ArticleMembranes2022
Fabrication of a Cation-Exchange Membrane via the Blending of SPES/N-Phthaloyl Chitosan/MIL-101(Fe) Using Response Surface Methodology for Desalination.
Article in Membranes, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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2 citing papers in PubMed, 13 citations in OpenAlex.
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10 authors at 5 institutions in 1 country.
Funding
Abstract
In the present work, a novel mixed matrix cation exchange membrane composed of sulfonated polyether sulfone (SPES), N-phthaloyl chitosan (NPHCs) and MIL-101(Fe) was synthesized using response surface methodology (RSM). The electrochemical and physical properties of the membrane, such as ion exchange capacity, water content, morphology, contact angle, fixed ion concentration and thermal stability were investigated. The RSM based on the Box-Behnken design (BBD) model was employed to simulate and evaluate the influence of preparation conditions on the properties of CEMs. The regression model was validated via the analysis of variance (ANOVA) which exhibited a high reliability and accuracy of the results. Moreover, the experimental data have a good fit and high reproducibility with the predicted results according to the regression analysis. The embedding of MIL-101(Fe) nanoparticles contributed to the improvement of ion selective separation by forming hydrogen bonds with the polymer network in the membrane. The optimum synthesis parameters such as degree of sulfonation (DS), the content of SPES and NPHCs and the content of MIL-101(Fe) were acquired to be 30%, 85:15 and 2%, respectively, and the corresponding desalination rate of the CEMs improved to 136% while the energy consumption reduced to 90%. These results revealed that the RSM was a promising strategy for optimizing the preparation factors of CEMs and other similar multi-response optimization studies.
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