In Silico Investigation into H₂ Uptake in MOFs: Combined Text/Data Mining and Structural Calculations

Metal-organic frameworks (MOFs) with high surface areas and adjustable lattice structures are attractive for gas storage and thus have been a great interest in research. Although tremendous amount of data on MOFs have been available in the literature, there are very few studies considering methodological approach for H₂ uptake properties of MOFs. In this study, we systematically investigated the H₂ uptake capabilities of MOFs by means of text and data mining (TDM) through retrieving data of the surface areas (SA) and pore volumes (PV) from published manuscripts. In addition, we calculated theoretical SA and PV values of all real MOFs available in Cambridge Structural Database (CSD). Prior to calculation, we applied an automated structure analysis algorithm that loads the coordinates of molecules from CSD experimental X-ray single-crystal structure and removes guest/solvent contaminants from the structure. We compared SA, PV, and H₂ uptake data from both TDM and structural calculation techniques and unraveled a list of MOFs with H₂ uptakes predicted from both experimental and theoretical SA/PV values that may be regarded as the most promising candidates for H₂ storage. The extensive and systematic TDM strategy estimates 5975 experimental SA and 7748 experimental PV values (2080 MOFs with SA + PV values) with 78-82% success rate. In addition, structural calculations reveal the theoretical SA and PV values along with a theoretical H₂ adsorption limit of MOFs in the absence of guest molecules. Combination of both TDM and structural calculation strategies provides a more comprehensive perspective for the investigation of hydrogen storage capacities in MOFs, which elucidates plausibility of new compounds as candidates for H₂ storage materials.