def EfccEhcpCalculator(self, EMT, PARAMETERS):
# Return 0 is used when the method is not desired to be used
# return 0
""" This method uses the EMT calculator to calculate and return the difference in energy between a system of
atoms placed in the HCP and FCC structure. """
# The atoms objects are created using the input size and element and the energy calculator
# is set to the EMT calculator
# The Lattice Constants, a,c, for the HCP lattice is here given by the nearest neighbor distance of
# the system in the FCC crystal structure, a = dnn, and the ideal relation between a and
# c: a/c = sqrt(8/3) => c = dnn / sqrt(8/3)
a = beta * PARAMETERS[self.Element][1] * Bohr
c = a * numpy.sqrt(8. / 3.)
# The HCP crystal is created, the size of the crystal is defined as 5,5,5, any smaller crystal will result in
# Neighborlist errors.
atoms1 = HexagonalClosedPacked(size=(5, 5, 5),
directions=[[2, -1, -1,
0], [0, 1, -1, 0],
[0, 0, 0, 1]],
symbol=self.Element,
latticeconstant={
'a': a,
'c': c
})
atoms1.set_calculator(EMT)
# The FCC crystal is created
atoms2 = FaceCenteredCubic(size=(self.Size, self.Size, self.Size),
symbol=self.Element)
atoms2.set_calculator(EMT)
# The energy difference pr atom is calculated and returned
return atoms1.get_potential_energy() / len(
atoms1) - atoms2.get_potential_energy() / len(atoms2)
from ase.lattice.hexagonal import HexagonalClosedPacked
from vasp import Vasp
import matplotlib.pyplot as plt
atoms = HexagonalClosedPacked(symbol='Ru',
latticeconstant={'a': 2.7,
'c/a': 1.584})
a_list = [2.5, 2.6, 2.7, 2.8, 2.9]
covera_list = [1.4, 1.5, 1.6, 1.7, 1.8]
for a in a_list:
energies = []
for covera in covera_list:
atoms = HexagonalClosedPacked(symbol='Ru',
latticeconstant={'a': a,
'c/a': covera})
wd = 'bulk/Ru/{0:1.2f}-{1:1.2f}'.format(a, covera)
calc = Vasp(wd,
xc='PBE',
# the c-axis is longer than the a-axis, so we use
# fewer kpoints.
kpts=[6, 6, 4],
encut=350,
atoms=atoms)
energies.append(atoms.get_potential_energy())
if not None in energies:
plt.plot(covera_list, energies, label=r'a={0} $\AA$'.format(a))
plt.xlabel('$c/a$')
plt.ylabel('Energy (eV)')
plt.legend()
plt.savefig('images/Ru-covera-scan.png')
atoms = HexagonalClosedPacked(symbol='Ru',
latticeconstant={
'a': 2.7,
'c/a': 1.584
})
a_list = [2.5, 2.6, 2.7, 2.8, 2.9]
covera_list = [1.4, 1.5, 1.6, 1.7, 1.8]
for a in a_list:
energies = []
for covera in covera_list:
atoms = HexagonalClosedPacked(symbol='Ru',
latticeconstant={
'a': a,
'c/a': covera
})
wd = 'bulk/Ru/{0:1.2f}-{1:1.2f}'.format(a, covera)
calc = Vasp(
wd,
xc='PBE',
# the c-axis is longer than the a-axis, so we use
# fewer kpoints.
kpts=[6, 6, 4],
encut=350,
atoms=atoms)
energies.append(atoms.get_potential_energy())
if not None in energies:
plt.plot(covera_list, energies, label=r'a={0} $\AA$'.format(a))
plt.xlabel('$c/a$')
plt.ylabel('Energy (eV)')
plt.legend()
plt.savefig('images/Ru-covera-scan.png')