Tuning the Pore Surface of an Ultramicroporous Framework for Enhanced Methane and Acetylene Purification Performance

Both methane (CH 4 ) and acetylene (C 2 H 2 ) are important energy source and raw chemicals in many industrial processes. The development of an energy-efficient and environmentally friendly separation and purification strategy for CH 4 and C 2 H 2 is necessary. Ultramicroporous metal–organic framework (MOF) materials have shown great success in the separation and purification of small-molecule gases. Herein, the synergy effect of tritopic polytetrazolate and ditopic terephthalate ligands successfully generates a series of isoreticular ultramicroporous cadmium tetrazolate–carboxylate MOF materials (SNNU-13–16) with excellent CH 4 and C 2 H 2 purification performance. Except for the uncoordinated tetrazolate N atoms serving as Lewis base sites, the pore size and pore surface of MOFs are systematically engineered by regulating dicarboxylic acid ligands varying from OH-BDC (SNNU-13) to Br-BDC (SNNU-14) to NH 2 -BDC (SNNU-15) to 1,4-NDC (SNNU-16). Benefiting from the ultramicroporous character (3.8–5.9 Å), rich Lewis base N sites, and tunable pore environments, all of these ultramicroporous MOFs exhibit a prominent separation capacity for carbon dioxide (CO 2 ) or C2 hydrocarbons from CH 4 and C 2 H 2 . Remarkably, SNNU-16 built by 1,4-NDC shows the highest ideal adsorbed solution theory CO 2 /CH 4, ethylene (C 2 H 4 )/CH 4, and C 2 H 2 /CH 4 separation selectivity values, which are higher than those of most famous MOFs with or without open metal sites. Dynamic breakthrough experiments show that SNNU-16 can also efficiently separate the C 2 H 2 /CO 2 mixtures with a gas flow rate of 4 mL min –1 under 1 bar and 298 K. The breakthrough time (18 min g –1 ) surpasses most best-gas-separation MOFs and nearly all other metal azolate–carboxylate MOF materials under the same conditions. The above prominently CH 4 and C 2 H 2 purification abilities of SNNU-13–16 materials were further confirmed by the Grand Canonical Monte Carlo (GCMC) simulations.