ugropy is a Python library to obtain subgroups from different thermodynamic
group contribution models using both the name or the SMILES representation of a
molecule. If the name is given, the library uses the
PubChemPy library to obtain the SMILES
representation from PubChem. In both cases, ugropy uses the
RDKit library to search the functional groups
in the molecule.
ugropy is in an early development stage, leaving issues of examples of
molecules that ugropy fails solving the subgroups of a model is very helpful.
ugropy is tested for Python 3.10, 3.11 and 3.12 on Linux, Windows and Mac
OS.
Try ugropy now
You can try ugropy without installing it by clicking on the Colab badge.
Models implemented
Gibbs / EoS models
Classic liquid-vapor UNIFAC
Predictive Soave-Redlich-Kwong (PSRK)
Property estimators
Joback
Abdulelah-Gani (beta)
Writers
ugropy allows you to convert the obtained functional groups or estimated
properties to the input format required by the following thermodynamic
libraries:
Example of use
Here is a little taste of ugropy, please, check the full tutorial
here to see
all it has to offer!
Get groups from the molecule’s name:
from ugropy import Groups
hexane = Groups("hexane")
print(hexane.unifac.subgroups)
print(hexane.psrk.subgroups)
print(hexane.joback.subgroups)
print(hexane.agani.primary.subgroups)
{'CH3': 2, 'CH2': 4}
{'CH3': 2, 'CH2': 4}
{'-CH3': 2, '-CH2-': 4}
{'CH3': 2, 'CH2': 4}
Get groups from molecule’s SMILES:
propanol = Groups("CCCO", "smiles")
print(propanol.unifac.subgroups)
print(propanol.psrk.subgroups)
print(propanol.joback.subgroups)
print(propanol.agani.primary.subgroups)
{'CH3': 1, 'CH2': 2, 'OH': 1}
{'CH3': 1, 'CH2': 2, 'OH': 1}
{'-CH3': 1, '-CH2-': 2, '-OH (alcohol)': 1}
{'CH3': 1, 'CH2': 2, 'OH': 1}
Estimate properties with the Joback and Abdulelah-Gani models!
limonene = Groups("limonene")
print(limonene.joback.subgroups)
print(f"{limonene.joback.critical_temperature} K")
print(f"{limonene.joback.vapor_pressure(176 + 273.15)} bar")
{'-CH3': 2, '=CH2': 1, '=C<': 1, 'ring-CH2-': 3, 'ring>CH-': 1, 'ring=CH-': 1, 'ring=C<': 1}
657.4486692170663 kelvin
1.0254019428522743 bar
print(limonene.agani.primary.subgroups)
print(limonene.agani.secondary.subgroups)
print(limonene.agani.tertiary.subgroups)
print(f"{limonene.agani.critical_temperature}")
print(limonene.agani.molecular_weight / limonene.agani.liquid_molar_volume)
{'CH3': 2, 'CH2=C': 1, 'CH2 (cyclic)': 3, 'CH (cyclic)': 1, 'CH=C (cyclic)': 1}
{'CH3-CHm=CHn (m,n in 0..2)': 1, '(CHn=C)cyc-CH3 (n in 0..2)': 1, 'CHcyc-C=CHn (n in 1..2)': 1}
{}
640.1457030826214 kelvin
834.8700605718585 gram / liter
Visualize your results! (The next code creates the ugropy logo)
mol = Groups("CCCC1=C(COC(C)(C)COC(=O)OCC)C=C(CC2=CC=CC=C2)C=C1", "smiles")
mol.unifac.draw(
title="ugropy",
width=800,
height=450,
title_font_size=50,
legend_font_size=14
)
Write down the Clapeyron.jl .csv input files.
from ugropy import writers
names = ["limonene", "adrenaline", "Trinitrotoluene"]
grps = [Groups(n) for n in names]
# Write the csv files into a database directory
writers.to_clapeyron(
molecules_names=names,
unifac_groups=[g.unifac.subgroups for g in grps],
psrk_groups=[g.psrk.subgroups for g in grps],
joback_objects=[g.joback for g in grps],
path="database"
)
Obtain the Caleb Bell’s Thermo subgroups
from ugropy import unifac
names = ["hexane", "ethanol"]
grps = [Groups(n) for n in names]
[writers.to_thermo(g.unifac.subgroups, unifac) for g in grps]
[{1: 2, 2: 4}, {1: 1, 2: 1, 14: 1}]
Installation
pip install ugropy