GNNPCSAFT Project
The project focuses on using Graph Neural Networks (GNN) to estimate the pure-component parameters of the Equation of State PC-SAFT.
Currently, the model takes into account the hard-chain, dispersive, and associative terms of PC-SAFT. Future work on polar and ionic terms is being studied.
Use cases of this package are demonstrated in Jupyter Notebooks:
compare.ipynb(Open in Colab): comparison of the performance of trained modelstraining.ipynb(Open in Colab): notebook for model trainingtuning.ipynb(Open in Colab): notebook for hyperparameter tuning
Model checkpoints can be found at Hugging Face.
Implementations with GNNPCSAFT:
1 maintainer
Release files for gnnepcsaft 0.5.3
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| gnnepcsaft-0.5.3.tar.gz | 18.9 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| gnnepcsaft-0.5.3-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 37.9 MB
Release files / gnnepcsaft-0.5.3.tar.gz
| Download URL | gnnepcsaft-0.5.3.tar.gz |
|---|---|
| Size | 18.9 MB |
| Tags | Source |
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Release files / gnnepcsaft-0.5.3-py3-none-any.whl
| Download URL | gnnepcsaft-0.5.3-py3-none-any.whl |
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| Size | 19.0 MB |
| Tags | Python 3 |
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uv/0.12.9 {"installer":{"name":"uv","version":"0.12.9","subcommand":["publish"]},"python":null,"implementation":{"name":null,"version":null},"distro":{"name":"Ubuntu","version":"24.04","id":"noble","libc":null},"system":{"name":null,"release":null},"cpu":null,"openssl_version":null,"setuptools_version":null,"rustc_version":null,"ci":true}
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