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.
Highlights
response surface methodology (RSM) integrating mathematics with statistics has been widely utilized to investigate, optimize and model the performance of complex systems, which can determine the significant factors affecting an experiment initiating from the design of experiment (DOE)
The RSM has been widely used in designing experiments, developing regression models and determining optimal variables in chemical, physical, biological and environmental processes [1]; as far as we are concerned, few studies have been conducted on the optimizing and modeling of the interaction effects of the synthetic parameters of a mixed matrix cation exchange membrane (MMCEMs)
It was necessary to test the stability of the Metal organic frameworks (MOFs) in a water, weak acid and alkaline environment in order to verify the feasibility of the synthesized MOFs used in the water treatment process
Summary
RSM integrating mathematics with statistics has been widely utilized to investigate, optimize and model the performance of complex systems, which can determine the significant factors affecting an experiment initiating from the design of experiment (DOE). It aims at reducing the number of experimental runs while maximizing output through the data generated. The RSM has been widely used in designing experiments, developing regression models and determining optimal variables in chemical, physical, biological and environmental processes [1]; as far as we are concerned, few studies have been conducted on the optimizing and modeling of the interaction effects of the synthetic parameters of a mixed matrix cation exchange membrane (MMCEMs)
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