def get_pourbaix_entries(self, chemsys):
"""
A helper function to get all entries necessary to generate
a pourbaix diagram from the rest interface.
Args:
chemsys ([str]): A list of elements comprising the chemical
system, e.g. ['Li', 'Fe']
"""
from pymatgen.analysis.pourbaix.entry import PourbaixEntry, IonEntry
from pymatgen.analysis.phase_diagram import PhaseDiagram
from pymatgen.core.ion import Ion
from pymatgen.entries.compatibility import\
MaterialsProjectAqueousCompatibility
chemsys = list(set(chemsys + ['O', 'H']))
entries = self.get_entries_in_chemsys(chemsys,
property_data=['e_above_hull'],
compatible_only=False)
compat = MaterialsProjectAqueousCompatibility("Advanced")
entries = compat.process_entries(entries)
solid_pd = PhaseDiagram(
entries) # Need this to get ion formation energy
url = '/pourbaix_diagram/reference_data/' + '-'.join(chemsys)
ion_data = self._make_request(url)
pbx_entries = []
for entry in entries:
if not set(entry.composition.elements)\
<= {Element('H'), Element('O')}:
pbx_entry = PourbaixEntry(entry)
pbx_entry.g0_replace(solid_pd.get_form_energy(entry))
pbx_entry.reduced_entry()
pbx_entries.append(pbx_entry)
# position the ion energies relative to most stable reference state
for n, i_d in enumerate(ion_data):
ion_entry = IonEntry(Ion.from_formula(i_d['Name']), i_d['Energy'])
refs = [
e for e in entries
if e.composition.reduced_formula == i_d['Reference Solid']
]
if not refs:
raise ValueError("Reference solid not contained in entry list")
stable_ref = sorted(refs, key=lambda x: x.data['e_above_hull'])[0]
rf = stable_ref.composition.get_reduced_composition_and_factor()[1]
solid_diff = solid_pd.get_form_energy(stable_ref)\
- i_d['Reference solid energy'] * rf
elt = i_d['Major_Elements'][0]
correction_factor = ion_entry.ion.composition[elt]\
/ stable_ref.composition[elt]
correction = solid_diff * correction_factor
pbx_entries.append(
PourbaixEntry(ion_entry, correction, 'ion-{}'.format(n)))
return pbx_entries
def get_pourbaix_entries(self, chemsys):
"""
A helper function to get all entries necessary to generate
a pourbaix diagram from the rest interface.
Args:
chemsys ([str]): A list of elements comprising the chemical
system, e.g. ['Li', 'Fe']
"""
from pymatgen.analysis.pourbaix.entry import PourbaixEntry, IonEntry
from pymatgen.analysis.phase_diagram import PhaseDiagram
from pymatgen.core.ion import Ion
from pymatgen.entries.compatibility import\
MaterialsProjectAqueousCompatibility
chemsys = list(set(chemsys + ['O', 'H']))
entries = self.get_entries_in_chemsys(
chemsys, property_data=['e_above_hull'], compatible_only=False)
compat = MaterialsProjectAqueousCompatibility("Advanced")
entries = compat.process_entries(entries)
solid_pd = PhaseDiagram(entries) # Need this to get ion formation energy
url = '/pourbaix_diagram/reference_data/' + '-'.join(chemsys)
ion_data = self._make_request(url)
pbx_entries = []
for entry in entries:
if not set(entry.composition.elements)\
<= {Element('H'), Element('O')}:
pbx_entry = PourbaixEntry(entry)
pbx_entry.g0_replace(solid_pd.get_form_energy(entry))
pbx_entry.reduced_entry()
pbx_entries.append(pbx_entry)
# position the ion energies relative to most stable reference state
for n, i_d in enumerate(ion_data):
ion_entry = IonEntry(Ion.from_formula(i_d['Name']), i_d['Energy'])
refs = [e for e in entries
if e.composition.reduced_formula == i_d['Reference Solid']]
if not refs:
raise ValueError("Reference solid not contained in entry list")
stable_ref = sorted(refs, key=lambda x: x.data['e_above_hull'])[0]
rf = stable_ref.composition.get_reduced_composition_and_factor()[1]
solid_diff = solid_pd.get_form_energy(stable_ref)\
- i_d['Reference solid energy'] * rf
elt = i_d['Major_Elements'][0]
correction_factor = ion_entry.ion.composition[elt]\
/ stable_ref.composition[elt]
correction = solid_diff * correction_factor
pbx_entries.append(PourbaixEntry(ion_entry, correction,
'ion-{}'.format(n)))
