def setUp(self):
module_dir = os.path.dirname(os.path.abspath(__file__))
with open(os.path.join(module_dir, "surface_samples.json")) as data_file:
surface_properties = json.load(data_file)
surface_energies, miller_indices = {}, {}
for mpid in surface_properties.keys():
e_surf_list, miller_list = [], []
for surface in surface_properties[mpid]["surfaces"]:
e_surf_list.append(surface["surface_energy"])
miller_list.append(surface["miller_index"])
surface_energies[mpid] = e_surf_list
miller_indices[mpid] = miller_list
# In the case of a high anisotropy material
# Nb: mp-8636
latt_Nb = Lattice.cubic(2.992)
# In the case of an fcc material
# Ir: mp-101
latt_Ir = Lattice.cubic(3.8312)
# In the case of a hcp material
# Ti: mp-72
latt_Ti = Lattice.hexagonal(4.6000, 2.8200)
self.ucell_Nb = Structure(
latt_Nb,
["Nb", "Nb", "Nb", "Nb"],
[[0, 0, 0], [0, 0.5, 0.5], [0.5, 0, 0.5], [0.5, 0.5, 0]],
)
self.wulff_Nb = WulffShape(
latt_Nb, miller_indices["mp-8636"], surface_energies["mp-8636"]
)
self.ucell_Ir = Structure(
latt_Nb,
["Ir", "Ir", "Ir", "Ir"],
[[0, 0, 0], [0, 0.5, 0.5], [0.5, 0, 0.5], [0.5, 0.5, 0]],
)
self.wulff_Ir = WulffShape(
latt_Ir, miller_indices["mp-101"], surface_energies["mp-101"]
)
self.ucell_Ti = Structure(
latt_Ti,
["Ti", "Ti", "Ti"],
[[0, 0, 0], [0.333333, 0.666667, 0.5], [0.666667, 0.333333, 0.5]],
)
self.wulff_Ti = WulffShape(
latt_Ti, miller_indices["mp-72"], surface_energies["mp-72"]
)
self.cube = WulffShape(Lattice.cubic(1), [(1, 0, 0)], [1])
self.hex_prism = WulffShape(
Lattice.hexagonal(2.63, 5.21), [(0, 0, 1), (1, 0, 0)], [0.35, 0.53]
)
self.surface_properties = surface_properties
def get_wulff_shape(self, material_id):
"""
Constructs a Wulff shape for a material.
Args:
material_id (str): Materials Project material_id, e.g. 'mp-123'.
Returns:
pymatgen.analysis.wulff.WulffShape
"""
from pymatgen.analysis.wulff import WulffShape
from pymatgen.symmetry.analyzer import SpacegroupAnalyzer
structure = self.get_structure_by_material_id(material_id)
surfaces = self.get_surface_data(material_id)["surfaces"]
lattice = (
SpacegroupAnalyzer(structure).get_conventional_standard_structure().lattice
)
miller_energy_map = {}
for surf in surfaces:
miller = tuple(surf["miller_index"])
# Prefer reconstructed surfaces, which have lower surface energies.
if (miller not in miller_energy_map) or surf["is_reconstructed"]:
miller_energy_map[miller] = surf["surface_energy"]
millers, energies = zip(*miller_energy_map.items())
return WulffShape(lattice, millers, energies)
def wulff_shape_from_chempot(self, chempot, symprec=1e-5):
"""
Method to get the Wulff shape at a specific chemical potential.
Args:
chempot (float): The chemical potential the Wulff Shape exist in.
