A data-guided approach for the evaluation of zeolites for hydrogen storage with the aid of molecular simulations

• Published in: Journal of molecular modeling 2024-02, Vol.30 (2), p.43-43, Article 43
• Main Authors: Manda, Timothy, Barasa, Godfrey Okumu, Louis, Hitler, Irfan, Ahmad, Agumba, John Onyango, Lugasi, Solomon Omwoma, Pembere, Anthony M. S.
• Format: Article
• Language: English
• Subjects: Accessibility; Adsorption; Algorithms; Characterization and Evaluation of Materials; Chemistry; Chemistry and Materials Science; Clean energy; Computer Appl. in Life Sciences; Computer Applications in Chemistry; Computer simulation; Correlation analysis; Data analysis; Density functional theory; Energy storage; Energy technology; Feature extraction; Fugacity; Helium; Hydrogen; Hydrogen storage materials; Machine learning; Materials science; Molecular dynamics; Molecular Medicine; Neural networks; Original Paper; Particle interactions; Performance evaluation; Pseudopotentials; Quantum chemistry; Simulation; Software; Storage capacity; Theoretical and Computational Chemistry; Zeolites
• ISSN: 1610-2940; 0948-5023
• DOI: 10.1007/s00894-024-05837-z

Context This study employs a data-guided approach to evaluate zeolites for hydrogen storage, utilizing molecular simulations. The development of efficient and practical hydrogen storage materials is crucial for advancing clean energy technologies. Zeolites have shown promise as potential candidates due to their unique porous structure and tunable properties. However, the selection and design of suitable zeolites for hydrogen storage remain challenging. Therefore, this work aims to address this materials science question by utilizing molecular simulations and data-guided approaches to evaluate zeolites’ performance for hydrogen storage. The results obtained from this study provide valuable insights into the evaluation of zeolites for hydrogen storage. Through molecular simulations, we analyze the adsorption behavior of hydrogen molecules in various zeolite structures. The performance of different zeolite frameworks in terms of hydrogen storage capacity, adsorption energy, and diffusion properties is assessed. Linde type A zeolite (LTA) had the highest capacity with a hydrogen capacity of 4.8wt% out of the 233 investigated zeolites. Furthermore, we investigate the influence of different factors such as mass (M), density (D), helium void fraction (HVF), accessible pore volume (APV), gravimetric surface area (GSA), and largest overall cavity diameter (Di) on the hydrogen storage performance of zeolites. The results show that Di, D, and M have a negative effect on the percentage weight capacity, while GSA and VSA have the highest positive contribution to the percentage weight. This study, therefore, provides new insights into the factors that affect their hydrogen storage capacity by exhibiting the importance of considering multiple factors when evaluating the performance of zeolites and demonstrates the potential of combining different computational methods to provide a more comprehensive understanding of materials. The current study contributes to the understanding of zeolite-based materials for hydrogen storage applications, aiding in the development of more efficient and practical hydrogen storage systems. Methods Computational techniques were employed to investigate the hydrogen storage properties of zeolites. Molecular simulations were performed using classical force fields and molecular dynamics methods. The calculations were carried out at a force field level of theory with the GGA functional. To accurately capture the thermodynamics and kinetics of hyd