High-throughput Screening Computation for Discovery of Porous Zeolites for Hydrogen Storage

Abstract

Hydrogen is considered an attractive energy resource because it is eco-friendly in contrast with fossil fuels. Hydrogen storage remains as essential technology for increasing the use of the hydrogen in applications such as hydrogen vehicles and fuel cells. Hydrogen storage requires retaining a high density of hydrogen molecules at ambient temperature in a suitable tank. Zeolites are one of the promising hydrogen storage materials, but experimentally investigating them for hydrogen storage is difficult since the number of the zeolites in the largescale material database has been increasing. In the present study I developed an efficient method of exploring potential zeolites in the database that had high volumetric hydrogen storage capacity. To do this I employed a high-throughput screening approach to automatically construct a zeolite database for hydrogen storage in the Inorganic Crystal Structural Database (ICSD). Also, I performed grand canonical Monte Carlo (GCMC) simulations to estimate hydrogen adsorption isotherms at operating ambient temperatures, to determine the volumetric hydrogen storage capacity of the zeolites. Finally, I found 10 top ranked materials in the zeolite database for H2 storage, and I calculated Pearson’s correlation coefficient to revealed the linear correlations between the hydrogen storage capacities and 3 structural characteristics (i.e., surface area, largest cavity diameter, pore limiting diameter). Furthermore, I investigated atom species in the 10 materials to show the relation between the hydrogen storage capacities and chemical elements. In future works, I expect the method can be easily applied to accelerate the discovery and design of porous materials for storing CO2 or toxic gases.