
self.ref_frame = ref_frame
elif ('POSCAR' in ref_frame) or ('CONTCAR' in ref_frame):
print(ref_frame)
print("initialising reference frame from POSCAR ")
self.ref_frame = VaspReader(input_location=ref_frame).read_POSCAR()
self.ref_coords = np.array([[a.scaled_position.x, a.scaled_position.y, a.scaled_position.z] for a in
self.ref_frame.asymmetric_unit[0].atoms])
self.atom_masks = None
if atoms is not None:
self.atom_masks = [id for id, atom in enumerate(self.ref_frame.asymmetric_unit[0].atoms) if
atom.label in atoms]
if isinstance(md_frames,list):
self.md_frames = md_frames # require the vasprun.xml containing the MD data
elif isinstance(md_frames,str):
self.md_frames = [md_frames]
self.get_dft_md_forces()
self.get_all_md_atomic_displacements()
if isinstance(force_constants, str):
try:
self.phonon = phonopy.load(supercell_matrix=supercell, # WARNING - hard coded!
primitive_matrix=primitive_matrix,
unitcell_filename=unit_cell_frame,
force_constants_filename=force_constants)
print("Use supercell " + str(supercell))
print("Use primitive matrix " + str(primitive_matrix) + " done")
except:
self.phonon = phonopy.load(supercell_matrix=supercell, # WARNING - hard coded!
primitive_matrix='auto',
unitcell_filename=unit_cell_frame,
force_constants_filename=force_constants)
print("INPUT PHONOPY force constant shape ", np.shape(self.phonon.force_constants))
#TODO - if the input supercell is not [1,1,1], then it will need to be expanded into the correct supercell shape here!
new_shape = np.shape(self.phonon.force_constants)[0] * np.shape(self.phonon.force_constants)[2]
self.force_constant = np.zeros((new_shape, new_shape))
self.force_constant = self.phonon.force_constants.transpose(0, 2, 1, 3).reshape(new_shape, new_shape)
elif (force_constants is None):
"""
Loading directly from SPOSCAR (supercell structure) and FORCESET to avoid problem of the need for
reconstructing the force constants for supercells from primitive cells
"""
print("Here try to use FORCE_SETS")
# if we want to get the eigenvector on all atoms in the supercell, we need to specify the primitive matrix
# as the identity matrix, making the phonopy to treat the supercell as the primitive, rather than generate them
# automatically
if not self.mode_resolved:
self.phonon = phonopy.load(supercell_filename=ref_frame, log_level=1, force_sets_filename=force_sets_filename)
else:
self.phonon = phonopy.load(supercell_filename=ref_frame, log_level=1, force_sets_filename=force_sets_filename,primitive_matrix=[[1, 0, 0], [0, 1, 0], [0, 0, 1]])
self.phonon.produce_force_constants()
print("INPUT PHONOPY force constant shape ", np.shape(self.phonon.force_constants))
new_shape = np.shape(self.phonon.force_constants)[0] * np.shape(self.phonon.force_constants)[2]
self.force_constant = np.zeros((new_shape, new_shape))
self.force_constant = self.phonon.force_constants.transpose(0, 2, 1, 3).reshape(new_shape, new_shape)
elif isinstance(force_constants, np.ndarray):
new_shape = np.shape(force_constants)[0] * np.shape(force_constants)[2]
self.force_constant = np.zeros((new_shape, new_shape))
self.force_constant = force_constants.transpose(0, 2, 1, 3).reshape(new_shape, new_shape)
print("force constant reshape ", np.shape(self.force_constant))
print("Force constants ready")
self.time_series = [t * potim for t in range(len(self.all_displacements))]
self.force_constant_3 = None
self.include_third_oder = include_third_order
if self.include_third_oder:
if isinstance(third_order_fc, str):
if os.path.isfile(third_order_fc):
print("Found third order force constants")
import h5py
f = h5py.File(third_order_fc) # './phono3py/fc3.hdf5'
raw_force_constant_3 = np.array(f['fc3'])
elif isinstance(third_order_fc, np.ndarray):
