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- Title
Enhanced hydrogen storage efficiency with sorbents and machine learning: a review.
- Authors
Osman, Ahmed I.; Abd-Elaziem, Walaa; Nasr, Mahmoud; Farghali, Mohamed; Rashwan, Ahmed K.; Hamada, Atef; Wang, Y. Morris; Darwish, Moustafa A.; Sebaey, Tamer A.; Khatab, A.; Elsheikh, Ammar H.
- Abstract
Hydrogen is viewed as the future carbon–neutral fuel, yet hydrogen storage is a key issue for developing the hydrogen economy because current storage techniques are expensive and potentially unsafe due to pressures reaching up to 700 bar. As a consequence, research has recently designed advanced hydrogen sorbents, such as metal–organic frameworks, covalent organic frameworks, porous carbon-based adsorbents, zeolite, and advanced composites, for safer hydrogen storage. Here, we review hydrogen storage with a focus on hydrogen sources and production, advanced sorbents, and machine learning. Carbon-based sorbents include graphene, fullerene, carbon nanotubes and activated carbon. We observed that storage capacities reach up to 10 wt.% for metal–organic frameworks, 6 wt.% for covalent organic frameworks, and 3–5 wt.% for porous carbon-based adsorbents. High-entropy alloys and advanced composites exhibit improved stability and hydrogen uptake. Machine learning has allowed predicting efficient storage materials.
- Subjects
HYDROGEN storage; MACHINE learning; SORBENTS; HYDROGEN economy; ACTIVATED carbon; FULLERENES; METALLIC composites
- Publication
Environmental Chemistry Letters, 2024, Vol 22, Issue 4, p1703
- ISSN
1610-3653
- Publication type
Article
- DOI
10.1007/s10311-024-01741-3