def get_hull_distance(competing_phase_directory='../competing_phases'):
"""
Calculate the material's distance to the thermodynamic hull,
based on species in the Materials Project database.
Args:
competing_phase_directory (str): absolute or relative path
to the location where your competing phases have been
relaxed. The default expectation is that they are stored
in a directory named 'competing_phases' at the same level
as your material's relaxation directory.
Returns:
float. distance (eV/atom) between the material and the
hull.
"""
finished_competitors = {}
original_directory = os.getcwd()
# Determine which competing phases have been relaxed in the current
# framework and store them in a dictionary ({formula: entry}).
if os.path.isdir(competing_phase_directory):
os.chdir(competing_phase_directory)
for comp_dir in [
dir for dir in os.listdir(os.getcwd()) if os.path.isdir(dir) and
is_converged(dir)
]:
vasprun = Vasprun('{}/vasprun.xml'.format(comp_dir))
composition = vasprun.final_structure.composition
energy = vasprun.final_energy
finished_competitors[comp_dir] = ComputedEntry(composition, energy)
os.chdir(original_directory)
else:
raise ValueError('Competing phase directory does not exist.')
composition = Structure.from_file('POSCAR').composition
try:
energy = Vasprun('vasprun.xml').final_energy
except:
raise ValueError('This directory does not have a converged vasprun.xml')
my_entry = ComputedEntry(composition, energy) # 2D material
entries = MPR.get_entries_in_chemsys(
[elt.symbol for elt in composition]
)
# If the energies of competing phases have been calculated in
# the current framework, put them in the phase diagram instead
# of the MP energies.
for i in range(len(entries)):
formula = entries[i].composition.reduced_formula
if formula in finished_competitors:
entries[i] = finished_competitors[formula]
else:
entries[i] = ComputedEntry(entries[i].composition, 100)
entries.append(my_entry) # 2D material
pda = PDAnalyzer(PhaseDiagram(entries))
decomp = pda.get_decomp_and_e_above_hull(my_entry, allow_negative=True)
return decomp[1]
def get_hull_distance(competing_phase_directory='../competing_phases'):
"""
Calculate the material's distance to the thermodynamic hull,
based on species in the Materials Project database.
Args:
competing_phase_directory (str): absolute or relative path
to the location where your competing phases have been
relaxed. The default expectation is that they are stored
in a directory named 'competing_phases' at the same level
as your material's relaxation directory.
Returns:
float. distance (eV/atom) between the material and the
hull.
"""
finished_competitors = {}
original_directory = os.getcwd()
# Determine which competing phases have been relaxed in the current
# framework and store them in a dictionary ({formula: entry}).
if os.path.isdir(competing_phase_directory):
os.chdir(competing_phase_directory)
for comp_dir in [
dir for dir in os.listdir(os.getcwd())
if os.path.isdir(dir) and is_converged(dir)
]:
vasprun = Vasprun('{}/vasprun.xml'.format(comp_dir))
composition = vasprun.final_structure.composition
energy = vasprun.final_energy
finished_competitors[comp_dir] = ComputedEntry(composition, energy)
os.chdir(original_directory)
else:
raise ValueError('Competing phase directory does not exist.')
composition = Structure.from_file('POSCAR').composition
try:
energy = Vasprun('vasprun.xml').final_energy
except:
raise ValueError(
'This directory does not have a converged vasprun.xml')
my_entry = ComputedEntry(composition, energy) # 2D material
entries = MPR.get_entries_in_chemsys([elt.symbol for elt in composition])
# If the energies of competing phases have been calculated in
# the current framework, put them in the phase diagram instead
# of the MP energies.
for i in range(len(entries)):
formula = entries[i].composition.reduced_formula
if formula in finished_competitors:
entries[i] = finished_competitors[formula]
else:
entries[i] = ComputedEntry(entries[i].composition, 100)
entries.append(my_entry) # 2D material
pda = PDAnalyzer(PhaseDiagram(entries))
decomp = pda.get_decomp_and_e_above_hull(my_entry, allow_negative=True)
return decomp[1]
def relax(dim=2, submit=True, force_overwrite=False):
"""
Writes input files and (optionally) submits a self-consistent
relaxation. Should be run before pretty much anything else, in
order to get the right energy and structure of the material.
