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rateConstants_barrierless.py
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import os
import sys, math, time
from array import array
import csv
import numpy
import math
import scipy.optimize as optimization
def get_barrierless_reactions(pathCSV, fileCSV, pathTS):
ifile = open(os.path.join(pathCSV,fileCSV), "r")
reader = csv.reader(ifile)
rownum = 0
TS_list = []
reactions_list = []
symmetry = []
for row in reader:
if rownum < 3:
pass
else:
reactants,products = row[0].split('=')
species = reactants.split('+') + products.split('+')
TS = "-p-".join(reactants.split('+')) + '-TS-' + "-p-".join(products.split('+'))
TS_list.append(TS)
reactions_list.append(row[0])
symmetry.append([row[0],row[1],row[2]])
rownum = rownum + 1
file_list = []
file_list_TS = []
for file_name in os.listdir(pathTS):
if file_name.endswith('.log'):
file_list_TS.append(file_name.split('.log')[0])
NO_TS_list = []
print '\nFiles missing from the TS folder'
for item in TS_list:
if item not in file_list_TS:
print item
NO_TS_list.append(item)
print '\n'
ifile.close()
return NO_TS_list
def read_minima_corrections(species_name, T, pathOutput):
file_name = pathOutput + "thermo-data-minima/" + species_name + "/" + species_name + ".data"
f = open(file_name, "r")
lines = f.readlines()
T = str(T) + ' '
for line in lines:
if line.startswith(T):
Hcorr = float(line.strip().split()[1])
Gcorr = float(line.strip().split()[2])
S = float(line.strip().split()[3])
return Hcorr, Gcorr, S
def cTST(T,reaction_name, species, conv_f, conv_b, SCF, pathOutput):
h = 6.62606957e-34
kB = 1.3806488e-23
R = 8.3144598
SCF_A = SCF[0]
SCF_B = SCF[1]
SCF_C = SCF[2]
SCF_D = SCF[3]
SCF_E = SCF[4]
SCF_F = SCF[5]
A = species[0]
B = species[1]
C = species[2]
D = species[3]
E = species[4]
F = species[5]
Hcorr_A, Gcorr_A, S_A = read_minima_corrections(A,T,pathOutput)
Hcorr_C, Gcorr_C, S_C = read_minima_corrections(C,T,pathOutput)
G_A = SCF_A + Gcorr_A
G_C = SCF_C + Gcorr_C
H_A = SCF_A + Hcorr_A
H_C = SCF_C + Hcorr_C
if conv_f == 1:
H_B = 0
G_B = 0
S_B = 0
else:
Hcorr_B, Gcorr_B, S_B = read_minima_corrections(B,T,pathOutput)
H_B = SCF_B + Hcorr_B
G_B = SCF_B + Gcorr_B
if conv_b == 1:
H_D = 0
G_D = 0
S_D = 0
H_E = 0
G_E = 0
S_E = 0
H_F = 0
G_F = 0
S_F = 0
elif conv_b == 1000:
Hcorr_D, Gcorr_D, S_D = read_minima_corrections(D,T,pathOutput)
H_D = SCF_D + Hcorr_D
G_D = SCF_D + Gcorr_D
H_E = 0
G_E = 0
S_E = 0
H_F = 0
G_F = 0
S_F = 0
elif conv_b == 1000000:
Hcorr_D, Gcorr_D, S_D = read_minima_corrections(D,T,pathOutput)
H_D = SCF_D + Hcorr_D
G_D = SCF_D + Gcorr_D
Hcorr_E, Gcorr_E, S_E = read_minima_corrections(E,T,pathOutput)
H_E = SCF_E + Hcorr_E
G_E = SCF_E + Gcorr_E
H_F = 0
G_F = 0
S_F = 0
else:
Hcorr_D, Gcorr_D, S_D = read_minima_corrections(D,T,pathOutput)
H_D = SCF_D + Hcorr_D
G_D = SCF_D + Gcorr_D
Hcorr_E, Gcorr_E, S_E = read_minima_corrections(E,T,pathOutput)
H_E = SCF_E + Hcorr_E
G_E = SCF_E + Gcorr_E
Hcorr_F, Gcorr_F, S_F = read_minima_corrections(F,T,pathOutput)
H_F = SCF_F + Hcorr_F
G_F = SCF_F + Gcorr_F
dHr = (H_C + H_D + H_E + H_F - H_A - H_B)*627.509*4184
dGr = (G_C + G_D + G_E + G_F - G_A - G_B)*627.509*4184
dSr = (S_C + S_D + S_E + S_F - S_A - S_B)
# modified for gas phase: C = P/RT (Standard state concentration with P = 1 atm reference)
if conv_f == 1:
n = 1
elif conv_f == 1000:
n = 2
if conv_b == 1:
m = 1
elif conv_b == 1000:
m = 2
elif conv_b == 1000000:
m = 3
elif conv_b == 1000000000:
m = 4
if dHr > 0:
dGf = dHr
dGb = 0
else:
dGf = 0
dGb = -dHr
kf = (kB*T/h)*((T*82.057)**(n-1))*math.exp(-dGf/(R*T))
