def get_barrier_all(self) -> Dict[str, Dict[str, str]]:
''' Get barrier heights for all rxn_names and facetpaths
Returns
-------
ts_ener : Dict[str,Dict[str,str]]
a dictionary with all barrier heights (kj/mol)
in a format like below
>>> ts_ener = {'Cu_111_OH_O+H':
{'TS_00': '155.27', 'TS_01': '157.97'}}
'''
ts_ener = {}
for facetpath, slab_path in zip(self.facetpaths, self.slab_paths):
minima_path = os.path.join(facetpath, 'minima')
for rxn in self.reactions:
r_name_list, p_name_list = IO.get_reactants_and_products(rxn)
rxn_name = IO.get_rxn_name(rxn)
ts_path = os.path.join(self.current_dir, facetpath, rxn_name,
'TS_estimate_unique')
ts_ener[facetpath + '_' + rxn_name] = self.get_barrier(
minima_path, ts_path, facetpath, r_name_list, p_name_list,
slab_path)
return ts_ener
def prepare_ts_estimate(self, rxn: Dict[str, str], scfactor: float,
scfactor_surface: float, pytemplate_xtb: str,
species_list: List[str],
reacting_atoms: Dict[str, int], metal_atom: str,
scaled1: bool, scaled2: bool) -> None:
''' Prepare TS estimates for subsequent xTB calculations
Parameters
___________
rxn : dict(yaml[str:str])
a dictionary with info about the paricular reaction. This can be
view as a splitted many reaction .yaml file to a single reaction
.yaml file
scfator : float
a scaling factor to scale a bond distance between
atoms taking part in the reaction
e.g. 1.4
scfactor_surface : float
a scaling factor to scale the target bond distance, i.e.
the average distance between adsorbed atom and the nearest
surface atom. Helpful e.g. when H is far away form the surface
in TS, whereas for minima it is close to the surface
e.g. 1.0
pytemplate_xtb : python script
a template file for penalty function minimization job
species_list : List[str]
a list of species which atoms take part in the reaction,
i.e. for ['CO2'] ['C'] is taking part in reaction
e.g. ['O', 'H'] or ['CO2', 'H']
reacting_atoms : Dict[str, int]
keys are sybols of atoms that takes part in reaction whereas,
values are their indicies
metal_atom : str
a checmical symbol for the surface atoms (only metallic surfaces
are allowed)
scaled1 : bool
specify whether use the optional scfactor_surface
for the species 1 (sp1)
scaled2 : bool
specify whether use the optional scfactor_surface
for the species 2 (sp2)
'''
r_name_list, p_name_list = IO.get_reactants_and_products(rxn)
rxn_name = IO.get_rxn_name(rxn)
ts_estimate_path = os.path.join(self.creation_dir, self.facetpath,
rxn_name, self.ts_estimate_dir)
self.TS_placer(ts_estimate_path, scfactor, rxn, rxn_name, r_name_list,
p_name_list, reacting_atoms)
self.filtered_out_equiv_ts_estimates(ts_estimate_path, rxn_name)
self.set_up_penalty_xtb(ts_estimate_path, pytemplate_xtb, species_list,
reacting_atoms, metal_atom, scaled1,
scfactor_surface)
def get_reaction_energies_all(self) -> None:
''' Get reactiom energy (kj/mol) for all facetpaths and reactions
Returns
-------
reaction_energies : Dict[str:float]
a dictionary with reaction energies for a given facetpath and
rxn_name, e.g.
>>> reaction_energies = {'Cu_111_OH_O+H': 70.81}
'''
reaction_energies = {}
for facetpath, slab_path in zip(self.facetpaths, self.slab_paths):
minima_path = os.path.join(facetpath, 'minima')
for rxn in self.reactions:
r_name_list, p_name_list = IO.get_reactants_and_products(rxn)
rxn_name = IO.get_rxn_name(rxn)
key = facetpath + '_' + rxn_name
reaction_energies[key] = float(
self.get_reaction_energy(minima_path, facetpath,
r_name_list, p_name_list,
slab_path))
return reaction_energies