This repository contains the code used in the paper Gibbs-Helmholtz Graph Neural Network: capturing the temperature dependency of activity coefficients at infinite dilution.
Check this notebook out to learn how to use GH-GNN for making predictions.
Clone the repository and create a conda environment with all dependencies installed by running by running:
git clone https://github.com/edgarsmdn/GH-GNN.git
cd GH-GNN
conda env create -f enviornment.yml
@article{sanchez2022ghgnn,
title={Gibbs-Helmholtz Graph Neural Network: capturing the temperature dependency of activity coefficients at infinite dilution},
author={Sanchez Medina, Edgar Ivan and Linke, Steffen and Stoll, Martin and Sundmacher, Kai},
journal={arXiv preprint arXiv:2212.01199},
year={2022}
}
If you use GH-GNN you could also give a star ⭐ to this repo
This material is licensed under the MIT license and is free and provided as-is. If you use the code provided in this repository please cite the original publication.