#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)