Aromatic Ring-Enhanced Pore-Space-Partitioned Metal-Organic Frameworks for Selective Separation of Saturated Hydrocarbons
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Updated: Nov 3, 2026

Electrophoretic Crystallization of Ultrathin High-performance Metal-organic Framework Membranes
Published on: August 16, 2018
Jia-Yao Liu1, Li-Qiu Yang1, Chen-Chen Xing1
1Key Laboratory of Applied Surface and Colloid Chemistry (MOE), Key Laboratory of Macromolecular Science of Shaanxi Province, School of Chemistry & Chemical Engineering, Shaanxi Normal University, Xi'an710062, China.
Abstract:
Light saturated hydrocarbons are difficult to separate efficiently because of their similar physicochemical properties, and metal-organic frameworks (MOFs) with tailor-made pore environments promising adsorbents for precise separation. Here, three aromatic ring-enhanced pore-space-partitioned MOFs (SNNU-304-306) were constructed by integrating thieno[2,3-b]thiophene-2,5-dicarboxylic acid (TDC) with tripyridyl partitioners of different aromatic frameworks and N-site characteristics. Modular variation of the partitioners within the same Ni-TDC framework tunes the cage geometry and local aromatic environment, enabling differentiated recognition of C1-C3 hydrocarbons. SNNU-306 exhibits the highest C2H6 and C3H8 uptakes, with C2H6/CH4 and C3H8/CH4 ideal adsorbed solution theory (IAST) selectivities of 34.1 and 1398.6 at 298 K. More importantly, dynamic breakthrough experiments show that SNNU-304 gives the longest separation time for C2H6/CH4, while SNNU-306 exhibits the longest separation time for C3H8/CH4, demonstrating the targeted regulation of different saturated-hydrocarbon separation requirements by different aromatic partitioners. For the ternary C3H8/C2H6/CH4 mixture, the CH4 purity reaches up to 99.96%. Grand Canonical Monte Carlo (GCMC) simulations reveal that different aromatic partitioners regulate host-guest interactions, thereby enabling differentiated hydrocarbon recognition. These results show that aromatic ring enhancement and pore-space partitioning synergistically transform pacs-MOFs into modularly tunable molecular-recognition systems, offering a strategy for the task-specific design of porous materials for saturated-hydrocarbon separation.
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