def perform_es_corr(self, gamma, prec, lattice, charge):
"""
Peform Electrostatic Kumagai Correction
Args:
gamma (float): Ewald parameter
prec (int): Precision parameter for reciprical/real lattice vector generation
lattice: Pymatgen Lattice object corresponding to defect supercell
charge (int): Defect charge
Return:
Electrostatic Point Charge contribution to Kumagai Correction (float)
"""
volume = lattice.volume
g_vecs, recip_summation, r_vecs, real_summation = generate_R_and_G_vecs(
gamma, [prec], lattice, self.dielectric)
recip_summation = recip_summation[0]
real_summation = real_summation[0]
es_corr = (recip_summation + real_summation +
self.get_potential_shift(gamma, volume) +
self.get_self_interaction(gamma))
es_corr *= -(charge**2.) * kumagai_to_V / 2. # [eV]
return es_corr
def test_generate_R_and_G_vecs(self):
gamma = 0.19357221
prec = 28
lattice = Lattice([[4.692882, -8.12831, 0.0], [4.692882, 8.12831, 0.0], [0.0, 0.0, 10.03391]])
epsilon = 10.0 * np.identity(3)
g_vecs, recip_summation, r_vecs, real_summation = generate_R_and_G_vecs(gamma, prec, lattice, epsilon)
self.assertEqual(len(g_vecs[0]), 16418)
self.assertAlmostEqual(recip_summation[0], 2.8946556e-15)
self.assertEqual(len(r_vecs[0]), 16299)
self.assertAlmostEqual(real_summation[0], 0.00679361)
def test_generate_R_and_G_vecs(self):
gamma = 0.19357221
prec = 28
lattice = Lattice( [[ 4.692882, -8.12831 , 0.],
[ 4.692882, 8.12831 , 0.],
[ 0., 0., 10.03391 ]])
epsilon = 10. * np.identity(3)
g_vecs, recip_summation, r_vecs, real_summation = generate_R_and_G_vecs( gamma, prec,
lattice, epsilon)
self.assertEqual(len(g_vecs[0]), 16418)
self.assertAlmostEqual(recip_summation[0], 2.8946556e-15)
self.assertEqual(len(r_vecs[0]), 16299)
self.assertAlmostEqual(real_summation[0], 0.00679361)
def get_correction(self, entry):
"""
Gets the Kumagai correction for a defect entry
Args:
entry (DefectEntry): defect entry to compute Kumagai correction on.
Requires following parameters in the DefectEntry to exist:
bulk_atomic_site_averages (list): list of bulk structure"s atomic site averaged ESPs * charge,
in same order as indices of bulk structure
note this is list given by VASP's OUTCAR (so it is multiplied by a test charge of -1)
defect_atomic_site_averages (list): list of defect structure"s atomic site averaged ESPs * charge,
in same order as indices of defect structure
note this is list given by VASP's OUTCAR (so it is multiplied by a test charge of -1)
site_matching_indices (list): list of corresponding site index values for
bulk and defect site structures EXCLUDING the defect site itself
(ex. [[bulk structure site index, defect structure"s corresponding site index], ... ]
initial_defect_structure (Structure): Pymatgen Structure object representing un-relaxed defect
structure
defect_frac_sc_coords (array): Defect Position in fractional coordinates of the supercell
given in bulk_structure
Returns:
KumagaiCorrection values as a dictionary
"""
bulk_atomic_site_averages = entry.parameters[
"bulk_atomic_site_averages"]
defect_atomic_site_averages = entry.parameters[
"defect_atomic_site_averages"]
site_matching_indices = entry.parameters["site_matching_indices"]
defect_sc_structure = entry.parameters["initial_defect_structure"]
defect_frac_sc_coords = entry.parameters["defect_frac_sc_coords"]
lattice = defect_sc_structure.lattice
volume = lattice.volume
q = entry.defect.charge
if not self.metadata["gamma"]:
self.metadata["gamma"] = tune_for_gamma(lattice, self.dielectric)
prec_set = [25, 28]
g_vecs, recip_summation, r_vecs, real_summation = generate_R_and_G_vecs(
self.metadata["gamma"], prec_set, lattice, self.dielectric)
pot_shift = self.get_potential_shift(self.metadata["gamma"], volume)
si = self.get_self_interaction(self.metadata["gamma"])
es_corr = [
(real_summation[ind] + recip_summation[ind] + pot_shift + si)
for ind in range(2)
]
# increase precision if correction is not converged yet
# TODO: allow for larger prec_set to be tried if this fails
if abs(es_corr[0] - es_corr[1]) > 0.0001:
logger.debug(
"Es_corr summation not converged! ({} vs. {})\nTrying a larger prec_set..."
