The effect of Schiff base network on the separation performance of thin film nanocomposite forward osmosis membranes

Nawshad Akther, Sungil Lim, Van Huy Tran, Sherub Phuntsho, Yanqin Yang, Tae-Hyun Bae, NorEddine Ghaffour, Ho Kyong Shon

Research output: Contribution to journalArticlepeer-review

23 Scopus citations

Abstract

In this study, Schiff base network-1 (SNW-1) nanoparticles, which are covalent organic frameworks (COFs), were used as fillers in the polyamide (PA) active layer to elevate the performance of thin-film nanocomposite (TFN) forward osmosis (FO) membranes. The TFN membranes were prepared by interfacial polymerization (IP) of m-phenylenediamine (MPD) and trimesoyl chloride (TMC), and the SNW-1 nanoparticles were dispersed in the MPD aqueous solution at various concentrations. The secondary amine groups of SNW-1 nanoparticles reacted with the acyl chloride groups of TMC during the IP reaction to form strong covalent/amide bonds, which facilitated better interface integration of SNW-1 nanoparticles in the PA layer. Additionally, the incorporation of amine-rich SNW-1 nanoparticles into the TFN membranes improved their surface hydrophilicity, and the porous structure of SNW-1 nanoparticles offered additional channels for transport of water molecules. The TFN0.005 membrane with a SNW-1 nanoparticle loading of 0.005 wt.% demonstrated a higher water flux than that of pristine TFC membrane in both AL-FS (12.0 vs. 9.3 Lm-2h-1) and AL-DS (25.2 vs. 19.4 Lm-2h-1) orientations when they were tested with deionized water and 0.5 M NaCl as feed and draw solution, respectively.
Original languageEnglish (US)
Pages (from-to)284-293
Number of pages10
JournalSeparation and Purification Technology
Volume217
DOIs
StatePublished - Feb 16 2019

Bibliographical note

KAUST Repository Item: Exported on 2021-02-19
Acknowledged KAUST grant number(s): URF/1/3404-01
Acknowledgements: The research conveyed in this paper was supported by King Abdullah University of Science and Technology (KAUST), Saudi Arabia, through the Competitive Research Grant Program – CRG2017 (CRG6), Grant # URF/1/3404-01.

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