"""
# Check if the user provided chemical potential is within the
# predetermine range of chemical potential. If not, raise a warning
if not max(self.chempot_range) >= chempot >= min(self.chempot_range):
warnings.warn("The provided chemical potential is outside the range "
"of chemical potential (%s to %s). The resulting Wulff "
"shape might not be reasonable." %(min(self.chempot_range),
max(self.chempot_range)))
latt = SpacegroupAnalyzer(self.ucell_entry.structure).\
get_conventional_standard_structure().lattice
miller_list = self.vasprun_dict.keys()
e_surf_list = []
for hkl in miller_list:
# At each possible configuration, we calculate surface energy as a
# function of u and take the lowest surface energy (corresponds to
# the most stable slab termination at that particular u)
surf_e_range_list = [self.calculate_gamma(vasprun)
for vasprun in self.vasprun_dict[hkl]]
e_list = []
for e_range in surf_e_range_list:
slope, intercept = self.get_slope_and_intercept(e_range)
e_list.append(slope * chempot + intercept)
e_surf_list.append(min(e_list))
return WulffShape(latt, miller_list, e_surf_list, symprec=symprec)
def wulff(st, miller_list=None, e_surf_list=None, show=0):
from pymatgen.core.structure import Structure
stpm = st.convert2pymatgen()
lat = stpm.lattice
recp_lattice = stpm.lattice.reciprocal_lattice_crystallographic
recp = Structure(recp_lattice, ["H"], [[0, 0, 0]])
dire = Structure(stpm.lattice, ["H"], [[0, 0, 0]])
print(dire.get_space_group_info())
print(recp.get_space_group_info())
# print(lat)
from pymatgen.analysis.wulff import WulffShape
WS = WulffShape(lat, miller_list, e_surf_list)
# print(dir(WS))
anisotropy = WS.anisotropy
weighted_surface_energy = WS.weighted_surface_energy
if show:
WS.show()
return anisotropy, weighted_surface_energy
def Wullff(self,
formate,
surface_energy,
pic_name,
directions=(3, 4, 4),
x=0.47,
y=-16):
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
from pymatgen.ext.matproj import MPRester
from pymatgen.io.cif import CifParser
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import pandas as pd
import os
if 'cif' in str(formate):
os.chdir(r"D:\Desktop\VASP practical\Cif library")
print(os.getcwd())
structure = CifParser(str(pic_name) + '.cif')
struct = structure.get_structures()[0]
else:
mpr = MPRester()
mp_id = formate
struct = mpr.get_structure_by_material_id(mp_id)
surface_energies = surface_energy
miller_list = surface_energies.keys()
e_surf_list = surface_energies.values()
font2 = {
'family': 'Times New Roman',
'fontsize': '40',
'weight': 'bold',
}
wulffshape = WulffShape(struct.lattice, miller_list, e_surf_list)
print(wulffshape.area_fraction_dict)
os.chdir(self.dire)
dict1 = wulffshape.area_fraction_dict
xx = []
yy = []
for key, value in dict1.items():
xx.append(key)
yy.append(value)
cc = wulffshape.effective_radius
bb = wulffshape.volume
dd = wulffshape.shape_factor
print(wulffshape.effective_radius)
res = pd.DataFrame({'Slab': xx, 'area': yy}) #构造原始数据文件
df = res.sort_values(by='area', ascending=True)
with open(str(pic_name) + '.txt', 'w') as f:
f.write('effective radius:' + str(cc) + ' ' + "volume:" +
str(bb) + ' ' + "shape factor:" + str(dd))
print(cc)
# os.chdir(r"D:\Desktop\VASP practical\workdir")
df.to_excel(str(pic_name) + ".xlsx") #生成Excel文件，并存到指定文件路径下
wulffshape.get_plot(bar_on=True,
aspect_ratio=(8, 8),
bar_pos=[0, 0.85, 1.1, 0.045],
direction=directions)
plt.title(str(pic_name), font2, x=x, y=y)
plt.savefig(str(pic_name) + ".png",
bbox_inches='tight',
transparent=True,
dpi=600,
format='png')
plt.show
os.chdir(r"D:\Desktop\VASP practical\workdir")
print('finished')
(2, 1, 0): 2.3969,
(3, 3, 2): 2.0944,
(1, 0, 0): 2.2084,
(2, 1, 1): 2.2353,
(3, 2, 2): 2.1242,
(3, 2, 1): 2.3183,
(2, 2, 1): 2.1732,
(3, 3, 1): 2.2288,
(3, 1, 1): 2.3039,
(1, 1, 1): 1.9235
}
miller_list = surface_energies_Ni.keys()
e_surf_list = surface_energies_Ni.values()
# We can now construct a Wulff shape with an accuracy up to a max Miller index of 3
wulffshape = WulffShape(Ni.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" %
(wulffshape.shape_factor, wulffshape.anisotropy,
wulffshape.weighted_surface_energy))
# If we want to see what our Wulff shape looks like
wulffshape.show()
# Lets try something a little more complicated, say LiFePO4
from pymatgen.util.testing import PymatgenTest
# Get the LiFePO4 structure
LiFePO4 = PymatgenTest.get_structure("LiFePO4")
# Let's add some oxidation states to LiFePO4, this will be
# all_slabs = slabgen.get_slabs()
# print("The Ni(111) slab only has %s termination." %(len(all_slabs)))
# Now let's assume that we then calculated the surface energies for these slabs
# Surface energy values in J/m^2
surface_energies_Ni = {
(0, 0, 1): 2.3869,
(2, 0, 1): 2.2862,
(1, -1, 0): 2.3964,
(0, 2, 0): 2.0944,
(-2, -2, 1): 0.9353,
(2, -2, 0): 2.3183,
(-1, 1, 1): 2.2288,
(0, 2, 2): 1.9235
}
miller_list = surface_energies_Ni.keys()
e_surf_list = surface_energies_Ni.values()
# We can now construct a Wulff shape with an accuracy up to a max Miller index of 3
wulffshape = WulffShape(struct.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" %(wulffshape.shape_factor,
# wulffshape.anisotropy,
# wulffshape.weighted_surface_energy))
# If we want to see what our Wulff shape looks like
wulffshape.show()