raw_force_constant_3 = third_order_fc
s = np.shape(raw_force_constant_3)[0] * 3
self.force_constant_3 = raw_force_constant_3.transpose([0, 3, 1, 4, 2, 5]).reshape(s, s, s)
print("Reshaped 3rd order force constant is ", np.shape(self.force_constant_3))
self.force_constant_4 = None
self.include_fourth_order = include_fourth_order
if self.include_fourth_order:
if isinstance(fourth_order_fc, np.ndarray):
raw_force_constant_4 = fourth_order_fc
s = np.shape(raw_force_constant_4)[0] * 3
self.force_constant_4 = raw_force_constant_4.transpose([0, 4, 1, 5, 2, 6, 3, 7]).reshape(s, s, s, s)
if self.mode_resolved:
self.prepare_phonon_eigs()
'LWAVE': False,
'LCHARG': False,
'LREAL': 'Auto',
'NELM': 150,
'NSW': 0,
'NCORE': 48,
'use_gw': True,
'Gamma_centered': True,
'MP_points': [1, 1, 1],
'executable': 'vasp_gam'
}
pwd = os.getcwd()
# get the trajectory
all_frames = VaspReader(args.traj).read_XDATCAR()
if not args.batch:
output = 'gap_dynamics.dat'
else:
output = 'gap_dynamics_' + str(args.part) + '.dat'
# figure out if this is a continuing calculation
if not os.path.exists(pwd + '/' + output):
o = open(pwd + '/' + output, 'w+')
o.write('Frame\t VBM \t CBM \t E_f \t E_g\n')
o.close()
last = 0
else:
o = open(pwd + '/' + output, 'r')
for l in o.readlines():
def composition_eq_point_curve():
cwd_1 = os.getcwd()
labels = {
0: 'Cs(Pb$_{x}$Sn$_{1-x})$Cl$_3$',
1: 'Cs(Pb$_{x}$Sn$_{1-x})$Br$_3$',
2: 'Cs(Pb$_{x}$Sn$_{1-x})$I$_3$'
}
colors = {
0: '#000000', # hex code for black
1: '#dd0000', # hex code for electric red
2: '#ffce00' # hex code for tangerine yellow
}
for counter, X in enumerate(['Cl', 'Br', 'I']):
data_dict = {}
for dir in [
r for r in glob.glob(os.getcwd() + "/*" + str(X) + "*")
if '.pdf' not in r
]:
os.chdir(dir)
print(dir)
cwd_2 = os.getcwd()
data = []
directories = glob.glob(os.getcwd() + "/disp_111_*_0_05")
if 'CsSnBr3_cubic' in dir:
directories = glob.glob(os.getcwd() + "/disp_Sn_111_*_0_05")
for sub_dir in directories:
os.chdir(sub_dir)
print(sub_dir)
energy = VaspReader(input_location='./OSZICAR'
).get_free_energies_from_oszicar()[-1]
crystal = VaspReader(input_location='./POSCAR').read_POSCAR()
energy = energy / crystal.total_num_atoms()
info = pickle.load(open('info.p', 'rb'))
info['energy'] = energy
data.append(info)
os.chdir(cwd_2)
os.chdir(cwd_1)
displacements = list(sorted([d['displacement'] for d in data]))
energy = []
for _dis in displacements:
for d in data:
if d['displacement'] == _dis:
energy.append(d['energy'])
energy = [e - energy[0] for e in energy]
x = np.array(displacements)
y = np.array(energy)
from scipy.optimize import curve_fit
popt, pcov = curve_fit(pes, x, y)
x = [0 + (0.6 / 100) * i for i in range(100)]
y = pes(np.array(x), *popt)
a = popt[0]
b = popt[1]
if 2 * a / (4 * b) > 0:
min_x = 0
else:
min_x = math.sqrt(-2 * a / (4 * b))
concentration = data[0]['concentration']
data_dict[1.0 - concentration] = min_x
os.chdir(cwd_1)
x = list(sorted(data_dict.keys()))
plt.plot(x, [data_dict[_x] for _x in x],
'o-',
c=colors[counter],
label=labels[counter],
ms=12,
lw=3)
plt.legend()
plt.xlabel('$x$ in Cs(Pb$_{x}$Sn$_{1-x}$)X$_{3}$')
plt.ylabel('Minima on PES ($x_{\min}$, \AA)')
plt.tight_layout()
plt.savefig('xeq_comp_summary.pdf')
def make_distorted_structure(poscar,
direction='111',
max_displacement=0.6,
number_of_points=15,
lattice_deformation=0,
atom_to_displace=['Sn', 'Pb']):
for counter, delta_d in enumerate([
0 + max_displacement / number_of_points * k
for k in range(number_of_points)
]):
crystal = VaspReader(input_location=poscar).read_POSCAR()
# expand or shrink the lattice parameters
crystal = deform_crystal_by_lattice_expansion_coefficients(
crystal, def_fraction=[lattice_deformation for _ in range(3)])
