class TestPourbaixPlotter(unittest.TestCase):
def setUp(self):
warnings.simplefilter("ignore")
module_dir = os.path.dirname(os.path.abspath(__file__))
(elements, entries) = PourbaixEntryIO.from_csv(
os.path.join(module_dir, "test_entries.csv"))
self.num_simplices = {
"Zn(s)": 7,
"ZnO2(s)": 7,
"Zn[2+]": 4,
"ZnO2[2-]": 4,
"ZnHO2[-]": 4
}
self.e_above_hull_test = {"ZnHO[+]": 0.0693, "ZnO(aq)": 0.0624}
self.decomp_test = {
"ZnHO[+]": {
"ZnO(s)": 0.5,
"Zn[2+]": 0.5
},
"ZnO(aq)": {
"ZnO(s)": 1.0
}
}
self.pd = PourbaixDiagram(entries)
self.multi_data = loadfn(os.path.join(test_dir, 'multicomp_pbx.json'))
self.plotter = PourbaixPlotter(self.pd)
def tearDown(self):
warnings.resetwarnings()
def test_plot_pourbaix(self):
# Default limits
plt = self.plotter.get_pourbaix_plot()
# Non-standard limits
plt = self.plotter.get_pourbaix_plot(limits=[[-5, 4], [-2, 2]])
# Try 3-D plot
plot_3d = self.plotter._get_plot()
plot_3d_unstable = self.plotter._get_plot(label_unstable=True)
plt.close()
plot_3d.close()
plot_3d_unstable.close()
def test_plot_entry_stability(self):
entry = self.pd.all_entries[0]
plt = self.plotter.plot_entry_stability(entry,
limits=[[-2, 14], [-3, 3]])
# binary system
pd_binary = PourbaixDiagram(self.multi_data['binary'],
comp_dict={
"Ag": 0.5,
"Te": 0.5
})
binary_plotter = PourbaixPlotter(pd_binary)
test_entry = pd_binary._unprocessed_entries[0]
plt = binary_plotter.plot_entry_stability(test_entry)
plt.close()
class TestPourbaixPlotter(unittest.TestCase):
def setUp(self):
module_dir = os.path.dirname(os.path.abspath(__file__))
(elements, entries) = PourbaixEntryIO.from_csv(
os.path.join(module_dir, "test_entries.csv"))
self.num_simplices = {
"Zn(s)": 7,
"ZnO2(s)": 7,
"Zn[2+]": 4,
"ZnO2[2-]": 4,
"ZnHO2[-]": 4
}
self.e_above_hull_test = {"ZnHO[+]": 0.0693, "ZnO(aq)": 0.0624}
self.decomp_test = {
"ZnHO[+]": {
"ZnO(s)": 0.5,
"Zn[2+]": 0.5
},
"ZnO(aq)": {
"ZnO(s)": 1.0
}
}
self.pd = PourbaixDiagram(entries)
self.plotter = PourbaixPlotter(self.pd)
def test_plot_pourbaix(self):
plt = self.plotter.get_pourbaix_plot(limits=[[-2, 14], [-3, 3]])
def test_get_entry_stability(self):
entry = self.pd.all_entries[0]
plt = self.plotter.plot_entry_stability(entry,
limits=[[-2, 14], [-3, 3]])
class TestPourbaixPlotter(unittest.TestCase):
def setUp(self):
warnings.simplefilter("ignore")
module_dir = os.path.dirname(os.path.abspath(__file__))
(elements, entries) = PourbaixEntryIO.from_csv(os.path.join(module_dir,
"test_entries.csv"))
self.num_simplices = {"Zn(s)": 7, "ZnO2(s)": 7, "Zn[2+]": 4, "ZnO2[2-]": 4, "ZnHO2[-]": 4}
self.e_above_hull_test = {"ZnHO[+]": 0.0693, "ZnO(aq)": 0.0624}
self.decomp_test = {"ZnHO[+]": {"ZnO(s)": 0.5, "Zn[2+]": 0.5}, "ZnO(aq)": {"ZnO(s)": 1.0}}
self.pd = PourbaixDiagram(entries)
self.multi_data = loadfn(os.path.join(test_dir, 'multicomp_pbx.json'))
self.plotter = PourbaixPlotter(self.pd)
def tearDown(self):
warnings.resetwarnings()
def test_plot_pourbaix(self):
# Default limits
plt = self.plotter.get_pourbaix_plot()
# Non-standard limits
plt = self.plotter.get_pourbaix_plot(limits=[[-5, 4], [-2, 2]])
# Try 3-D plot
plot_3d = self.plotter._get_plot()
plot_3d_unstable = self.plotter._get_plot(label_unstable=True)
plt.close()
plot_3d.close()
plot_3d_unstable.close()
def test_plot_entry_stability(self):
entry = self.pd.all_entries[0]
plt = self.plotter.plot_entry_stability(entry, limits=[[-2, 14], [-3, 3]])
# binary system
pd_binary = PourbaixDiagram(self.multi_data['binary'],
comp_dict = {"Ag": 0.5, "Te": 0.5})
binary_plotter = PourbaixPlotter(pd_binary)
test_entry = pd_binary._unprocessed_entries[0]
plt = binary_plotter.plot_entry_stability(test_entry)
plt.close()
def plot_pourbaix_diagram(metastability=0.0,
ion_concentration=1e-6,
fmt='pdf'):
"""
Creates a Pourbaix diagram for the material in the cwd.