.format(es_corr[0], es_corr[1]))
prec_set = [30, 35]
g_vecs, recip_summation, r_vecs, real_summation = generate_R_and_G_vecs(
self.metadata["gamma"], prec_set, lattice, self.dielectric)
es_corr = [
(real_summation[ind] + recip_summation[ind] + pot_shift + si)
for ind in range(2)
]
if abs(es_corr[0] - es_corr[1]) < 0.0001:
raise ValueError(
"Correction still not converged after trying prec_sets up to 35... serious error."
)
es_corr = es_corr[0] * -(q**2.) * kumagai_to_V / 2. # [eV]
# if no sampling radius specified for pot align, then assuming Wigner-Seitz radius:
if not self.metadata["sampling_radius"]:
wz = lattice.get_wigner_seitz_cell()
dist = []
for facet in wz:
midpt = np.mean(np.array(facet), axis=0)
dist.append(np.linalg.norm(midpt))
self.metadata["sampling_radius"] = min(dist)
# assemble site_list based on matching indices
# [[defect_site object, Vqb for site], .. repeat for all non defective sites]
site_list = []
for bs_ind, ds_ind in site_matching_indices:
Vqb = -(defect_atomic_site_averages[int(ds_ind)] -
bulk_atomic_site_averages[int(bs_ind)])
site_list.append([defect_sc_structure[int(ds_ind)], Vqb])
pot_corr = self.perform_pot_corr(defect_sc_structure,
defect_frac_sc_coords, site_list,
self.metadata["sampling_radius"], q,
r_vecs[0], g_vecs[0],
self.metadata["gamma"])
entry.parameters["kumagai_meta"] = dict(self.metadata)
entry.parameters["potalign"] = pot_corr / (-q) if q else 0.
return {
"kumagai_electrostatic": es_corr,
"kumagai_potential_alignment": pot_corr
}
def test_kumagai(self):
gamma = 0.19357221
prec = 28
lattice = Lattice(
[[4.692882, -8.12831, 0.0], [4.692882, 8.12831, 0.0], [0.0, 0.0, 10.03391]]
)
# note that real/recip vector generation is not dependent on epsilon
g_vecs, _, r_vecs, _ = generate_R_and_G_vecs(
gamma, prec, lattice, 80.0 * np.identity(3)
)
# test real space summation (bigger for large epsilon)
kc_high_diel = KumagaiCorrection(80.0 * np.identity(3), gamma=gamma)
real_sum = kc_high_diel.get_real_summation(gamma, r_vecs[0])
self.assertAlmostEqual(real_sum, 0.00843104)
# test recip space summation (bigger for small epsilon)
kc_low_diel = KumagaiCorrection(0.1 * np.identity(3), gamma=gamma)
recip_sum = kc_low_diel.get_recip_summation(gamma, g_vecs[0], lattice.volume)
self.assertAlmostEqual(recip_sum, 0.31117099)
# test self interaction
si_corr = kc_low_diel.get_self_interaction(gamma)
self.assertAlmostEqual(si_corr, -0.54965249)
# test potenital shift interaction correction
ps_corr = kc_low_diel.get_potential_shift(gamma, lattice.volume)
self.assertAlmostEqual(ps_corr, -0.00871593)
# """Test Defect Entry approach to correction """
bulk_struc = Poscar.from_file(
os.path.join(PymatgenTest.TEST_FILES_DIR, "defect", "CONTCAR_bulk")
).structure
bulk_out = Outcar(os.path.join(PymatgenTest.TEST_FILES_DIR, "defect", "OUTCAR_bulk.gz"))
