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https://github.com/ipqa-research/ugropy

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.
https://github.com/ipqa-research/ugropy

chemical chemical-engineering compound contribution engineering excess fragmentation functional gibbs group groups grupal joback molecule properties pure python thermodynamics unifac

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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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README

        

![logo](logo.png)

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`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](https://github.com/mcs07/PubChemPy) library to obtain the SMILES
representation from PubChem. In both cases, `ugropy` uses the
[RDKit](https://github.com/rdkit/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](https://mybinder.org/v2/gh/ipqa-research/ugropy/main). 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:

- [Clapeyron.jl](https://github.com/ClapeyronThermo/Clapeyron.jl)
- [Thermo](https://github.com/CalebBell/thermo)

# Example of use
You can check the full tutorial
[here](https://ipqa-research.github.io/ugropy/tutorial/tutorial.html).

Get groups from the molecule's name:

```python
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:

```python
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!

```python
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)

```Python
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](https://github.com/ClapeyronThermo/Clapeyron.jl)
.csv input files.

```python
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](https://github.com/CalebBell/thermo) subgroups

```python
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
```