Args:
metastability (float): desired metastable tolerance energy
(meV/atom). <~50 is generally a sensible range to use.
ion_concentration (float): in mol/kg. Sensible values are
generally between 1e-8 and 1.
fmt (str): matplotlib format style. Check the matplotlib
docs for options.
"""
# Create a ComputedEntry object for the 2D material.
composition = Structure.from_file('POSCAR').composition
energy = Vasprun('vasprun.xml').final_energy
cmpd = ComputedEntry(composition, energy)
# Define the chemsys that describes the 2D compound.
chemsys = ['O', 'H'] + [
elt.symbol
for elt in composition.elements if elt.symbol not in ['O', 'H']
]
# Pick out the ions pertaining to the 2D compound.
ion_dict = dict()
for elt in chemsys:
if elt not in ['O', 'H'] and ION_FORMATION_ENERGIES[elt]:
ion_dict.update(ION_FORMATION_ENERGIES[elt])
elements = [Element(elt) for elt in chemsys if elt not in ['O', 'H']]
# Add "correction" for metastability
cmpd.correction -= float(cmpd.composition.num_atoms)\
* float(metastability) / 1000.0
# Calculate formation energy of the compound from its end
# members
form_energy = cmpd.energy
for elt in composition.as_dict():
form_energy -= CHEMICAL_POTENTIALS[elt] * cmpd.composition[elt]
# Convert the compound entry to a pourbaix entry.
# Default concentration for solid entries = 1
pbx_cmpd = PourbaixEntry(cmpd)
pbx_cmpd.g0_replace(form_energy)
pbx_cmpd.reduced_entry()
# Add corrected ionic entries to the pourbaix diagram
# dft corrections for experimental ionic energies:
# Persson et.al PHYSICAL REVIEW B 85, 235438 (2012)
pbx_ion_entries = list()
# Get PourbaixEntry corresponding to each ion.
# Default concentration for ionic entries = 1e-6
# ion_energy = ion_exp_energy + ion_correction * factor
# where factor = fraction of element el in the ionic entry
# compared to the reference entry
for elt in elements:
for key in ion_dict:
comp = Ion.from_formula(key)
if comp.composition[elt] != 0:
factor = comp.composition[elt]
energy = ion_dict[key]
pbx_entry_ion = PourbaixEntry(IonEntry(comp, energy))
pbx_entry_ion.correction = (ION_CORRECTIONS[elt.symbol] *
factor)
pbx_entry_ion.conc = ion_concentration
pbx_entry_ion.name = key
pbx_ion_entries.append(pbx_entry_ion)
# Generate and plot Pourbaix diagram
# Each bulk solid/ion has a free energy g of the form:
# g = g0_ref + 0.0591 * log10(conc) - nO * mu_H2O +
# (nH - 2nO) * pH + phi * (-nH + 2nO + q)
all_entries = [pbx_cmpd] + pbx_ion_entries
pourbaix = PourbaixDiagram(all_entries)
# Analysis features
# panalyzer = PourbaixAnalyzer(pourbaix)
# instability = panalyzer.get_e_above_hull(pbx_cmpd)
plotter = PourbaixPlotter(pourbaix)
plot = plotter.get_pourbaix_plot(limits=[[0, 14], [-2, 2]],
label_domains=True)
fig = plot.gcf()
ax1 = fig.gca()
# Add coloring to highlight the stability region for the 2D
# material, if one exists.
stable_entries = plotter.pourbaix_plot_data(limits=[[0, 14], [-2, 2]])[0]
for entry in stable_entries:
if entry == pbx_cmpd:
col = plt.cm.Blues(0)
else:
col = plt.cm.rainbow(
float(ION_COLORS[entry.composition.reduced_formula]))
vertices = plotter.domain_vertices(entry)
patch = Polygon(vertices, closed=True, fill=True, color=col)
ax1.add_patch(patch)
fig.set_size_inches((11.5, 9))
plot.tight_layout(pad=1.09)
# Save plot
if metastability:
plot.suptitle('Metastable Tolerance ='
' {} meV/atom'.format(metastability),
fontsize=20)
plot.savefig('{}_{}.{}'.format(composition.reduced_formula,
ion_concentration, fmt),
transparent=True)
else:
plot.savefig('{}_{}.{}'.format(composition.reduced_formula,
ion_concentration, fmt),
transparent=True)
plot.close()
def plot_pourbaix_diagram(metastability=0.0, ion_concentration=1e-6, fmt='pdf'):
"""
Creates a Pourbaix diagram for the material in the cwd.
