Large-Scale\nComputational Screening-Aided Development\nof High-Performance Adsorbent for Simultaneous Capture of Aromatic\nVolatile Organic Compounds

The\ndevelopment of an efficient adsorbent for the simultaneous\ncapture of large amounts of benzene, toluene, ethylbenzene, and xylene\nisomers (BTEX) is an important and challenging issue. Here, through\na stepwise screening of 10,142 metal–organic framework (MOF)\nstructures from the computation-ready, experimental (CoRE) MOF database,\n65 MOFs are proposed as promising adsorbent candidates for BTEX capture\nby considering the structures with accessible pore sizes for BTEX\nadsorption, sufficient hydrophobicity, high benzene selectivity (>0.2),\nand large total BTEX uptake (>3 mmol/g). Among the top-performing\nMOFs in terms of the BTEX<sub>matrix</sub> (total BTEX uptake ×\nbenzene selectivity), EGUELUY01 was synthesized, and it exhibited\nlarge uptakes (≈5 mmol/g) for all BTEX components at concentrations\nof 1200–1500 ppm, which are superior to the BTEX uptake of\nthe benchmark adsorbent, activated carbon. Moreover, some structure–property\nrelationships required for BTEX adsorbents are provided through the\nobtained large-scale simulation data and machine learning analysis.\nThe determined relationships will be useful for the future development\nof efficient BTEX adsorbents.