#set pressures and temperature
model.parameters.T = 450
model.parameters.p_COgas = 1
model.parameters.p_O2gas = 1
#prepare initial state of system with all bridge sites covered by O
#for i in range(model.size[0]):
# for j in range(model.size[1]):
# model._put([i,j,0,model.lattice.ruo2_bridge], model.proclist.o)
#model._adjust_database()
#get TOF labels
tof_labels = model.get_tof_header().split(' ')
#get coverage labels
cov_labels = model.get_occupation_header().split(' ')
#Number of kmc steps taken in each sample
sample_step = 1e5
#Number of samples
N = 100
#prepare arrays for TOFs, coverages and kmc steps
tofs = np.zeros((N, len(tof_labels)))
covs = np.zeros((N, len(cov_labels)))
steps = np.zeros((N, 1))
#run model and save data
for i in range(N):
atoms = model.get_atoms(geometry=False)
from ase.all import view
#load model
model = KMC_Model(print_rates=False, banner=False)
#set pressures and temperature
model.parameters.T = 600
model.parameters.p_COgas = 1
model.parameters.p_O2gas = 1
#prepare random initial state of O-poisoned lattice (known steady-state solution)
#this ensures faster relaxation.
#get coverage labels, disregarding the empty species
Nsite_types = model.lattice.spuck
cov_labels = model.get_occupation_header().split(' ')[:-Nsite_types]
#define guess coverages
guess_coverages = [0.05, 0.05, 0.95, 0.95] #CO_br, CO_cus, O_br, O_cus
#dictionaries for converting to kmos variables
kmos_species = {'CO':model.proclist.co, 'O':model.proclist.o}
kmos_sites = {'bridge':model.lattice.ruo2_bridge, 'cus':model.lattice.ruo2_cus}
#available sites
sites_list = []
for i in range(model.size[0]):
for j in range(model.size[1]):
sites_list.append([i,j])
#convert coverages to occupations
from ase.all import view
#load model
model = KMC_Model(print_rates=False, banner=False)
#set pressures and temperature
model.parameters.T = 600
model.parameters.p_COgas = 1
model.parameters.p_O2gas = 1
#prepare random initial state of O-poisoned lattice (known steady-state solution)
#this ensures faster relaxation.
#get coverage labels, disregarding the empty species
Nsite_types = model.lattice.spuck
cov_labels = model.get_occupation_header().split(' ')[:-Nsite_types]
#define guess coverages
guess_coverages = [0.05, 0.05, 0.95, 0.95] #CO_br, CO_cus, O_br, O_cus
#dictionaries for converting to kmos variables
kmos_species = {'CO': model.proclist.co, 'O': model.proclist.o}
kmos_sites = {
'bridge': model.lattice.ruo2_bridge,
'cus': model.lattice.ruo2_cus
}
#available sites
sites_list = []
for i in range(model.size[0]):
for j in range(model.size[1]):
#set pressures and temperature
model.parameters.T = 450
model.parameters.p_COgas = 1
model.parameters.p_O2gas = 1
#prepare initial state of system with all bridge sites covered by O
#for i in range(model.size[0]):
# for j in range(model.size[1]):
# model._put([i,j,0,model.lattice.ruo2_bridge], model.proclist.o)
#model._adjust_database()
#get TOF labels
tof_labels = model.get_tof_header().split(' ')
#get coverage labels
cov_labels = model.get_occupation_header().split(' ')
#Number of kmc steps taken in each sample
sample_step = 1e5
#Number of samples
N = 100
#prepare arrays for TOFs, coverages and kmc steps
tofs = np.zeros((N,len(tof_labels)))
covs = np.zeros((N,len(cov_labels)))
steps = np.zeros((N,1))
#run model and save data
for i in range(N):
atoms = model.get_atoms(geometry=False)