Args:
metastability (float): desired metastable tolerance energy
(meV/atom). <~50 is generally a sensible range to use.
ion_concentration (float): in mol/kg. Sensible values are
generally between 1e-8 and 1.
fmt (str): matplotlib format style. Check the matplotlib
docs for options.
"""
# Create a ComputedEntry object for the 2D material.
composition = Structure.from_file('POSCAR').composition
energy = Vasprun('vasprun.xml').final_energy
cmpd = ComputedEntry(composition, energy)
# Define the chemsys that describes the 2D compound.
chemsys = ['O', 'H'] + [elt.symbol for elt in composition.elements
if elt.symbol not in ['O', 'H']]
# Experimental ionic energies
# See ions.yaml for ion formation energies and references.
exp_dict = ION_DATA['ExpFormEnergy']
ion_correction = ION_DATA['IonCorrection']
# Pick out the ions pertaining to the 2D compound.
ion_dict = dict()
for elt in chemsys:
if elt not in ['O', 'H'] and exp_dict[elt]:
ion_dict.update(exp_dict[elt])
elements = [Element(elt) for elt in chemsys if elt not in ['O', 'H']]
# Add "correction" for metastability
cmpd.correction -= float(cmpd.composition.num_atoms)\
* float(metastability) / 1000.0
# Calculate formation energy of the compound from its end
# members
form_energy = cmpd.energy
for elt in composition.as_dict():
form_energy -= END_MEMBERS[elt] * cmpd.composition[elt]
# Convert the compound entry to a pourbaix entry.
# Default concentration for solid entries = 1
pbx_cmpd = PourbaixEntry(cmpd)
pbx_cmpd.g0_replace(form_energy)
pbx_cmpd.reduced_entry()
# Add corrected ionic entries to the pourbaix diagram
# dft corrections for experimental ionic energies:
# Persson et.al PHYSICAL REVIEW B 85, 235438 (2012)
pbx_ion_entries = list()
# Get PourbaixEntry corresponding to each ion.
# Default concentration for ionic entries = 1e-6
# ion_energy = ion_exp_energy + ion_correction * factor
# where factor = fraction of element el in the ionic entry
# compared to the reference entry
for elt in elements:
for key in ion_dict:
comp = Ion.from_formula(key)
if comp.composition[elt] != 0:
factor = comp.composition[elt]
energy = ion_dict[key]
pbx_entry_ion = PourbaixEntry(IonEntry(comp, energy))
pbx_entry_ion.correction = ion_correction[elt.symbol]\
* factor
pbx_entry_ion.conc = ion_concentration
pbx_entry_ion.name = key
pbx_ion_entries.append(pbx_entry_ion)
# Generate and plot Pourbaix diagram
# Each bulk solid/ion has a free energy g of the form:
# g = g0_ref + 0.0591 * log10(conc) - nO * mu_H2O +
# (nH - 2nO) * pH + phi * (-nH + 2nO + q)
all_entries = [pbx_cmpd] + pbx_ion_entries
pourbaix = PourbaixDiagram(all_entries)
# Analysis features
panalyzer = PourbaixAnalyzer(pourbaix)
# instability = panalyzer.get_e_above_hull(pbx_cmpd)
plotter = PourbaixPlotter(pourbaix)
plot = plotter.get_pourbaix_plot(limits=[[0, 14], [-2, 2]],
label_domains=True)
fig = plot.gcf()
ax1 = fig.gca()
# Add coloring to highlight the stability region for the 2D
# material, if one exists.
stable_entries = plotter.pourbaix_plot_data(
limits=[[0, 14], [-2, 2]])[0]
for entry in stable_entries:
if entry == pbx_cmpd:
col = plt.cm.Blues(0)
else:
col = plt.cm.rainbow(float(
ION_COLORS[entry.composition.reduced_formula]))
vertices = plotter.domain_vertices(entry)
patch = Polygon(vertices, closed=True, fill=True, color=col)
ax1.add_patch(patch)
fig.set_size_inches((11.5, 9))
plot.tight_layout(pad=1.09)
# Save plot
if metastability:
plot.suptitle('Metastable Tolerance ='
' {} meV/atom'.format(metastability),
fontsize=20)
plot.savefig('{}_{}.{}'.format(
composition.reduced_formula, ion_concentration, fmt),
transparent=True)
else:
plot.savefig('{}_{}.{}'.format(composition.reduced_formula,
ion_concentration, fmt),
transparent=True)
plot.close()