Molecular transport through mixed matrix membranes: A time-dependent density functional approach

AIChE Journal ◽  
2017 ◽  
Vol 63 (10) ◽  
pp. 4586-4594 ◽  
Author(s):  
Yu Liu ◽  
Fangyuan Guo ◽  
Jun Hu ◽  
Honglai Liu ◽  
Ying Hu
Keyword(s):  
Density Functional ◽  
Molecular Transport ◽  
Functional Approach ◽  
Time Dependent ◽  
Mixed Matrix Membranes ◽  
Mixed Matrix ◽  
Dependent Density ◽  
Matrix Membranes

scholarly journals Symbiosis-inspired de novo synthesis of ultrahigh MOF growth mixed matrix membranes for sustainable carbon capture

2021 ◽  
Vol 119 (1) ◽  
pp. e2114964119
Author(s):  
Shanshan He ◽  
Bin Zhu ◽  
Xu Jiang ◽  
Gang Han ◽  
Songwei Li ◽  
...  
Keyword(s):  
Carbon Capture ◽  
Density Functional ◽  
De Novo ◽  
Metal Organic Framework ◽  
Gas Diffusion ◽  
Mixed Matrix Membranes ◽  
Synthesis Methods ◽  
Mixed Matrix ◽  
Interfacial Compatibility ◽  
Matrix Membranes

Mixed matrix membranes (MMMs) are one of the most promising solutions for energy-efficient gas separation. However, conventional MMM synthesis methods inevitably lead to poor filler–polymer interfacial compatibility, filler agglomeration, and limited loading. Herein, inspired by symbiotic relationships in nature, we designed a universal bottom-up method for in situ nanosized metal organic framework (MOF) assembly within polymer matrices. Consequently, our method eliminating the traditional postsynthetic step significantly enhanced MOF dispersion, interfacial compatibility, and loading to an unprecedented 67.2 wt % in synthesized MMMs. Utilizing experimental techniques and complementary density functional theory (DFT) simulation, we validated that these enhancements synergistically ameliorated CO2 solubility, which was significantly different from other works where MOF typically promoted gas diffusion. Our approach simultaneously improves CO2 permeability and selectivity, and superior carbon capture performance is maintained even during long-term tests; the mechanical strength is retained even with ultrahigh MOF loadings. This symbiosis-inspired de novo strategy can potentially pave the way for next-generation MMMs that can fully exploit the unique characteristics of both MOFs and matrices.

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