Screening PIM-1 performance as a membrane for binary mixture separation of gaseous organic compounds
Developing microporous polymeric membranes for the separation of a diverse set of organic species can have a profound impact on many industrial fields. This study reports data for unary/binary adsorption and membrane separation performance for acetaldehyde, acetone, methane, methanethiol, propane, a...
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Veröffentlicht in: | Journal of membrane science 2020-04, Vol.599 (C), p.117798, Article 117798 |
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Sprache: | eng |
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Zusammenfassung: | Developing microporous polymeric membranes for the separation of a diverse set of organic species can have a profound impact on many industrial fields. This study reports data for unary/binary adsorption and membrane separation performance for acetaldehyde, acetone, methane, methanethiol, propane, and propene studied with PIM-1. The data is reported at 300 K for the pure gases, 15 unique binary pairs, and at 3 molar fractions (45 pairs in all), which required a total of 2633 independent simulations. Based on the potential complexities associated with binary adsorption processes, we describe a statistical approach that can be broadly applicable in identifying system equilibration and overall contribute to predictions with increased fidelity, enabling high-throughput screening. We provide correlations from available experimental porous polymer data that can predict diffusivity as a function of the membrane fractional free volume for propane and propene. Using these results, several PIM-1 binary mixture membrane performance metrics, such as permselectivity, are reported for paraffin/olefin separation. These relations are essential for experimental and computational studies because they allow researchers to assess gas diffusivity/permeability results while avoiding expensive methods needed to otherwise quantify gas transport.
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•6 pure and 45 binary simulated isotherms are reported for gaseous organic compounds.•A statistical method increases the fidelity of predictions from screening studies.•Diffusivity correlations enable analysis of hydrocarbon separation performance. |
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ISSN: | 0376-7388 1873-3123 |
DOI: | 10.1016/j.memsci.2019.117798 |