4.7 Article

CO2/CH4 mixed gas separation using poly(ether-b-amide)-ZnO nanocomposite membranes: Experimental and molecular dynamics study

期刊

POLYMER TESTING
卷 86, 期 -, 页码 -

出版社

ELSEVIER SCI LTD
DOI: 10.1016/j.polymertesting.2020.106464

关键词

PEBA-ZnO mixed matrix membrane; Gas separation; CO2/CH4 selectivity; GCMC simulation; MD simulation

资金

  1. Research & Technology Directorate at National Iranian Gas Company (NIGC) of Iran and Energy Research Institute at the University of Kashan

向作者/读者索取更多资源

Poly (ether-b-amide) (PEBA) mixed matrix membranes (MMMs) filled by different amounts of nano ZnO (up to 1 wt %) were synthesized and their gas separation performance was evaluated for CO2, CH4 and N-2 pure gas and their binary mixtures. The ZnO-filled PEBA MMMs were characterized using ATR-FTIR, FESEM, AFM, TGA, DMTA, XRD and Mechanical tensile strength analyses. Generally, it was revealed that 0.5 wt % loading of ZnO into the polymer matrix caused a ZnO-PEO interaction; while ZnO-ZnO self-association hindered the interaction for the MMMs with other loadings of ZnO. As a result, PEBA-ZnO 0.5 wt % MMM possessed a higher glass transition temperature (T-g). Therefore, the CO2 permeability through PEBA-ZnO 0.5 wt % enhanced 27% than simple PEBA membrane. Moreover, all the fabricated MMMs were simulated by molecular simulation. Grand Canonical Monte Carlo (GCMC) and Molecular Dynamics (MD) methods were also applied to simulate the structural and gas transport properties of the membranes. The RDF, XRD, T-g, FFV and density analysis were compared with experimental results. Also, a binary mixture of CO2:CH4 (10:90) was used to determine CO2 permeability and CO2/CH4 selectivity, which were considerably reduced compared to single gas experiments. Moreover, the solubility of the binary gas mixture, the energy distribution and density distribution of both gases within the simulated cell were calculated by molecular simulation.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据