d = [int(_d) for _d in list(direction)]
displacement_vector = cVector3D(d[0], d[1], d[2]).normalise()
# just displace the first atom that is the element that we want to displace
_displace_vec = displacement_vector.vec_scale(delta_d)
# _next = True
for mol in crystal.asymmetric_unit:
for atom in mol.atoms:
if (atom.label in atom_to_displace): # and (_next is True):
print(atom.label)
atom.position = atom.position + _displace_vec
# _next = False
try:
n = crystal.all_atoms_count_dictionaries()['Sn']
except KeyError:
n = 0
folder_name = 'disp' + '_' + str(direction) + '_' + str(
n) + '_str_' + str(counter) + '_a_def_' + str(
lattice_deformation).replace('.', '_')
cwd = os.getcwd()
try:
os.makedirs(cwd + '/' + folder_name)
except:
pass
os.chdir(cwd + '/' + folder_name)
_dict = crystal.all_atoms_count_dictionaries()
if 'Sn' not in _dict.keys():
_dict['Sn'] = 0
if 'Pb' not in _dict.keys():
_dict['Pb'] = 0
system_dict = {
'atom_to_displace': atom_to_displace,
'concentration': _dict['Sn'] / (_dict['Sn'] + _dict['Pb']),
'displacement': delta_d,
'id': counter,
'direction': direction,
'deformation': lattice_deformation
}
pickle.dump(system_dict, open('info.p', 'wb'))
VaspWriter().write_structure(crystal, 'POSCAR')
os.chdir(cwd)
def get_this_pes(directory=os.getcwd()):
cmap = matplotlib.cm.get_cmap('YlOrRd')
cwd = os.getcwd()
data = []
for dir in glob.glob(directory + "/disp_*"):
os.chdir(dir)
try:
energy = VaspReader(input_location='./OSZICAR'
).get_free_energies_from_oszicar()[-1]
crystal = VaspReader(input_location='./POSCAR').read_POSCAR()
energy = energy / crystal.total_num_atoms()
info = pickle.load(open('info.p', 'rb'))
info['energy'] = energy
data.append(info)
except:
pass
os.chdir(cwd)
deformations = set([d['deformation'] for d in data])
deformations = list(sorted(deformations))
max_def = max(deformations) + 0.0001
max_displacement = 0
min_x = []
min_y = []
for id, _def in enumerate(deformations):
displacement = [
d['displacement'] for d in data if d['deformation'] == _def
]
displacement = list(sorted(displacement))
energy = []
for dis in displacement:
for d in data:
if (d['deformation'] == _def) and (d['displacement'] == dis):
energy.append(d['energy'])
energy = [e - energy[0] for e in energy]
x = np.array(displacement)
y = np.array(energy)
from scipy.optimize import curve_fit
popt, pcov = curve_fit(pes, x, y)
x = [0 + (0.6 / 100) * i for i in range(100)]
y = pes(np.array(x), *popt)
a = popt[0]
b = popt[1]
if 2 * a / (4 * b) > 0:
min_x.append(0)
min_y.append(0)
else:
min_x.append(math.sqrt(-2 * a / (4 * b)))
min_y.append(pes(math.sqrt(-2 * a / (4 * b)), *popt))
if id % 2 == 0:
plt.plot(x,
y,
'-',
c=cmap((0.05 + _def) / (2 * max_def)),
label=str(_def * 100) + '\%',
lw=2)
else:
plt.plot(x, y, '-', c=cmap((0.05 + _def) / (2 * max_def)), lw=2)
max_displacement = max(x)
plt.ticklabel_format(style='sci', axis='y', scilimits=(0, 0))
plt.plot([0, max_displacement], [0, 0], 'k--')
plt.plot(min_x, min_y, 'o-', c='k', lw=3.5)
plt.legend()
plt.ylim([-0.01, 0.0150])
plt.xlim([0, max_displacement])
plt.xlabel('B-Cation Displacement $\Delta d$ (\AA)')
plt.ylabel('$E-E_{\Delta d=0}$ (eV/atom)')
plt.tight_layout()
plt.savefig('pes.pdf')
def pressure_eq_point_curve():
cwd = os.getcwd()
labels = {
0: 'CsPbBr$_3$',
1: 'Cs(Pb$_{0.5}$Sn$_{0.5})$Br$_3$',
2: 'CsSnBr$_3$'
}
colors = {
0: '#000000', # hex code for black
1: '#dd0000', # hex code for electric red
2: '#ffce00' # hex code for tangerine yellow
}
for counter, sys in enumerate([
'CsPbBr3_cubic', 'mixed_CsPbSnBr3_SC_1_1_1_CsPbSnBr3_5_str_17',
'CsSnBr3_cubic'
]):
os.chdir(sys)
this_dir = os.getcwd()
data = []
for dir in glob.glob("./disp_*"):
os.chdir(dir)
try:
energy = VaspReader(input_location='./OSZICAR'
