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Autor(en) / Beteiligte
Relating transport modeling to nanofiltration membrane fabrication: Navigating the permeability-selectivity trade-off in desalination pretreatment
Ist Teil von
  • Journal of membrane science, 2018-05, Vol.554, p.26-38
Ort / Verlag
Elsevier B.V
Link zum Volltext
Elsevier ScienceDirect Journals Complete
  • Faced with a pressing need for membranes with a higher permeability and selectivity, the field of membrane technology can benefit from a systematic framework for designing membranes with the necessary physical characteristics. In this work, we present an approach through which transport modeling is employed in fabricating specialized nanofiltration membranes, that experimentally demonstrate enhanced selectivity. Specifically, the Donnan-Steric Pore Model with dielectric exclusion (DSPM-DE) is used to probe for membrane properties desirable in desalination pretreatment. Nanofiltration membranes are systematically fabricated in-house using layer-by-layer (LbL) deposition to validate model predictions and to develop a new specialized membrane for this application. The new membrane presents a 30% increase in permeability and a 50% reduction in permeate hardness relative to state-of-the-art NF membranes. Our results indicate that a ‘specialized’ tight membrane can outperform looser counterparts in both permeability and selectivity. Given the possibility of extending this framework to other applications, the work furthers our understanding of the relationships governing membrane form and function, while having broad potential implications for future nanofiltration membranes used in chemical separation and purification. [Display omitted] •Modeling can probe for membrane properties desirable in desalination pretreatment.•Nanofiltration membranes are systematically prepared to validate model predictions.•Pore size affects rejection & selectivity more than membrane charge or thickness.•New membrane achieves 30% higher permeability and 50% lower permeate hardness.
ISSN: 0376-7388
eISSN: 1873-3123
DOI: 10.1016/j.memsci.2018.02.053
Titel-ID: cdi_crossref_primary_10_1016_j_memsci_2018_02_053

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