marco-hoffmann/GRAPPA
A GNN model for the prediction of pure component vapor pressures.
This project helps chemical engineers and material scientists predict how substances will behave as gases. By simply providing a molecule's SMILES string, you get predictions for its vapor pressure, boiling temperature, and the underlying Antoine equation parameters. This tool is designed for researchers and scientists who need quick, reliable estimates of these thermophysical properties based purely on molecular structure.
No commits in the last 6 months.
Use this if you need to quickly estimate vapor pressures, boiling temperatures, or Antoine parameters for pure chemical components based only on their molecular structure.
Not ideal if you require experimental accuracy or predictions for complex mixtures rather than pure components.
Stars
13
Forks
2
Language
Python
License
MIT
Category
Last pushed
Feb 03, 2025
Commits (30d)
0
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