return pbx_entries
def form_e(stable_solids_minus_h2o, entries_aqcorr, gas_gibbs=True):
"""
Calculate the formation energy for the entries in stable_solids_minus_h2o
Reduce by stoicheometric factor if applicable (ex. Fe4O4)
Args:
stable_solids_minus_h2o: list of stable solids without O2, H2O, H2, and
H2O2 (from stable_entr)
entries_aqcorr: entries list before being modified by stable_entr
"""
#| - form_e
#| - Imported Modules
from pymatgen.analysis.pourbaix.entry import PourbaixEntry
from pymatgen.phasediagram.maker import PhaseDiagram
from entry_methods import base_atom
from energy_scheme import ref_atoms_dict
#__|
ref_atom_energies = ref_atoms_dict()
e_o = ref_atom_energies['e_o']
e_h = ref_atom_energies['e_h']
pd = PhaseDiagram(entries_aqcorr)
base_at = base_atom(stable_solids_minus_h2o)
d = {}
for i in stable_solids_minus_h2o:
if i.name in base_at:
d[i.name] = i.energy_per_atom
def form_energy(entry, solid_ref_energy_dict, gas_gibbs=True):
"""
Calculates the formation energy of an entry relative to the VASP
energies of the reference atoms. Gibbs/entropy corrections for the gas
phase are optionable
Args:
entry: Entry whose formation energy will be calculated
solid_ref_energy_dict: Dictionary of reference atom energies
gas_gibbs: Whether the gas phase reference atoms will have an
entropic correction
"""
if gas_gibbs==True:
ref_dict = {}
ref_dict['O'] = e_o-0.3167
ref_dict['H'] = e_h-0.36218
elif gas_gibbs==False:
ref_dict = {}
ref_dict['O'] = e_o
ref_dict['H'] = e_h
z = ref_dict.copy()
z.update(solid_ref_energy_dict)
ref_dict = z
elem_dict = entry.composition.get_el_amt_dict()
entry_e = entry.energy
for elem in entry.composition.elements:
elem_num = elem_dict[elem.symbol]
entry_e = entry_e - elem_num*ref_dict[elem.symbol]
return entry_e
pbx_solid_entries = []
for entry in stable_solids_minus_h2o:
pbx_entry = PourbaixEntry(entry)
pbx_entry.g0_replace(form_energy(entry, d, gas_gibbs=gas_gibbs)) #Replace E with form E relative to ref elements
# pbx_entry.g0_replace(pd.get_form_energy(entry)) #Replace E with form E relative to ref elements
pbx_entry.reduced_entry() #Reduces parameters by stoich factor (ex. Li2O2 -> LiO)
pbx_solid_entries.append(pbx_entry)
return pbx_solid_entries
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']]
# 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
total = sum([composition[el] for el in elements])
comp_dict = {el.symbol: composition[el]/total for el in elements}
pourbaix_diagram = PourbaixDiagram(all_entries, comp_dict=comp_dict)
plotter = PourbaixPlotter(pourbaix_diagram)
# Plotting details...
font = "serif"
fig = plt.figure(figsize=(14, 9))
ax1 = fig.gca()
ax1.set_xlim([0, 14])
ax1.set_xticklabels([int(t) for t in ax1.get_xticks()], fontname=font,
fontsize=18)
ax1.set_ylim(-2, 2)
ax1.set_yticklabels(ax1.get_yticks(), fontname=font, fontsize=18)
ax1.set_xlabel("pH", fontname=font, fontsize=18)
ax1.set_ylabel("Potential vs. SHE (V)", fontname=font, fontsize=18)
# Outline water's stability range.
ax1.plot([0, 14], [0, -0.829], color="gray", linestyle="--", alpha=0.7,
linewidth=2)
ax1.plot([0, 14], [1.229, 0.401], color="gray", linestyle="--", alpha=0.7,
linewidth=2)
stable_entries = plotter.pourbaix_plot_data(
limits=[[0, 14], [-2, 2]])[0]
# Add coloring.
colors = sb.color_palette("Set2", len(stable_entries))
i = 0
for entry in stable_entries:
col = colors[i]
i += 1
vertices = plotter.domain_vertices(entry)
center_x = sum([v[0] for v in vertices])/len(vertices)
center_y = sum([v[1] for v in vertices])/len(vertices)
patch = Polygon(vertices, closed=True, fill=True, facecolor=col,
linewidth=2, edgecolor="w")
ax1.text(center_x, center_y, plotter.print_name(entry),
verticalalignment="center", horizontalalignment="center",
fontname=font, fontsize=18)
ax1.add_patch(patch)
plt.savefig("pourbaix.{}".format(fmt))
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']]
# 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()
