Prediction of Hydrogen Adsorption and Moduli of Metal–Organic Frameworks (MOFs) Using Machine Learning Strategies

Prediction of Hydrogen Adsorption and Moduli of Metal–Organic Frameworks (MOFs) Using Machine Learning Strategies

For hydrogen-powered vehicles, the efficiency cost brought about by the current industry choices of hydrogen storage methods greatly reduces the system’s overall efficiency. The physisorption of hydrogen fuel onto metal–organic frameworks (MOFs) is a promising alternative storage method due to their...

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Bibliographic Details
Main Authors: Nicole Kate Borja, Christine Joy E. Fabros, Bonifacio T. Doma
Format: Article
Language:English
Published: MDPI AG 2024-02-01
Series:Energies
Subjects:
hydrogen uptakes in metal–organic frameworks (MOFs)
machine learning algorithms
modulus prediction of MOFs
Online Access:https://www.mdpi.com/1996-1073/17/4/927

Internet

https://www.mdpi.com/1996-1073/17/4/927

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