kb = (kB*T/h)*((T*82.057)**(m-1))*math.exp(-dGb/(R*T))
return kf,kb, dGr/4184, dHr/4184, dSr
def calculate_rate_constants(pathTS,pathOutput,listBarrierless):
def read_minima_data(species_name, pathOutput):
species_name = species_name + ' '
file_name = pathOutput + "minima-SCF.txt"
f = open(file_name, "r")
lines = f.readlines()
for line in lines:
if line.startswith(species_name):
SCF = float(line.strip().split()[1])
ZPE = float(line.strip().split()[2])
return SCF, ZPE
for reaction_name in listBarrierless:
lines_to_write = []
temperatures = [300, 400, 500, 600, 700, 800, 900, 1000, 1200, 1400, 1600, 1800, 2000, 2200, 2400, 2600, 2800, 3000]
reactants,products = reaction_name.split('-TS-')
if len(reactants.split('-p-'))==1:
A = reactants
B = ''
conv_f = 1
SCF_A, ZPE_A = read_minima_data(A,pathOutput)
SCF_B, ZPE_B = 0, 0
if len(reactants.split('-p-'))==2:
A,B = reactants.split('-p-')
conv_f = 1000
SCF_A, ZPE_A = read_minima_data(A,pathOutput)
SCF_B, ZPE_B = read_minima_data(B,pathOutput)
if len(products.split('-p-'))==1:
C = products
D = ''
E = ''
F = ''
conv_b = 1
SCF_C, ZPE_C = read_minima_data(C,pathOutput)
SCF_D, ZPE_D = 0, 0
SCF_E, ZPE_E = 0, 0
SCF_F, ZPE_F = 0, 0
if len(products.split('-p-'))==2:
C,D = products.split('-p-')
E = ''
F = ''
conv_b = 1000
SCF_C, ZPE_C = read_minima_data(C,pathOutput)
SCF_D, ZPE_D = read_minima_data(D,pathOutput)
SCF_E, ZPE_E = 0, 0
SCF_F, ZPE_F = 0, 0
if len(products.split('-p-'))==3:
C,D,E = products.split('-p-')
F = ''
conv_b = 1000000
SCF_C, ZPE_C = read_minima_data(C,pathOutput)
SCF_D, ZPE_D = read_minima_data(D,pathOutput)
SCF_E, ZPE_E = read_minima_data(E,pathOutput)
SCF_F, ZPE_F = 0, 0
if len(products.split('-p-'))==4:
C,D,E,F = products.split('-p-')
conv_b = 1000000000
SCF_C, ZPE_C = read_minima_data(C,pathOutput)
SCF_D, ZPE_D = read_minima_data(D,pathOutput)
SCF_E, ZPE_E = read_minima_data(E,pathOutput)
SCF_F, ZPE_F = read_minima_data(F,pathOutput)
SCF = [SCF_A, SCF_B, SCF_C, SCF_D, SCF_E, SCF_F]
ZPE = [ZPE_A, ZPE_B, ZPE_C, ZPE_D, ZPE_E, ZPE_F]
species = [A, B, C, D, E, F]
for T in temperatures:
kf_cTST, kb_cTST, dGr, dHr, dSr = cTST(T,reaction_name, species, conv_f, conv_b, SCF, pathOutput)
contents = "%-20d %15.3f %15.3f %15.3f %15.6E %15.6E" %(T, dGr, dHr, dSr, kf_cTST, kb_cTST)
lines_to_write.append(contents)
lines_to_write = sorted(list(set(lines_to_write)),key=lambda item: (int(item.partition(' ')[0]) if item[0].isdigit() else float('inf'), item))
text = "\n".join(lines_to_write) + "\n"
header1 = "%-20s %15s %15s %15s %15s %15s" %('Temperature', 'dGr (kcal/mol)', 'dHr (kcal/mol)', 'dSr (cal/mol)', 'kf(cTST)', 'kb(cTST)') + '\n'
header2 = "%-20s %15s %15s %15s %15s %15s" %('-----------', '--------------', '--------------', '--------------', '--------------', '---------------') + '\n'
rate_constants_dir = pathOutput+"rate-constants-barrierless/"
if not os.path.exists(rate_constants_dir):
os.makedirs(rate_constants_dir)
with open(os.path.join(rate_constants_dir,reaction_name + '.txt'), "w") as File:
File.writelines(header1+header2)
File.writelines(text)
def get_symmetry_factors(pathCSV,fileCSV):
# Get symmetry factors
ifile = open(os.path.join(pathCSV,fileCSV), "r")
reader = csv.reader(ifile)
rownum = 0
species_list = []
TS_list = []
reactions_list = []
symmetry = []
for row in reader:
if rownum < 3:
pass
else:
reactants,products = row[0].split('=')
species = reactants.split('+') + products.split('+')
species_list.extend(species)
TS = "-p-".join(reactants.split('+')) + '-TS-' + "-p-".join(products.split('+'))