Args:
dim (int): 2 for relaxing a 2D material, 3 for a 3D material.
submit (bool): Whether or not to submit the job.
force_overwrite (bool): Whether or not to overwrite files
if an already converged vasprun.xml exists in the
directory.
"""
if force_overwrite or not utl.is_converged(os.getcwd()):
directory = os.getcwd().split('/')[-1]
# vdw_kernel.bindat file required for VDW calculations.
if VDW_KERNEL != '/path/to/vdw_kernel.bindat':
os.system('cp {} .'.format(VDW_KERNEL))
# KPOINTS
Kpoints.automatic_density(Structure.from_file('POSCAR'),
1000).write_file('KPOINTS')
# INCAR
INCAR_DICT.update({'MAGMOM': utl.get_magmom_string()})
Incar.from_dict(INCAR_DICT).write_file('INCAR')
# POTCAR
utl.write_potcar()
# Special tasks only performed for 2D materials.
if dim == 2:
# Ensure 20A interlayer vacuum
utl.add_vacuum(20 - utl.get_spacing(), 0.9)
# Remove all z k-points.
kpts_lines = open('KPOINTS').readlines()
with open('KPOINTS', 'w') as kpts:
for line in kpts_lines[:3]:
kpts.write(line)
kpts.write(kpts_lines[3].split()[0] + ' '
+ kpts_lines[3].split()[1] + ' 1')
# Submission script
if QUEUE == 'pbs':
utl.write_pbs_runjob(directory, 1, 16, '800mb', '6:00:00',
VASP_2D)
submission_command = 'qsub runjob'
elif QUEUE == 'slurm':
utl.write_slurm_runjob(directory, 16, '800mb', '6:00:00',
VASP_2D)
submission_command = 'sbatch runjob'
if submit:
os.system(submission_command)
def relax(dim=2, submit=True, force_overwrite=False):
"""
Writes input files and (optionally) submits a self-consistent
relaxation. Should be run before pretty much anything else, in
order to get the right energy and structure of the material.
Args:
dim (int): 2 for relaxing a 2D material, 3 for a 3D material.
submit (bool): Whether or not to submit the job.
force_overwrite (bool): Whether or not to overwrite files
if an already converged vasprun.xml exists in the
directory.
"""
if force_overwrite or not utl.is_converged(os.getcwd()):
directory = os.getcwd().split('/')[-1]
# vdw_kernel.bindat file required for VDW calculations.
if VDW_KERNEL != '/path/to/vdw_kernel.bindat':
os.system('cp {} .'.format(VDW_KERNEL))
# KPOINTS
Kpoints.automatic_density(Structure.from_file('POSCAR'),
1000).write_file('KPOINTS')
# INCAR
INCAR_DICT.update({'MAGMOM': utl.get_magmom_string()})
Incar.from_dict(INCAR_DICT).write_file('INCAR')
# POTCAR
utl.write_potcar()
# Special tasks only performed for 2D materials.
if dim == 2:
# Ensure 20A interlayer vacuum
utl.add_vacuum(20 - utl.get_spacing(), 0.9)
