High-throughput computational screening and thermodynamics-informed machine learning for lithium-based ceramic materials for high-temperature CO2 capture.
capture. A reaction-level graph neural network with transfer learning was proposed that efficiently predicted the temperature dependence of the carbonation reaction.
Authors
- Hongjian Tang (ORCID: https://orcid.org/0000-0003-0484-3665)
- Yang Yang (ORCID: https://orcid.org/0009-0002-5189-8415)
- Zhihan Shen (ORCID: https://orcid.org/0009-0001-0619-872X)
- Lunbo Duan
Institutions
- Ministry of Education (RO)
Publication Details
- Journal
- PubMed
- Published
- 2026-09-09
- DOI
- https://doi.org/10.1039/d6cc04275a
- Primary Topic
- Machine Learning in Materials Science
- Type
- article
- Field-Weighted Citation Impact
- 0.00