Representation learning for long-chain hydrocarbon adsorption in zeolites
A suite of machine learning models was assessed for predicting long-chain hydrocarbon adsorption in zeolites. Graph neural networks and vision transformers struggle while ZeoNet significantly outperforms others.
Authors
- Yachan Liu
- Wei Fan (ORCID: https://orcid.org/0000-0002-8581-2651)
- Peng Bai (ORCID: https://orcid.org/0000-0002-6881-4663)
- Subhransu Maji (ORCID: https://orcid.org/0000-0002-3869-9334)
- Gustavo Pérez
- Aaron Sun
- Ping Yang (ORCID: https://orcid.org/0009-0003-3987-7467)
Institutions
- Amherst College (US)
- University of Massachusetts Amherst (US)
Publication Details
- Journal
- Journal of Materials Chemistry A
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1039/d5ta04285b
- Primary Topic
- Neural Networks and Applications
- Type
- article
- Field-Weighted Citation Impact
- 0.00