Computational Methods for MOF/Polymer Membranes. Issue 2 (4th February 2016)

• Record Type: Journal Article
• Authors: Erucar, Ilknur; Keskin, Seda
• Is Part Of: Chemical record. Volume 16:Issue 2(2016)
• Page Start: 703
• Page End: 718
• Publication Date: 2016-02-04
• Subjects: computational chemistry -- gas separation -- membranes -- metal–organic frameworks -- polymers; Chemistry -- Periodicals; 540
• DOI: 10.1002/tcr.201500275
• Languages: English
• ISSNs: 1527-8999

Abstract

Abstract: Metal–organic framework (MOF)/polymer mixed matrix membranes (MMMs) have received significant interest in the last decade. MOFs are incorporated into polymers to make MMMs that exhibit improved gas permeability and selectivity compared with pure polymer membranes. The fundamental challenge in this area is to choose the appropriate MOF/polymer combinations for a gas separation of interest. Even if a single polymer is considered, there are thousands of MOFs that could potentially be used as fillers in MMMs. As a result, there has been a large demand for computational studies that can accurately predict the gas separation performance of MOF/polymer MMMs prior to experiments. We have developed computational approaches to assess gas separation potentials of MOF/polymer MMMs and used them to identify the most promising MOF/polymer pairs. In this Personal Account, we aim to provide a critical overview of current computational methods for modeling MOF/polymer MMMs. We give our perspective on the background, successes, and failures that led to developments in this area and discuss the opportunities and challenges of using computational methods for MOF/polymer MMMs. Abstract : Metal–organic framework (MOF)/polymer mixed matrix membranes (MMMs) combine the excellent gas permeability and selectivity of MOFs with the easy processability of polymers. There has been a large demand for computational studies that can accurately predict the gas separation performance of MOF/polymer MMMs prior to experiments. In this Personal Account, we review the current computational approaches for modeling MOF‐based MMMs and discuss the strategies to identify the most promising MOF/polymer pairs for specific gas separations.