The low volumetric density of hydrogen is a major limitation to its use as a transportation fuel. Filling a fuel tank with nanoporous materials, such as metal–organic frameworks (MOFs), could greatly improve the deliverable capacity of these tanks if appropriate materials could be found. However, since MOFs can be made from many combinations of metal nodes, organic linkers, and functional groups, the design space of possible MOFs is enormous. Experimental characterization of thousands of MOFs is infeasible, and even conventional molecular simulations can be prohibitively expensive for large databases. In this work, we have developed a data-driven approach to accelerate materials screening and learn structure–property relationships. We report new descriptors for gas adsorption in MOFs derived from the energetics of MOF–guest interactions. Using the bins of an energy histogram as features, we trained a sparse regression model to predict gas uptake in multiple MOF databases to an accuracy within 3 g L⁻¹. The interpretable model parameters indicate that a somewhat weak attraction between hydrogen and the framework is ideal for cryogenic storage and release. Our machine learning method is more than three orders of magnitude faster than conventional molecular simulations, enabling rapid exploration of large numbers of MOFs. As a case study, we applied the method to screen a database of more than 50 000 experimental MOF structures. We experimentally validated one of the top candidates identified from the accelerated screening, MFU-4l. This material exhibited a hydrogen deliverable capacity of 47 g L⁻¹ (54 g L⁻¹ simulated) when operating at storage conditions of 77 K, 100 bar and delivery at 160 K, 5 bar.

We present a fast and accurate, semi-analytical method for predicting hydrogen adsorption in nanoporous materials. For any temperature and pressure, the adsorbed amount is calculated as an integral over the energy density of adsorption sites (guest-host interactions) plus an average guest-guest term. The guest-host interaction energy is calculated using a classical force field with hydrogen modelled as a single-site probe. The guest-guest interaction energy is approximated using an average coordination number, which is regressed using Gaussian Process Regression (GPR). Local adsorption at each site is then modelled using a Langmuir isotherm, which when weighted with its probability density gives an accurate description of hydrogen adsorption. The method is tested on 933 metal-organic frameworks (MOFs) from the Computation-Ready Experimental (CoRE) MOF database at 77 K from ${10}^{-5}$ to 100 bar, and the results are compared against GCMC predictions. To demonstrate the utility of the method, we calculated hydrogen adsorption isotherms for 12,914 existing MOF structures, at two different temperatures at a speed about 100 times that of GCMC simulations and analyzed the results. We found 13 MOFs with predicted deliverable capacities exceeding the DOE target of 50 g/L for adsorption at 100 bar, 77 K and desorption at 5 bar, 160 K.

Molecular diffusion is commonly found to slow down with increasing molecular size. Deviations from this pattern occur in some host materials with pore sizes approaching the diameters of the guest molecules. A variety of theoretical models have been suggested to explain deviations from this pattern, but robust experimental data are scarcely available. Here, we present such data, obtained by monitoring the chain length dependence of the uptake of n-alkanes in the zeolitic imidazolate framework ZIF-4. A monotonic decrease in diffusivity from ethane to n-butane was observed, followed by an increase for n-pentane, and another decrease for n-hexane. This observation was confirmed by uptake measurements with n-butane/n-pentane mixtures, which yield faster uptake of n-pentane. Further evidence is provided by the observation of overshooting effects, i.e., by transient n-pentane concentrations exceeding the (eventually attained) equilibrium value. Accompanying grand canonical Monte Carlo simulations reveal, for the larger n-alkanes, significant differences between the adsorbed and gas phase molecular configurations, indicating strong confinement effects within ZIF-4, which, with increasing chain length, may be expected to give rise to configurational shifts facilitating molecular propagation at particular chain lengths.