Computational Screening of Metal-Organic Frameworks for Ethylene Purification from Ethane/Ethylene/Acetylene Mixture

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Abstract

Identification of high-performing sorbent materials is the key step in developing energyefficient adsorptive separation processes for ethylene production. In this work, a computational screening of metal-organic frameworks (MOFs) for the purification of ethylene from the ternary ethane/ethylene/acetylene mixture under thermodynamic equilibrium conditions is conducted. Modified evaluation metrics are proposed for an efficient description of the performance of MOFs for the ternary mixture separation. Two different separation schemes are proposed and potential MOF adsorbents are identified accordingly. Finally, the relationships between the MOF structural characteristics and its adsorption properties are discussed, which can provide valuable information for optimal MOF design.

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Zhou, Y., Zhang, X., Zhou, T., & Sundmacher, K. (2022). Computational Screening of Metal-Organic Frameworks for Ethylene Purification from Ethane/Ethylene/Acetylene Mixture. Nanomaterials, 12(5). https://doi.org/10.3390/nano12050869

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