Statistical Thermodynamics Reactor

A python script to calculate reaction data with Statistical Thermodynamics (ΔG, ΔS, ΔH, ΔU, reaction constant); from the lecture of Roberto Marquardt.

Try the Web App:

Try the web app based on Streamlit: it's free, no need to install anything!

Stat-Therm-Reactor Web App

Required package:

pandas
matplotlib

Remarks:

The script works for one reaction only.
The input parameters are stored in a dictionary called 'data'. The reaction state functions are stored in a dictionary called 'results'.
The script is meant to be used from python interpreter. Make sure the script is located in the working directory or added to the pythonpath
To convert cm-1 to Joule: multiply for hc

Required parameters summary:

U0_value: Internal Energy of the reaction at 0 kelvin at standard pressure [Joule/mol]
s_c: stoichiometric number, positive for products and negative for reactants
P: pressure [bar]
m: molecular mass [dalton]
B: rotational constant [cm-1]
o: symmetry number of the compound (The symmetry number of a molecule is the order of the finite rotational sub-group of the point group of the molecule.)
linear: the molecule is linear ('True'), not linear ('False'), or an atom ('Atom')
n_mod: list of the vibrational mode frequencies [cm-1]
n_deg: list of the vibrational mode degeneracies
gn_list_elec: list of electron levels degeneracies
En: list of electron level Energies [cm-1]
spin_list: list of the nuclear spins
A: other eventual rotational constant [cm-1]
C: other eventual rotational constant [cm-1]
T: temperature [Kelvin]

Usage in the python interpreter:

Import the functions:
from stat_thermo import *

Initialize a dictionary with the value of the Internal Energy at 0 Kelvin (U0_value), by typing

data["U0"]= U0_value

Initialize a new compound (compound_name) and set the stoichiometric number:

data["compound_name"]=dict()
data["compound_name"]["s_c"]= stechometric number

Start setting the parameters for each reactant and product. Do not change the keyword 'param'. Use this order:

data['compound_name']["param"]= [P, m, B, o, linear (True, False or 'Atom'), n_mod, n_deg, gn_list_elec, En, spin_list, A, C]

Functions

Low-level functions:

Partition functions:
- qt(T, P, m)
- qro(T, B, linear, o, A=0, C=0)
- qv(T, n_mod, n_deg)
- qe(T, gn_list_elec, En)
- qn(spin_list)
- Q(name, T, P, m, B, o, linear, n_mod, n_deg, gn_list_elec, En, spin_list, A=0, C=0)
Internal Energy:
- Ut(T)
- Ur(T, linear)
- Uv(T, n_mod, n_deg)
- Ue(T, qe, gn_list_elec, En)
- U(compound_name, T, n_mod, n_deg, linear, qe, gn_list_elec, En)
Entropy:
- St(qt)
- S(T, q, U)
- S_calc(compound_name, T)

Easy-to-use functions:

Q_fast(compound_name, T)
U_fast(name, T)
S_fast(name, T)
k_fast(T)

Plotting the state functions:

plot(Ti, Tf, step, save=False)

Print the results on screen:

visual()

Save the results:

save(filename='stat_thermo_results')

Example:

Decomposition of formaldehyde into carbon monoxide and dihydrogen:

1 H2CO ⇌ 1 H2 + 1 CO

# import the functions

from stat_thermo import *

# set up the initial parameters

data["U0"]= -1700
data["H2"]=dict()
data["H2"]["s_c"]= 1
data['H2']['param']=[1, 2.01588, 60.89, 2, True,[4280], [1], [1], [0], [1/2, 1/2], 0, 0]
data["CO"]=dict()
data["CO"]["s_c"]= 1
data["CO"]["param"]=[1, 28.0140, 1.930, 1, True, [2156], [1], [1], [0], [0, 0], 0, 0]
data["H2CO"]=dict()
data["H2CO"]["s_c"]= -1
data["H2CO"]["param"]=[1, 30.02628, 9.405, 2, False, [2843, 2766, 1746, 1501, 1247, 1164],[1,1,1,1,1,1], [1], [0], [1/2, 1/2, 0, 0], 1.295, 1.134 ]

# Calculate the results

Q_fast("H2",300) #calculate all q for H2
data["H2"][300]["qt"] #to see the values of qt
U_fast("H2",300)
S_fast("H2",300)
k_fast(300)
k_fast(100)
visual()
plot(100,300,20, save= "example")
visual()
save("reaction_data")

Help

In the python interpreter type:

import stat_thermo
help(stat_thermo)

Lucandia/stat_thermo_reactor