# Remove all z k-points.
kpts_lines = open('KPOINTS').readlines()
with open('KPOINTS', 'w') as kpts:
for line in kpts_lines[:3]:
kpts.write(line)
kpts.write(kpts_lines[3].split()[0] + ' ' +
kpts_lines[3].split()[1] + ' 1')
# Submission script
if QUEUE == 'pbs':
utl.write_pbs_runjob(directory, 1, 16, '800mb', '6:00:00', VASP_2D)
submission_command = 'qsub runjob'
elif QUEUE == 'slurm':
utl.write_slurm_runjob(directory, 16, '800mb', '6:00:00', VASP_2D)
submission_command = 'sbatch runjob'
if submit:
os.system(submission_command)
competing_species = get_competing_species(directories)
relax_competing_species(competing_species)
for directory in directories:
os.chdir(directory)
relax()
os.chdir('../')
loop = True
while loop:
print('>> Checking convergence')
finished_2d, finished_3d = [], []
for directory in directories:
if is_converged(directory):
finished_2d.append(directory)
for directory in competing_species:
if is_converged('all_competitors/{}'.format(directory[0])):
finished_3d.append(directory[0])
if len(finished_2d + finished_3d) == len(directories +
competing_species):
print('>> Plotting hull distances')
plot_hull_distances(get_hull_distances(finished_2d))
loop = False
else:
print('>> Not all directories converged ({}/{})'.format(
len(finished_2d + finished_3d),
len(directories + competing_species)))
os.chdir(directory)
converged[directory] = False
run_friction_calculations()
os.chdir('../')
loop = True
while loop:
time.sleep(INTERVAL)
loop = False
for directory in directories:
os.chdir(directory)
converged[directory] = True
for subdirectory in [
dir for dir in os.listdir(os.getcwd())
if os.path.isdir(dir)]:
if not is_converged(subdirectory):
converged[directory] = False
break
if not converged[directory]:
print('>> Not all directories converged')
loop = True
print('>> Plotting gamma surface for {}'.format(directory))
plot_gamma_surface()
os.chdir('../')
and dir not in ['all_competitors']]
if __name__ == '__main__':
for directory in directories:
os.chdir(directory)
run_linemode_calculation()
os.chdir('../')
loop = True
while loop:
print('>> Checking convergence')
finished = []
for directory in directories:
if is_converged('{}/pbe_bands'.format(directory)):
finished.append(directory)
if len(finished) == len(directories):
print('>> Plotting band structures')
for directory in finished:
os.chdir('{}/pbe_bands'.format(directory))
plot_normal_band_structure()
os.chdir('../../')
loop = False
else:
print('>> Not all directories converged ({}/{})'.format(
len(finished), len(directories)))
time.sleep(INTERVAL)
]
if __name__ == '__main__':
for directory in directories:
os.chdir(directory)
run_linemode_calculation()
os.chdir('../')
loop = True
while loop:
print('>> Checking convergence')
finished = []
for directory in directories:
if is_converged('{}/pbe_bands'.format(directory)):
finished.append(directory)
if len(finished) == len(directories):
print('>> Plotting band structures')
for directory in finished:
os.chdir('{}/pbe_bands'.format(directory))
plot_normal_band_structure()
os.chdir('../../')
loop = False
else:
print('>> Not all directories converged ({}/{})'.format(
len(finished), len(directories)))
time.sleep(INTERVAL)
def plot_ion_hull_and_voltages(ion, fmt='pdf'):
"""
Plots the phase diagram between the pure material and pure ion,
Connecting the points on the convex hull of the phase diagram.
Args:
ion (str): name of atom that was intercalated, e.g. 'Li'.
fmt (str): matplotlib format style. Check the matplotlib
docs for options.
"""
# Calculated with the relax() function in
# twod_materials.stability.startup. If you are using other input
# parameters, you need to recalculate these values!
ion_ev_fu = {'Li': -1.7540797, 'Mg': -1.31976062, 'Al': -3.19134607}
energy = Vasprun('vasprun.xml').final_energy
composition = Structure.from_file('POSCAR').composition
# Get the formula (with single-digit integers preceded by a '_').
twod_material = list(composition.reduced_formula)
twod_formula = str()
for i in range(len(twod_material)):
try:
int(twod_material[i])
twod_formula += '_{}'.format(twod_material[i])
except:
twod_formula += twod_material[i]
twod_ev_fu = energy / composition.get_reduced_composition_and_factor()[1]
data = [(0, 0, 0, twod_ev_fu)] # (at% ion, n_ions, E_F, abs_energy)
for directory in [
dir for dir in os.listdir(os.getcwd()) if os.path.isdir(dir)
]:
if is_converged(directory):
os.chdir(directory)
energy = Vasprun('vasprun.xml').final_energy
composition = Structure.from_file('POSCAR').composition
ion_fraction = composition.get_atomic_fraction(ion)
no_ion_comp_dict = composition.as_dict()
no_ion_comp_dict.update({ion: 0})
no_ion_comp = Composition.from_dict(no_ion_comp_dict)
n_twod_fu = no_ion_comp.get_reduced_composition_and_factor()[1]
n_ions = composition[ion] / n_twod_fu
E_F = ((energy - composition[ion] * ion_ev_fu[ion] -
twod_ev_fu * n_twod_fu) / composition.num_atoms)
data.append((ion_fraction, n_ions, E_F, energy / n_twod_fu))
os.chdir('../')
data.append((1, 1, 0, ion_ev_fu[ion])) # Pure ion
sorted_data = sorted(data, key=operator.itemgetter(0))
