GRAPPA -- A Hybrid Graph Neural Network for Predicting Pure Component Vapor Pressures
Paper โข 2501.08729 โข Published
GRAPPA is a hybrid graph neural network that predicts the Antoine parameters of pure components from their SMILES. This repository contains the unchanged published state dict, so that screening-properties (the property package of the ScreeningTool process-screening framework) can download it on first use.
All credit goes to the original authors. Code and weights: marco-hoffmann/GRAPPA (MIT licence, see LICENSE).
@misc{Hoffmann2025,
title = {GRAPPA - A Hybrid Graph Neural Network for Predicting Pure Component Vapor Pressures},
author = {Marco Hoffmann and Hans Hasse and Fabian Jirasek},
year = {2025},
eprint = {2501.08729},
archivePrefix = {arXiv},
primaryClass = {cs.LG},
url = {https://arxiv.org/abs/2501.08729}
}
| File | Content |
|---|---|
models/GRAPPA_state_dict.pt |
PyTorch state dict (tensors only; load with weights_only=True) |
The model outputs Antoine A, B, C for ln(p/kPa) with T in K. Molecules with formal charges are not supported.