CO2/CH4 mixed-gas separation in PIM-1 at high pressures: Bridging atomistic simulations with process modeling
KAUST DepartmentChemical Engineering Program
Advanced Membranes and Porous Materials Research Center
Physical Science and Engineering (PSE) Division
Online Publication Date2021-09-08
Print Publication Date2021-12
Embargo End Date2023-09-01
Permanent link to this recordhttp://hdl.handle.net/10754/671169
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AbstractPolymeric membranes with intrinsic microporosity have been at the center of attention for gas separation applications since the introduction of PIM-1. This study utilizes atomistic simulations to model and to understand the pure- and mixed-gas transport properties of PIM-1 for the CO2/CH4 gas pair. Monte Carlo and molecular dynamics methods were combined in the estimation of sorption and diffusion of CO2 and CH4 in PIM-1. Simulated sorption and permeability data compared very well with experimental reports. Mixed-gas adsorption simulations proved the existence of competitive adsorption, favoring CO2, hence resulting in an increase in solubility selectivities. However, in mixed-gas environment CH4 permeabilities increased significantly compared to pure gas conditions, overall decreasing perm-selectivities of the polymer. Plasticization of the polymer around 25 bar CO2 partial fugacity was apparent both in pure- and mixed-gas conditions. Simulations at different gas feed compositions proved the dependence of competitive sorption and CO2-induced swelling in partial feed gas fugacities. Simulation results were combined to obtain a macroscopic permeability model that relates the multicomponent permeability to the permeate pressure and composition. Accurate estimations of permeabilities by the model were achieved allowing future implementation of the model in process simulation tools.
CitationBalçık, M., Tantekin-Ersolmaz, S. B., Pinnau, I., & Ahunbay, M. G. (2021). CO2/CH4 mixed-gas separation in PIM-1 at high pressures: Bridging atomistic simulations with process modeling. Journal of Membrane Science, 119838. doi:10.1016/j.memsci.2021.119838
SponsorsThis work was supported by the Scientific Projects Unit of Istanbul Technical University (Grant # MDK-2018-41400) and the Scientific and Technological Research Council of Turkey-TUBITAK (Grant #217M630). Computing resources used in this work were provided by the National Center for High Performance Computing of Turkey (UHeM) under grant # 1003032013.
JournalJournal of Membrane Science