# Determine which compositions are on the convex hull.
energy_profile = np.array([[item[0], item[2]] for item in sorted_data
if item[2] <= 0])
hull = ConvexHull(energy_profile)
convex_ion_fractions = [
energy_profile[vertex, 0] for vertex in hull.vertices
]
convex_formation_energies = [
energy_profile[vertex, 1] for vertex in hull.vertices
]
convex_ion_fractions.append(convex_ion_fractions.pop(0))
convex_formation_energies.append(convex_formation_energies.pop(0))
concave_ion_fractions = [
pt[0] for pt in sorted_data if pt[0] not in convex_ion_fractions
]
concave_formation_energies = [
pt[2] for pt in sorted_data if pt[0] not in convex_ion_fractions
]
voltage_profile = []
j = 0
k = 0
for i in range(1, len(sorted_data) - 1):
if sorted_data[i][0] in convex_ion_fractions:
voltage = -(
((sorted_data[i][3] - sorted_data[k][3]) -
(sorted_data[i][1] - sorted_data[k][1]) * ion_ev_fu[ion]) /
(sorted_data[i][1] - sorted_data[k][1]))
voltage_profile.append((sorted_data[k][0], voltage))
voltage_profile.append((sorted_data[i][0], voltage))
j += 1
k = i
voltage_profile.append((voltage_profile[-1][0], 0))
voltage_profile.append((1, 0))
voltage_profile_x = [tup[0] for tup in voltage_profile]
voltage_profile_y = [tup[1] for tup in voltage_profile]
ax = plt.figure(figsize=(14, 10)).gca()
ax.plot([0, 1], [0, 0], 'k--')
ax.plot(convex_ion_fractions,
convex_formation_energies,
'b-',
marker='o',
markersize=12,
markeredgecolor='none')
ax.plot(concave_ion_fractions,
concave_formation_energies,
'r',
marker='o',
linewidth=0,
markersize=12,
markeredgecolor='none')
ax2 = ax.twinx()
ax2.plot(voltage_profile_x, voltage_profile_y, 'k-', marker='o')
ax.text(0, 0.002, r'$\mathrm{%s}$' % twod_formula, family='serif', size=24)
ax.text(0.99,
0.002,
r'$\mathrm{%s}$' % ion,
family='serif',
size=24,
horizontalalignment='right')
ax.set_xticklabels(ax.get_xticks(), family='serif', size=20)
ax.set_yticklabels(ax.get_yticks(), family='serif', size=20)
ax2.set_yticklabels(ax2.get_yticks(), family='serif', size=20)
ax.set_xlabel('at% {}'.format(ion), family='serif', size=28)
ax.set_ylabel(r'$\mathrm{E_F\/(eV/atom)}$', size=28)
ax2.yaxis.set_label_position('right')
if ion == 'Li':
ax2.set_ylabel(r'$\mathrm{Potential\/vs.\/Li/Li^+\/(V)}$', size=28)
elif ion == 'Mg':
ax2.set_ylabel(r'$\mathrm{Potential\/vs.\/Mg/Mg^{2+}\/(V)}$', size=28)
elif ion == 'Al':
ax2.set_ylabel(r'$\mathrm{Potential\/vs.\/Al/Al^{3+}\/(V)}$', size=28)
plt.savefig('{}_hull.{}'.format(ion, fmt), transparent=True)
def plot_band_alignments(directories, run_type='PBE', fmt='pdf'):
"""
Plot CBM's and VBM's of all compounds together, relative to the band
edges of H2O.
Args:
directories (list): list of the directory paths for materials
to include in the plot.
run_type (str): 'PBE' or 'HSE', so that the function knows which
subdirectory to go into (pbe_bands or hse_bands).
fmt (str): matplotlib format style. Check the matplotlib
docs for options.