defect_out = Outcar(os.path.join(PymatgenTest.TEST_FILES_DIR, "defect", "OUTCAR_vac_Ga_-3.gz"))
epsilon = 18.118 * np.identity(3)
vac = Vacancy(bulk_struc, bulk_struc.sites[0], charge=-3)
defect_structure = vac.generate_defect_structure()
defect_frac_coords = [0.0, 0.0, 0.0]
parameters = {
"bulk_atomic_site_averages": bulk_out.electrostatic_potential,
"defect_atomic_site_averages": defect_out.electrostatic_potential,
"site_matching_indices": [[ind, ind - 1] for ind in range(len(bulk_struc))],
"initial_defect_structure": defect_structure,
"defect_frac_sc_coords": defect_frac_coords,
}
dentry = DefectEntry(vac, 0.0, parameters=parameters)
kc = KumagaiCorrection(epsilon)
kcorr = kc.get_correction(dentry)
self.assertAlmostEqual(kcorr["kumagai_electrostatic"], 0.88236299)
self.assertAlmostEqual(kcorr["kumagai_potential_alignment"], 2.09704862)
# test ES correction
high_diel_es_corr = kc_high_diel.perform_es_corr(gamma, prec, lattice, -3.0)
self.assertAlmostEqual(high_diel_es_corr, 0.25176240)
low_diel_es_corr = kc_low_diel.perform_es_corr(gamma, prec, lattice, -3.0)
self.assertAlmostEqual(low_diel_es_corr, 201.28810966)
# test pot correction
site_list = []
for bs_ind, ds_ind in dentry.parameters["site_matching_indices"]:
Vqb = -(
defect_out.electrostatic_potential[ds_ind]
- bulk_out.electrostatic_potential[bs_ind]
)
site_list.append([defect_structure[ds_ind], Vqb])
sampling_radius = dentry.parameters["kumagai_meta"]["sampling_radius"]
gamma = dentry.parameters["kumagai_meta"]["gamma"]
q = -3
g_vecs, _, r_vecs, _ = generate_R_and_G_vecs(
gamma, 28, defect_structure.lattice, np.identity(3)
)
high_diel_pot_corr = kc_high_diel.perform_pot_corr(
defect_structure,
defect_frac_coords,
site_list,
sampling_radius,
q,
r_vecs[0],
g_vecs[0],
gamma,
)
self.assertAlmostEqual(high_diel_pot_corr, 2.35840716)
low_diel_pot_corr = kc_low_diel.perform_pot_corr(
defect_structure,
defect_frac_coords,
site_list,
sampling_radius,
q,
r_vecs[0],
g_vecs[0],
gamma,
)
self.assertAlmostEqual(low_diel_pot_corr, -58.83598095)
# test the kumagai plotter
kcp = kc.plot()
self.assertTrue(kcp)
# check that uncertainty metadata exists
self.assertAlmostEqual(
set(kc.metadata["pot_corr_uncertainty_md"].keys()),
set(["number_sampled", "stats"]),
)
def test_kumagai(self):
gamma = 0.19357221
prec = 28
lattice = Lattice( [[ 4.692882, -8.12831 , 0.],
[ 4.692882, 8.12831 , 0.],
[ 0., 0., 10.03391 ]])
#note that real/recip vector generation is not dependent on epsilon
g_vecs, _, r_vecs, _ = generate_R_and_G_vecs( gamma, prec, lattice, 80. * np.identity(3))
#test real space summation (bigger for large epsilon)
kc_high_diel = KumagaiCorrection( 80. * np.identity(3), gamma=gamma)
real_sum = kc_high_diel.get_real_summation( gamma, r_vecs[0])
self.assertAlmostEqual( real_sum, 0.00843104)
#test recip space summation (bigger for small epsilon)
kc_low_diel = KumagaiCorrection( 0.1 * np.identity(3), gamma=gamma)
