def process(i,j,comp=0.5, heat_map_scale='Pt_ref', pt_oxid_V=0.6470339): """ Creates and analyzes a Pourbaix Diagram from two elements (they can be the same ex. Pt,Pt). Finds relevant entries, creates Pourbaix diagram, identifies stable phases, and calculates the stability of the phase Args: i: First element in the system j: Second element in the system comp: Composition loading of the two elements (default is 0.5) """ #| - - process entries = pd_entries(i.symbol,j.symbol) coord = phase_coord(entries, comp, prim_elem=i.symbol) filt1 = phase_filter(coord,'metallic') filt2 = phase_filter(coord,'metallic_metallic') filt = filt1 + filt2 # msp = most_stable_phase(filt,Pt_ref=True) if not filt: print 'heat_map.process - no phase present - '+i.symbol+'-'+j.symbol msp = [-1.5,'Pourbaix Entry placeholder'] # TEMP else: msp = most_stable_phase(filt, scale=heat_map_scale, pt_oxid_V=pt_oxid_V) # msp = most_stable_phase(filt,pH=10.5,scale=heat_map_scale) return msp
def ref_atoms(i,j, scale): """ TEMP """ #| - - ref_atoms ref_atoms = pd_entries(i.symbol,j.symbol) print ref_atoms #TEMP_PRINT return ref_atoms print ref_atoms # TEMP_PRINT
def process_alloy(i,
j): # Deprecated *******************************************
"""
Creates and analyzes a Pourbaix Diagram from two elements (they can be the
same ex. Pt,Pt). Finds relevant entries, removes the pure element entries,
for each alloy removes all other alloys and analyzes stability of all
forced alloy phases. Returns the the most highest performing forced alloy
phase.
Args:
i: First element in the system
j: Second element in the system
"""
# | - - process_alloy
entries = pd_entries(i.symbol, j.symbol)
# entries = pure_atoms_remove(entries)
alloy_entr = alloy_entries(entries)
if not alloy_entr:
print 'heat map - no alloy entries'
non_alloy = process(i, j)
return non_alloy
base_atoms = base_atom(entries)
alloy_performance_lst = []
for alloy in alloy_entr:
entries_0 = entries[:]
comp = alloy.composition \
.fractional_composition.get_atomic_fraction(base_atoms[0])
for alloy_0 in alloy_entr:
if not alloy_0 == alloy: entries_0.remove(alloy_0)
coord = phase_coord(entries_0, comp)
filt1 = phase_filter(coord, 'metallic')
filt2 = phase_filter(coord, 'metallic_metallic')
filt = filt1 + filt2
try:
alloy_performance_lst.append(
most_stable_phase(filt, scale='Pt_ref'))
except:
pass
alloy_performance_lst.sort(key=lambda x: x[0], reverse=True)
# NOTE This sort will not work when the performance criteria is distance
# from the ORR line (which needs to be as small as possible)
try:
best_alloy = alloy_performance_lst[0]
except:
best_alloy = [-1, 'placeholder'] #NOTE Make this better
return best_alloy
def oxidation_dissolution_product_0(i, j, scale):
"""
Creates Pourbaix Diagrams for single or binary systems
"""
#| - - oxidation_dissolution_product_0
# from pourdiag import pd_entries
from pymatgen.analysis.pourbaix.maker import PourbaixDiagram
from pymatgen.analysis.pourbaix.plotter import PourbaixPlotter
from pd_screen_tools import phase_coord, phase_filter
from stability_crit import most_stable_phase, oxidation_dissolution_product
elem0 = i.symbol; elem1 = j.symbol
mat_co_0 = 0.50 # Composition of 1st entry in elem_sys
entr = pd_entries(elem0,elem1)
pourbaix = PourbaixDiagram(entr,{elem0: mat_co_0,elem1: 1-mat_co_0})
plotter = PourbaixPlotter(pourbaix)
coord = phase_coord(entr,mat_co_0)
filt1 = phase_filter(coord,'metallic')
filt2 = phase_filter(coord,'metallic_metallic')
filt = filt1 + filt2
msp = most_stable_phase(filt,scale='RHE')
tmp = oxidation_dissolution_product(coord,msp)
if 'Ion' in tmp:
entry_lst = 'dis'
else:
entry_lst = 'oxi'
"""
entry_lst = ''
i_cnt = 0
for i in tmp:
entry_lst = str(entry_lst)+'\n'+str(i)
if i_cnt==0:
entry_lst = entry_lst[1:]
i_cnt=i_cnt+1
"""
return entry_lst
def process_alloy(i,j): # Deprecated ******************************************* """ Creates and analyzes a Pourbaix Diagram from two elements (they can be the same ex. Pt,Pt). Finds relevant entries, removes the pure element entries, for each alloy removes all other alloys and analyzes stability of all forced alloy phases. Returns the the most highest performing forced alloy phase. Args: i: First element in the system j: Second element in the system """ #| - - process_alloy entries = pd_entries(i.symbol,j.symbol) # entries = pure_atoms_remove(entries) alloy_entr = alloy_entries(entries) if not alloy_entr: print 'heat map - no alloy entries' non_alloy = process(i,j) return non_alloy base_atoms = base_atom(entries) alloy_performance_lst = [] for alloy in alloy_entr: entries_0 = entries[:] comp = alloy.composition \ .fractional_composition.get_atomic_fraction(base_atoms[0]) for alloy_0 in alloy_entr: if not alloy_0 == alloy: entries_0.remove(alloy_0) coord = phase_coord(entries_0,comp) filt1 = phase_filter(coord,'metallic') filt2 = phase_filter(coord,'metallic_metallic') filt = filt1 + filt2 try: alloy_performance_lst.append(most_stable_phase(filt, scale='Pt_ref')) except: pass