"""
if run_type == 'HSE':
subdirectory = 'hse_bands'
else:
subdirectory = 'pbe_bands'
band_gaps = {}
for directory in directories:
if is_converged('{}/{}'.format(directory, subdirectory)):
os.chdir('{}/{}'.format(directory, subdirectory))
band_structure = Vasprun('vasprun.xml').get_band_structure()
band_gap = band_structure.get_band_gap()
# Vacuum level energy from LOCPOT.
locpot = Locpot.from_file('LOCPOT')
evac = max(locpot.get_average_along_axis(2))
if not band_structure.is_metal():
is_direct = band_gap['direct']
cbm = band_structure.get_cbm()
vbm = band_structure.get_vbm()
else:
cbm = None
vbm = None
is_metal = True
is_direct = False
band_gaps[directory] = {
'CBM': cbm,
'VBM': vbm,
'Direct': is_direct,
'Metal': band_structure.is_metal(),
'E_vac': evac
}
os.chdir('../../')
ax = plt.figure(figsize=(16, 10)).gca()
x_max = len(band_gaps) * 1.315
ax.set_xlim(0, x_max)
# Rectangle representing band edges of water.
ax.add_patch(
plt.Rectangle((0, -5.67),
height=1.23,
width=len(band_gaps),
facecolor='#00cc99',
linewidth=0))
ax.text(len(band_gaps) * 1.01,
-4.44,
r'$\mathrm{H+/H_2}$',
size=20,
verticalalignment='center')
ax.text(len(band_gaps) * 1.01,
-5.67,
r'$\mathrm{O_2/H_2O}$',
size=20,
verticalalignment='center')
x_ticklabels = []
y_min = -8
i = 0
# Nothing but lies.
are_directs, are_indirects, are_metals = False, False, False
for compound in [cpd for cpd in directories if cpd in band_gaps]:
x_ticklabels.append(compound)
# Plot all energies relative to their vacuum level.
evac = band_gaps[compound]['E_vac']
if band_gaps[compound]['Metal']:
cbm = -8
vbm = -2
else:
cbm = band_gaps[compound]['CBM']['energy'] - evac
vbm = band_gaps[compound]['VBM']['energy'] - evac
# Add a box around direct gap compounds to distinguish them.
if band_gaps[compound]['Direct']:
are_directs = True
linewidth = 5
elif not band_gaps[compound]['Metal']:
are_indirects = True
linewidth = 0
# Metals are grey.
if band_gaps[compound]['Metal']:
are_metals = True
linewidth = 0
color_code = '#404040'
else:
color_code = '#002b80'
# CBM
ax.add_patch(
plt.Rectangle((i, cbm),
height=-cbm,
width=0.8,
facecolor=color_code,
linewidth=linewidth,
edgecolor="#e68a00"))
# VBM
ax.add_patch(
plt.Rectangle((i, y_min),
height=(vbm - y_min),
width=0.8,
facecolor=color_code,
linewidth=linewidth,
edgecolor="#e68a00"))
i += 1
ax.set_ylim(y_min, 0)
# Set tick labels
ax.set_xticks([n + 0.4 for n in range(i)])
ax.set_xticklabels(x_ticklabels, family='serif', size=20, rotation=60)
ax.set_yticklabels(ax.get_yticks(), family='serif', size=20)
# Add a legend
height = y_min
if are_directs:
ax.add_patch(
plt.Rectangle((i * 1.165, height),
width=i * 0.15,
height=(-y_min * 0.1),
facecolor='#002b80',
edgecolor='#e68a00',
linewidth=5))
ax.text(i * 1.24,
height - y_min * 0.05,
'Direct',
family='serif',
color='w',
size=20,
horizontalalignment='center',
verticalalignment='center')
height -= y_min * 0.15
if are_indirects:
ax.add_patch(
plt.Rectangle((i * 1.165, height),
width=i * 0.15,
height=(-y_min * 0.1),
facecolor='#002b80',
linewidth=0))
ax.text(i * 1.24,
height - y_min * 0.05,
'Indirect',
family='serif',
size=20,
color='w',
horizontalalignment='center',
verticalalignment='center')
height -= y_min * 0.15
if are_metals:
ax.add_patch(
plt.Rectangle((i * 1.165, height),
width=i * 0.15,
height=(-y_min * 0.1),
facecolor='#404040',
linewidth=0))
ax.text(i * 1.24,
height - y_min * 0.05,
'Metal',
family='serif',
size=20,
color='w',
horizontalalignment='center',
verticalalignment='center')