recip_sum = kc_low_diel.get_recip_summation( gamma, g_vecs[0], lattice.volume)
self.assertAlmostEqual( recip_sum, 0.31117099)
#test self interaction
si_corr = kc_low_diel.get_self_interaction( gamma)
self.assertAlmostEqual( si_corr, -0.54965249)
#test potenital shift interaction correction
ps_corr = kc_low_diel.get_potential_shift( gamma, lattice.volume)
self.assertAlmostEqual( ps_corr, -0.00871593)
# """Test Defect Entry approach to correction """
bulk_struc = Poscar.from_file(os.path.join( test_dir, 'defect', 'CONTCAR_bulk')).structure
bulk_out = Outcar( os.path.join( test_dir, 'defect', 'OUTCAR_bulk.gz'))
defect_out = Outcar( os.path.join( test_dir, 'defect', 'OUTCAR_vac_Ga_-3.gz'))
epsilon = 18.118 * np.identity(3)
vac = Vacancy(bulk_struc, bulk_struc.sites[0], charge=-3)
defect_structure = vac.generate_defect_structure()
defect_frac_coords = [0.,0.,0.]
parameters = {'bulk_atomic_site_averages': bulk_out.electrostatic_potential,
'defect_atomic_site_averages': defect_out.electrostatic_potential,
'site_matching_indices': [[ind, ind-1] for ind in range(len(bulk_struc))],
'initial_defect_structure': defect_structure,
'defect_frac_sc_coords': defect_frac_coords}
dentry = DefectEntry( vac, 0., parameters=parameters)
kc = KumagaiCorrection( epsilon)
kcorr = kc.get_correction( dentry)
self.assertAlmostEqual( kcorr['kumagai_electrostatic'], 0.88236299)
self.assertAlmostEqual( kcorr['kumagai_potential_alignment'], 2.09704862)
# test ES correction
high_diel_es_corr = kc_high_diel.perform_es_corr( gamma, prec, lattice, -3.)
self.assertAlmostEqual( high_diel_es_corr, 0.25176240)
low_diel_es_corr = kc_low_diel.perform_es_corr( gamma, prec, lattice, -3.)
self.assertAlmostEqual( low_diel_es_corr, 201.28810966)
# test pot correction
site_list = []
for bs_ind, ds_ind in dentry.parameters['site_matching_indices']:
Vqb = -(defect_out.electrostatic_potential[ds_ind] - bulk_out.electrostatic_potential[bs_ind])
site_list.append([defect_structure[ds_ind], Vqb])
sampling_radius = dentry.parameters["kumagai_meta"]["sampling_radius"]
gamma = dentry.parameters["kumagai_meta"]["gamma"]
q = -3
g_vecs, _, r_vecs, _ = generate_R_and_G_vecs( gamma, 28, defect_structure.lattice, np.identity(3))
high_diel_pot_corr = kc_high_diel.perform_pot_corr( defect_structure, defect_frac_coords,
site_list, sampling_radius, q,
r_vecs[0], g_vecs[0], gamma)
self.assertAlmostEqual( high_diel_pot_corr, 2.35840716)
low_diel_pot_corr = kc_low_diel.perform_pot_corr( defect_structure, defect_frac_coords,
site_list, sampling_radius, q,
r_vecs[0], g_vecs[0], gamma)
self.assertAlmostEqual( low_diel_pot_corr, -58.83598095)
#test the kumagai plotter
kcp = kc.plot()
self.assertTrue( kcp)
#check that uncertainty metadata exists
self.assertAlmostEqual(set(kc.metadata['pot_corr_uncertainty_md'].keys()), set(['number_sampled', 'stats']))
