Graph neural networks for temperature-dependent activity coefficient prediction of solutes in ionic liquids

Graph neural networks for temperature-dependent activity coefficient prediction of solutes in ionic liquids

Rittig, J. (Rheinisch-Westfälische Technische Hochschule)
Ben Hicham, Karim (Rheinisch-Westfälische Technische Hochschule)
Schweidtmann, A.M. (TU Delft ChemE/Product and Process Engineering)
Dahmen, Manuel (Forschungszentrum Jülich GmbH)
Mitsos, Alexander (Rheinisch-Westfälische Technische Hochschule; Forschungszentrum Jülich GmbH; JARA Center for Simulation and Data Science (CSD))

2023

Ionic liquids (ILs) are important solvents for sustainable processes and predicting activity coefficients (ACs) of solutes in ILs is needed. Recently, matrix completion methods (MCMs), transformers, and graph neural networks (GNNs) have shown high accuracy in predicting ACs of binary mixtures, superior to well-established models, e.g., COSMO-RS and UNIFAC. GNNs are particularly promising here as they learn a molecular graph-to-property relationship without pretraining, typically required for transformers, and are, unlike MCMs, applicable to molecules not included in training. For ILs, however, GNN applications are currently missing. Herein, we present a GNN to predict temperature-dependent infinite dilution ACs of solutes in ILs. We train the GNN on a database including more than 40,000 AC values and compare it to a state-of-the-art MCM. The GNN and MCM achieve similar high prediction performance, with the GNN additionally enabling high-quality predictions for ACs of solutions that contain ILs and solutes not considered during training.

Activity coefficient prediction
Graph learning
Green solvents
Ionic liquids
Machine learning

http://resolver.tudelft.nl/uuid:f9c33150-d32d-417c-b7a8-1f5071ef71d0

https://doi.org/10.1016/j.compchemeng.2023.108153

2023-07-26

0098-1354

Computers & Chemical Engineering, 171

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Institutional Repository

journal article

© 2023 J. Rittig, Karim Ben Hicham, A.M. Schweidtmann, Manuel Dahmen, Alexander Mitsos