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
(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
# important when we want to take surface polarity into consideration
LiFePO4.add_oxidation_state_by_element({"Fe": 2, "Li": 1, "P": 5, "O": -2})
slabgen = SlabGenerator(LiFePO4, (0, 0, 1), 10, 10)
all_slabs = slabgen.get_slabs(bonds={("P", "O"): 2})
# any bond between P and O less than 2 Angstroms cannot be broken when generating slabs
print("For the (001) slab of LiFePO4, there are %s terminations." %
(len(all_slabs)))
for slab in all_slabs:
print(slab.is_polar(), slab.is_symmetric())
'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" %
(wulffshape.shape_factor, wulffshape.anisotropy,
wulffshape.weighted_surface_energy))
# If we want to see what our Wulff shape looks like
wulffshape.show(color_set="RdBu", direction=(1.00, 0.25, 0.25))
