Abstract

Metal organic frameworks (MOFs) are promising materials for the storage of hydrogen fuel due to their high surface areas, tunable properties, and reversible gas adsorption. Although several MOFs are known to exhibit high hydrogen densities on a gravimetric basis, realizing high volumetric capacities a critical attribute for maximizing the driving range of fuel cell vehicles remains a challenge. Here, MOFs that achieve high gravimetric and volumetric H2 densities simultaneously are identified computationally, and demonstrated experimentally. The hydrogen capacities of ~100,000 MOFs drawn from databases of known and hypothetical compounds were predicted using empirical correlations and direct atomistic simulations. Based on these predictions, promising MOF candidates were synthesized and evaluated with respect to their usable H2 capacities. Several MOFs predicted to exhibit high capacities displayed low surface areas upon activation, highlighting the need to understand the factors that control stability. Consistent with the computational predictions, several MOFs were experimentally demonstrated to exhibit an uncommon combination of high usable volumetric and gravimetric capacities. Importantly, the measured capacities exceed those of the benchmark compound MOF-5, the record-holder for combined volumetric/gravimetric performance. Multiple machine learning algorithms were trained on this computationally-generated database. The relative accuracy of these algorithms were compared, with the most promising algorithm applied to predict H2 capacities in an additional 400,000 MOFs. Our study illustrates the value of computational screening in pinpointing materials that optimize overall storage performance.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.