# Who needs axes?
ax.spines['top'].set_visible(False)
ax.spines['right'].set_visible(False)
ax.spines['bottom'].set_visible(False)
ax.spines['left'].set_visible(False)
ax.yaxis.set_ticks_position('left')
ax.xaxis.set_ticks_position('bottom')
ax.set_ylabel('eV', family='serif', size=24)
plt.savefig('band_alignments.{}'.format(fmt), transparent=True)
plt.close()
def plot_ion_hull_and_voltages(ion, fmt='pdf'):
"""
Plots the phase diagram between the pure material and pure ion,
Connecting the points on the convex hull of the phase diagram.
Args:
ion (str): name of atom that was intercalated, e.g. 'Li'.
fmt (str): matplotlib format style. Check the matplotlib
docs for options.
"""
# Calculated with the relax() function in
# twod_materials.stability.startup. If you are using other input
# parameters, you need to recalculate these values!
ion_ev_fu = {'Li': -1.7540797, 'Mg': -1.31976062, 'Al': -3.19134607}
energy = Vasprun('vasprun.xml').final_energy
composition = Structure.from_file('POSCAR').composition
# Get the formula (with single-digit integers preceded by a '_').
twod_material = list(composition.reduced_formula)
twod_formula = str()
for i in range(len(twod_material)):
try:
int(twod_material[i])
twod_formula += '_{}'.format(twod_material[i])
except:
twod_formula += twod_material[i]
twod_ev_fu = energy / composition.get_reduced_composition_and_factor()[1]
data = [(0, 0, 0, twod_ev_fu)] # (at% ion, n_ions, E_F, abs_energy)
for directory in [
dir for dir in os.listdir(os.getcwd()) if os.path.isdir(dir)]:
if is_converged(directory):
os.chdir(directory)
energy = Vasprun('vasprun.xml').final_energy
composition = Structure.from_file('POSCAR').composition
ion_fraction = composition.get_atomic_fraction(ion)
no_ion_comp_dict = composition.as_dict()
no_ion_comp_dict.update({ion: 0})
no_ion_comp = Composition.from_dict(no_ion_comp_dict)
n_twod_fu = no_ion_comp.get_reduced_composition_and_factor()[1]
n_ions = composition[ion] / n_twod_fu
E_F = (
(energy - composition[ion] * ion_ev_fu[ion]
- twod_ev_fu * n_twod_fu)
/ composition.num_atoms
)
data.append((ion_fraction, n_ions, E_F, energy / n_twod_fu))
os.chdir('../')
data.append((1, 1, 0, ion_ev_fu[ion])) # Pure ion
sorted_data = sorted(data, key=operator.itemgetter(0))
# Determine which compositions are on the convex hull.
energy_profile = np.array([[item[0], item[2]]
for item in sorted_data if item[2] <= 0])
hull = ConvexHull(energy_profile)
convex_ion_fractions = [
energy_profile[vertex, 0] for vertex in hull.vertices]
convex_formation_energies = [
energy_profile[vertex, 1] for vertex in hull.vertices]
convex_ion_fractions.append(convex_ion_fractions.pop(0))
convex_formation_energies.append(convex_formation_energies.pop(0))
concave_ion_fractions = [
pt[0] for pt in sorted_data if pt[0] not in convex_ion_fractions]
concave_formation_energies = [
pt[2] for pt in sorted_data if pt[0] not in convex_ion_fractions]
voltage_profile = []
j = 0
k = 0
for i in range(1, len(sorted_data) - 1):
if sorted_data[i][0] in convex_ion_fractions:
voltage = -(
((sorted_data[i][3] - sorted_data[k][3])
- (sorted_data[i][1] - sorted_data[k][1]) * ion_ev_fu[ion])
/ (sorted_data[i][1] - sorted_data[k][1])
)
voltage_profile.append((sorted_data[k][0], voltage))
voltage_profile.append((sorted_data[i][0], voltage))
j += 1
k = i
voltage_profile.append((voltage_profile[-1][0], 0))
voltage_profile.append((1, 0))
