Abstract

Hydrogen storage in nanoporous materials has been attracting a great deal of attention in recent years, as high gravimetric H2 capacities, exceeding 10 wt% in some cases, can be achieved at 77 K using materials with particularly high surface areas. However, volumetric capacities at low temperatures, and both gravimetric and volumetric capacities at ambient temperature, need to be improved before such adsorbents become practically viable. This article therefore discusses approaches to increasing the gravimetric and volumetric hydrogen storage capacities of nanoporous materials, and maximizing the usable capacity of a material between the upper storage and delivery pressures. In addition, recent advances in machine learning and data science provide an opportunity to apply this technology to the search for new materials for hydrogen storage. The large number of possible component combinations and substitutions in various porous materials, including Metal-Organic Frameworks (MOFs), is ideally suited to a machine learning approach; so this is also discussed, together with some new material types that could prove useful in the future for hydrogen storage applications.

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