Computational Screening of MOFs for Acetylene Separation

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Abstract

Efficient separation of acetylene (C2H2) from CO2 and CH4 is important to meet the requirement of high-purity acetylene in various industrial applications. Metal organic frameworks (MOFs) are great candidates for adsorption-based C2H2/CO2 and C2H2/CH4 separations due to their unique properties such as wide range of pore sizes and tunable chemistries. Experimental studies on the limited number of MOFs revealed that MOFs offer remarkable C2H2/CO2 and C2H2/CH4 selectivities based on single-component adsorption data. We performed the first large-scale molecular simulation study to investigate separation performances of 174 different MOF structures for C2H2/CO2 and C2H2/CH4 mixtures. Using the results of molecular simulations, several adsorbent performance evaluation metrics, such as selectivity, working capacity, adsorbent performance score, sorbent selection parameter, and regenerability were computed for each MOF. Based on these metrics, the best adsorbent candidates were identified for both separations. Results showed that the top three most promising MOF adsorbents exhibit C2H2/CO2 selectivities of 49, 47, 24 and C2H2/CH4 selectivities of 824, 684, 638 at 1 bar, 298 K and these are the highest C2H2 selectivities reported to date in the literature. Structure-performance analysis revealed that the best MOF adsorbents have pore sizes between 4 and 11 Å, surface areas in the range of 600–1,200 m2/g and porosities between 0.4 and 0.6 for selective separation of C2H2 from CO2 and CH4. These results will guide the future studies for the design of new MOFs with high C2H2 separation potentials.

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Nemati Vesali Azar, A., & Keskin, S. (2018). Computational Screening of MOFs for Acetylene Separation. Frontiers in Chemistry, 6. https://doi.org/10.3389/fchem.2018.00036

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