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A Python library designed to swiftly and effortlessly obtain the UNIFAC-like groups from molecules by their names and subsequently integrate them into inputs for thermodynamic libraries. UNIFAC, PSRK, and Joback models are implemented.

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Binder License Python 3.10+ Docs PyPI version

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 from its Binder. Open the binder.ipynb file to explore the basic features.

Models supported v2.0.7

  • Classic liquid-vapor UNIFAC
  • Predictive Soave-Redlich-Kwong (PSRK)
  • Joback

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

You can check the full tutorial here.

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)
{'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)
{'CH3': 1, 'CH2': 2, 'OH': 1}
{'CH3': 1, 'CH2': 2, 'OH': 1}
{'-CH3': 1, '-CH2-': 2, '-OH (alcohol)': 1}

Estimate properties with the Joback model!

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 K
1.0254019428522743 bar

Visualize your results! (The next code creates the ugropy logo)

from IPython.display import SVG

mol = Groups("CCCC1=C(COC(C)(C)COC(=O)OCC)C=C(CC2=CC=CC=C2)C=C1", "smiles")

svg = mol.unifac.draw(
    title="ugropy",
    width=800,
    height=450,
    title_font_size=50,
    legend_font_size=14
)

SVG(svg)

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", "2-butanone"]

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, 18: 1}]

Installation

pip install ugropy