Machine learning of metal-organic framework design for carbon dioxide capture and utilization
Metal-organic frameworks (MOFs) are attractive materials with easily tunable porous structures. Their selective carbon dioxide (CO2) capture ability can be varied by altering the functionality of the organic ligands. However, rule-based approaches to tuning and developing MOFs with high CO2 capture...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-11-01
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| Series: | Journal of CO2 Utilization |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2212982024002762 |
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