期刊
JOURNAL OF APPLIED POLYMER SCIENCE
卷 139, 期 15, 页码 -出版社
WILEY
DOI: 10.1002/app.51953
关键词
asymmetric; carbon nanotube; dehydration; electrospinning; pervaporation
资金
- Universiti Sains Malaysia [1001/PJKIMIA/8014092]
This study developed an asymmetric membrane using electrospun carboxyl-functionalised multi-walled carbon nanotube/polyvinyl alcohol composite nanofibers on a dense PVA layer, resulting in significantly improved pervaporation performance. The membrane showed nearly 80% increase in water permeation flux and enhanced separation factor. The parameters from the Rautenbach model demonstrated that the pervaporation process is controlled by sorption, with good agreement between experimental and predicted data.
This study focuses on the development of an asymmetric membrane comprised of an electrospun carboxyl-functionalised multi-walled carbon nanotube (COOH-MWCNT)/poly (vinyl alcohol) (PVA) composite nanofibre layer on a dense PVA separation layer (MCOOH-MWCNT). The electrospun nanofibre layer in this study acts as a pre-selective layer instead of its common function as a membrane support. In addition, COOH-MWCNT, a hydrophilic filler is integrated in the nanofibres to further enhance the membrane pervaporation separation performance. Immense improvement was observed in the pervaporation performance of the resultant asymmetric membranes in the dehydration of aqueous 1,4-dioxane solutions, owing to the presence of the electrospun composite nanofibres as a hydrophilic layer. The resultant asymmetric membrane showed an increase of nearly 80% in water permeation flux as compared to that of the dense PVA membrane alone, and the separation factor was improved from 392.65 to 605.35. The parameters estimated using Rautenbach model showed that the dehydration of aqueous 1,4-dioxane solutions via pervaporation is dominantly governed by sorption process. The permeation flux, transport coefficient of water and 1,4-dioxane of the electrospun asymmetric membrane showed a good agreement in between the experimental data and those predicted using Rautenbach model.
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