voltage_profile_x = [tup[0] for tup in voltage_profile]
voltage_profile_y = [tup[1] for tup in voltage_profile]
ax = plt.figure(figsize=(14, 10)).gca()
ax.plot([0, 1], [0, 0], 'k--')
ax.plot(convex_ion_fractions, convex_formation_energies, 'b-', marker='o',
markersize=12, markeredgecolor='none')
ax.plot(concave_ion_fractions, concave_formation_energies, 'r', marker='o',
linewidth=0, markersize=12, markeredgecolor='none')
ax2 = ax.twinx()
ax2.plot(voltage_profile_x, voltage_profile_y, 'k-', marker='o')
ax.text(0, 0.002, r'$\mathrm{%s}$' % twod_formula, family='serif', size=24)
ax.text(0.99, 0.002, r'$\mathrm{%s}$' % ion, family='serif', size=24,
horizontalalignment='right')
ax.set_xticklabels(ax.get_xticks(), family='serif', size=20)
ax.set_yticklabels(ax.get_yticks(), family='serif', size=20)
ax2.set_yticklabels(ax2.get_yticks(), family='serif', size=20)
ax.set_xlabel('at% {}'.format(ion), family='serif', size=28)
ax.set_ylabel(r'$\mathrm{E_F\/(eV/atom)}$', size=28)
ax2.yaxis.set_label_position('right')
if ion == 'Li':
ax2.set_ylabel(r'$\mathrm{Potential\/vs.\/Li/Li^+\/(V)}$', size=28)
elif ion == 'Mg':
ax2.set_ylabel(r'$\mathrm{Potential\/vs.\/Mg/Mg^{2+}\/(V)}$', size=28)
elif ion == 'Al':
ax2.set_ylabel(r'$\mathrm{Potential\/vs.\/Al/Al^{3+}\/(V)}$', size=28)
plt.savefig('{}_hull.{}'.format(ion, fmt), transparent=True)
def plot_band_alignments(directories, run_type="PBE", fmt="pdf"):
"""
Plot CBM's and VBM's of all compounds together, relative to the band
edges of H2O.
Args:
directories (list): list of the directory paths for materials
to include in the plot.
run_type (str): 'PBE' or 'HSE', so that the function knows which
subdirectory to go into (pbe_bands or hse_bands).
fmt (str): matplotlib format style. Check the matplotlib
docs for options.
"""
if run_type == "HSE":
subdirectory = "hse_bands"
else:
subdirectory = "pbe_bands"
band_gaps = {}
for directory in directories:
if is_converged("{}/{}".format(directory, subdirectory)):
os.chdir("{}/{}".format(directory, subdirectory))
band_structure = Vasprun("vasprun.xml").get_band_structure()
band_gap = band_structure.get_band_gap()
# Vacuum level energy from LOCPOT.
locpot = Locpot.from_file("LOCPOT")
evac = max(locpot.get_average_along_axis(2))
try:
is_metal = False
is_direct = band_gap["direct"]
cbm = band_structure.get_cbm()
vbm = band_structure.get_vbm()
except AttributeError:
cbm = None
vbm = None
is_metal = True
is_direct = False
band_gaps[directory] = {"CBM": cbm, "VBM": vbm, "Direct": is_direct, "Metal": is_metal, "E_vac": evac}
os.chdir("../../")
ax = plt.figure(figsize=(16, 10)).gca()
x_max = len(band_gaps) * 1.315
ax.set_xlim(0, x_max)
# Rectangle representing band edges of water.
ax.add_patch(plt.Rectangle((0, -5.67), height=1.23, width=len(band_gaps), facecolor="#00cc99", linewidth=0))
ax.text(len(band_gaps) * 1.01, -4.44, r"$\mathrm{H+/H_2}$", size=20, verticalalignment="center")
ax.text(len(band_gaps) * 1.01, -5.67, r"$\mathrm{O_2/H_2O}$", size=20, verticalalignment="center")
x_ticklabels = []
y_min = -8
i = 0
# Nothing but lies.
are_directs, are_indirects, are_metals = False, False, False
for compound in [cpd for cpd in directories if cpd in band_gaps]:
x_ticklabels.append(compound)
# Plot all energies relative to their vacuum level.
evac = band_gaps[compound]["E_vac"]
if band_gaps[compound]["Metal"]:
cbm = -8
vbm = -2
else:
cbm = band_gaps[compound]["CBM"]["energy"] - evac
vbm = band_gaps[compound]["VBM"]["energy"] - evac
# Add a box around direct gap compounds to distinguish them.
if band_gaps[compound]["Direct"]:
are_directs = True
linewidth = 5
elif not band_gaps[compound]["Metal"]:
are_indirects = True
linewidth = 0
# Metals are grey.
if band_gaps[compound]["Metal"]:
are_metals = True
linewidth = 0
color_code = "#404040"
else:
color_code = "#002b80"
# CBM
ax.add_patch(
plt.Rectangle(
(i, cbm), height=-cbm, width=0.8, facecolor=color_code, linewidth=linewidth, edgecolor="#e68a00"
)
)
# VBM
ax.add_patch(
plt.Rectangle(
(i, y_min),
height=(vbm - y_min),
width=0.8,
facecolor=color_code,
linewidth=linewidth,
edgecolor="#e68a00",
)
)
i += 1
ax.set_ylim(y_min, -2)
# Set tick labels
ax.set_xticks([n + 0.4 for n in range(i)])
ax.set_xticklabels(x_ticklabels, family="serif", size=20, rotation=60)
ax.set_yticklabels(ax.get_yticks(), family="serif", size=20)
# Add a legend
height = y_min
if are_directs:
ax.add_patch(
plt.Rectangle(
(i * 1.165, height),
width=i * 0.15,
height=(-y_min * 0.1),
facecolor="#002b80",
edgecolor="#e68a00",
linewidth=5,
)
)
ax.text(
i * 1.24,
height - y_min * 0.05,
"Direct",
family="serif",
color="w",
size=20,
horizontalalignment="center",
verticalalignment="center",
)
height -= y_min * 0.15
if are_indirects:
ax.add_patch(
plt.Rectangle((i * 1.165, height), width=i * 0.15, height=(-y_min * 0.1), facecolor="#002b80", linewidth=0)
)
ax.text(
i * 1.24,
height - y_min * 0.05,
"Indirect",
family="serif",
size=20,
color="w",
horizontalalignment="center",
verticalalignment="center",
)
height -= y_min * 0.15
if are_metals:
ax.add_patch(
plt.Rectangle((i * 1.165, height), width=i * 0.15, height=(-y_min * 0.1), facecolor="#404040", linewidth=0)
)
ax.text(
i * 1.24,
height - y_min * 0.05,
"Metal",
family="serif",
size=20,
color="w",
horizontalalignment="center",
verticalalignment="center",
)
# Who needs axes?
ax.spines["top"].set_visible(False)
ax.spines["right"].set_visible(False)
ax.spines["bottom"].set_visible(False)
ax.spines["left"].set_visible(False)
ax.yaxis.set_ticks_position("left")
ax.xaxis.set_ticks_position("bottom")
ax.set_ylabel("eV", family="serif", size=24)
plt.savefig("band_alignments.{}".format(fmt), transparent=True)
plt.close()
competing_species = get_competing_species(directories)
relax_competing_species(competing_species)
for directory in directories:
os.chdir(directory)
relax()
os.chdir('../')
loop = True
while loop:
print('>> Checking convergence')
finished_2d, finished_3d = [], []
for directory in directories:
if is_converged(directory):
finished_2d.append(directory)
for directory in competing_species:
if is_converged('all_competitors/{}'.format(directory[0])):
finished_3d.append(directory[0])
if len(finished_2d + finished_3d) == len(
directories + competing_species):
print('>> Plotting hull distances')
plot_hull_distances(get_hull_distances(finished_2d))
loop = False
else:
print('>> Not all directories converged ({}/{})'.format(
len(finished_2d + finished_3d), len(
directories + competing_species)))
converged[directory] = False
run_friction_calculations()
os.chdir('../')
loop = True
while loop:
time.sleep(INTERVAL)
loop = False
for directory in directories:
os.chdir(directory)
converged[directory] = True
for subdirectory in [
dir for dir in os.listdir(os.getcwd())
if os.path.isdir(dir)
]:
if not is_converged(subdirectory):
converged[directory] = False
break
if not converged[directory]:
print('>> Not all directories converged')
loop = True
print('>> Plotting gamma surface for {}'.format(directory))
plot_gamma_surface()
os.chdir('../')