TS_list.append(TS)
reactions_list.append(row[0])
symmetry.append([row[0],row[1],row[2]])
rownum = rownum + 1
return symmetry
def curvefit_arrhenius(pathOutput,pathCSV,fileCSV):
R = 8.3144621
Path = pathOutput + "rate-constants-barrierless/"
Path2final = pathOutput
if not os.path.exists(Path):
os.mkdir(Path)
def kf(T, A, n, Ea):
return A*(T**n)*numpy.exp(-Ea/R/T)
def logkf(T, lnA, n, Ea):
return -Ea/R/T + n*numpy.log(T) + lnA
lines_to_write = []
for file_name in os.listdir(Path):
if file_name.endswith('.txt'):
reaction_name = file_name.split('.txt')[0]
reactants, products = reaction_name.split('-TS-')
reactants = '+'.join(reactants.split('-p-'))
products = '+'.join(products.split('-p-'))
reaction_name = '='.join([reactants,products])
data = numpy.genfromtxt(Path + file_name,skip_header=2)
xdata = data[0:18,0]
ydata = data[0:18,4]
ydata = numpy.log(data[0:18,4])
dHf = numpy.mean(data[0:18,2])
x0 = numpy.array([1.0,1.0,dHf])
sigma = numpy.ones((ydata.size,))
coeff = optimization.curve_fit(logkf, xdata, ydata)
#coeff = optimization.curve_fit(logkf, xdata, ydata, x0, sigma, bounds = ([0, -10, -numpy.inf],[numpy.inf, 10, numpy.inf]))
a = coeff[0]
perr = numpy.sqrt(numpy.diag(coeff[1]))
A = a[0]
n = a[1]
Ea = a[2]/4.184
A = math.exp(a[0])
n = a[1]
Ea = a[2]/4.184
for sym in get_symmetry_factors(pathCSV,fileCSV):
if sym[0]== reaction_name:
for_sym = float(sym[1])
back_sym = float(sym[2])
A = for_sym*A
contents = "%-50s %15.3E %15.2f %15.3f" %(reaction_name, A, n, Ea)
lines_to_write.append(contents)
k = A*(xdata**n)*numpy.exp(-Ea*4.184/R/xdata)
kf = for_sym*numpy.exp(ydata)
SSE = numpy.sum(numpy.square(kf-k))
avg = numpy.sum(kf)
SST = numpy.sum(numpy.square(kf-avg))
R_square = 1 - (SSE/SST)
print R_square, reaction_name
f = open(Path+file_name.split('.txt')[0]+'.data', 'w')
numpy.savetxt(f,numpy.c_[xdata, kf, k, kf/k], fmt='%5d %15.3E %15.3E %10.2f', header='%4s %14s %15s %10s'%('T(K)', 'Data', 'Fit', 'Data/fit'), footer='\n')
numpy.savetxt(f,numpy.c_[A, n, Ea], fmt='%15.3E %15.3f %15.3f',header='%10s %15s %22s'%('A', 'n', 'Ea (cal/mol)'))
numpy.savetxt(f,numpy.c_[perr[0], perr[1], perr[2]], fmt='%15.3E %15.3f %15.3f')
numpy.savetxt(f,numpy.c_[R_square], fmt='%15.4f', header='')
f.close()
lines_to_write = sorted(list(set(lines_to_write)),key=str.lower)
text = "\n".join(lines_to_write) + "\n"
header1 = "%-50s %15s %15s %15s" %('Reaction', 'A', 'n', 'Ea(cal/mol)') + '\n'
header2 = "%-50s %15s %15s %15s" %('--------------------------------------------------', '---------------', '---------------', '---------------') + '\n'
with open(os.path.join(Path2final,'kinetics-barrierless.txt'), "w") as File:
File.writelines(header1+header2)
File.writelines(text)
###############################################################################
# Change input output paths and set output file names here
###############################################################################
base_directory = '/gpfs/group/umt/default/HMX/nitramine_gas_phase_mechanism/improvements-to-caltech-mechanism/final-gas-phase-mechanism/'
pathCSV = base_directory
pathB3LYP = base_directory + 'M062X-minima'
pathTS = base_directory + 'M062X-TS'
pathOutput = base_directory + 'Output-files/'
fileCSV = 'PSU-gas-phase-mechanism.csv'
###############################################################################
list_of_barrierless_reactions = get_barrierless_reactions(pathCSV, fileCSV, pathTS)
calculate_rate_constants(pathTS,pathOutput,list_of_barrierless_reactions)
curvefit_arrhenius(pathOutput,pathCSV,fileCSV)