Abstract
In this study, novel thin-film nanocomposite (TFN) membranes were developed by incorporating graphene oxide (GO) and Aquaporin Z (AqpZ) reconstituting nanostructure (AQN) into the polyamide (PA) active layer to improve the forward osmosis (FO) performances of the PA TFN membranes. First, the AQN loading in the PA layer was optimized, followed by the GO addition in PA layer at various loadings until the optimal FO process performance was attained. Experimental results showed that GO flakes increased membrane water flux but decreased selectivity by creating non-selective voids in PA layer. Whereas, AQN increased membrane selectivity by healing the non-selective PA defects created by the GO flakes. The synergistic effect of GO-AQN improved the water flux without deteriorating the selectivity of the membrane. The TFN membrane with 0.2 wt% AQN and 0.005 wt% GO loading (TFN50) showed almost 3 folds increase in water flux (24.1 L·m−2·h−1) in comparison to the TFC membrane (8.2 L·m−2·h−1), while retaining the membrane selectivity (0.37 g.L−1). Interestingly, the TFN50 membrane demonstrated a 27% lower specific reverse salt flux (SRSF) and a marginal increase in water flux than the TFN membrane embedded with 0.005 wt% GO and no AQN (TFNGO50). The overall experimental results confirmed that the addition of AQN into GO-based PA TFN membranes could improve the membrane selectivity by reducing the non-selective PA defects created by GO flakes. The results of this study could provide strategies to further enhance the selectivity of GO-based TFN membranes by preventing the formation of defective PA layer.
Original language | English (US) |
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Pages (from-to) | 114795 |
Journal | Desalination |
Volume | 498 |
DOIs | |
State | Published - Jan 2021 |
Externally published | Yes |
Bibliographical note
KAUST Repository Item: Exported on 2021-02-16Acknowledged KAUST grant number(s): CRG2017, URF/1/3404-01
Acknowledgements: The research reported in this paper was supported by the ARC Industrial Transformation Research Hub (IH170100009), Australia and the King Abdullah University of Science and Technology (KAUST), Saudi Arabia through the Competitive Research Grant Program–CRG2017 (CRG6), Grant #URF/1/3404-01.
This publication acknowledges KAUST support, but has no KAUST affiliated authors.