).get_free_energies_from_oszicar()[-1]
crystal = VaspReader(input_location='./POSCAR').read_POSCAR()
energy = energy / crystal.total_num_atoms()
info = pickle.load(open('info.p', 'rb'))
info['energy'] = energy
data.append(info)
except:
pass
os.chdir(this_dir)
deformations = set([d['deformation'] for d in data])
deformations = list(sorted(deformations))
min_x = []
for id, _def in enumerate(deformations):
displacement = [
d['displacement'] for d in data if d['deformation'] == _def
]
displacement = list(sorted(displacement))
energy = []
for dis in displacement:
for d in data:
if (d['deformation'] == _def) and (d['displacement']
== dis):
energy.append(d['energy'])
energy = [e - energy[0] for e in energy]
x = np.array(displacement)
y = np.array(energy)
from scipy.optimize import curve_fit
popt, pcov = curve_fit(pes, x, y)
a = popt[0]
b = popt[1]
if 2 * a / (4 * b) > 0:
min_x.append(0)
else:
min_x.append(math.sqrt(-2 * a / (4 * b)))
plt.plot(deformations,
min_x,
'o--',
label=labels[counter],
ms=10,
c=colors[counter])
_deformations = []
_min_x = []
for t in range(len(min_x)):
if (min_x[t] > 0):
_deformations.append(deformations[t])
_min_x.append(min_x[t])
x = np.array(_deformations)
y = np.array(_min_x)
from scipy import interpolate
f = interpolate.interp1d(x, y)
x = np.array([
min(_deformations) + k *
(max(_deformations) - min(_deformations)) / 100 for k in range(100)
])
y = f(x)
from scipy.optimize import curve_fit
popt, pcov = curve_fit(square, y, x, maxfev=2000)
a = popt[0]
b = popt[1]
_y = np.array([(max(y) + 0.1 * max(y)) * k / 100 for k in range(100)])
_x = square(_y, *popt)
print(_x[0])
plt.plot(_x, _y, '-', lw=2, c=colors[counter])
os.chdir(cwd)
plt.xlim([0.015, 0.052])
plt.xlabel('Lattice Deformation $\delta $')
plt.ylabel('Minima on PES ($x_{\min}$, \AA)')
plt.legend()
plt.tight_layout()
plt.savefig("xeq_pressure_summary_Br.pdf")
def get_pes_across_composition(X='Cl'):
cmap = matplotlib.cm.get_cmap('coolwarm')
cwd_1 = os.getcwd()
data_dict = {}
min_x = []
min_y = []
for dir in [
r for r in glob.glob(os.getcwd() + "/*" + str(X) + "*")
if '.pdf' not in r
]:
os.chdir(dir)
cwd_2 = os.getcwd()
data = []
for sub_dir in glob.glob(os.getcwd() + "/disp_111_*_0_05"):
os.chdir(sub_dir)
print(sub_dir)
energy = VaspReader(input_location='./OSZICAR'
).get_free_energies_from_oszicar()[-1]
crystal = VaspReader(input_location='./POSCAR').read_POSCAR()
energy = energy / crystal.total_num_atoms()
info = pickle.load(open('info.p', 'rb'))
info['energy'] = energy
data.append(info)
os.chdir(cwd_2)
os.chdir(cwd_1)
displacements = list(sorted([d['displacement'] for d in data]))
energy = []
for _dis in displacements:
for d in data:
if d['displacement'] == _dis:
energy.append(d['energy'])
energy = [e - energy[0] for e in energy]
x = np.array(displacements)
y = np.array(energy)
from scipy.optimize import curve_fit
popt, pcov = curve_fit(pes, x, y)
x = [0 + (0.6 / 100) * i for i in range(100)]
y = pes(np.array(x), *popt)
a = popt[0]
b = popt[1]
if 2 * a / (4 * b) > 0:
min_x.append(0)
min_y.append(0)
else:
min_x.append(math.sqrt(-2 * a / (4 * b)))
min_y.append(pes(math.sqrt(-2 * a / (4 * b)), *popt))
data_dict[1.0 - data[0]['concentration']] = {'x': x, 'y': y}
for k in list(sorted(data_dict.keys())):
plt.plot(data_dict[k]['x'],
data_dict[k]['y'],
'-',
c=cmap(k),
label=str(k))
# plt.legend(loc=2)
plt.ticklabel_format(style='sci', axis='y', scilimits=(0, 0))
plt.plot(min_x, min_y, 'o', c='#00743F')
max_displacemnt = 0.6
plt.xlim([0, max_displacemnt])
plt.plot([0, max_displacemnt], [0, 0], 'k--')
plt.xlabel('B-Cation Displacement $\Delta d$ (\AA)')
plt.ylabel('$E-E_{\Delta d=0}$ (eV/atom)')
plt.tight_layout()
plt.savefig(X + "_B_111_landscape.pdf")