Abstract
A well-functioning membrane such as high rejection efficiency and high flux rate is indeed the main goal in a study. In fact, so many studies on the factors that affect the membrane are carried out, such as pressure rate, polymer type, additive type, temperature effect during fabrication and so on. Therefore, the development of analytical modeling is vital to predict the optimal performance in good membrane production. Therefore, in this study, the main objective is to develop analytical modeling using Response Surface (RS) methodology for Sodium Dodecyl Sulfate (SDS) surfactant membrane, and also to determine the factors used such as polymer concentration and dye concentration in the experiment is statistically significant. The performance selected in this study were the rejection efficiency and the flux rate. Through the choice of Central Composite Design (CCD) that have been selected from the RS methodology, analytical modeling has been made through the development of an experimental framework that will be used to collect input. Modeling from the RS methodology will provide insights to predict the relationship between response parameters as well as statistically significant factors between input and output. Through the experimental data collected, the data were processed through ANOVA to determine the statistical validation of the adopted RS methodology. From the results of the experiments, the highest rejection efficiency and flux rate were 99.3% and 43.962 (L.m2 / h), respectively. 3D graphs, 2d contours, and equations for rejection efficiency and flux rate were developed as a result of analysis of Variance (ANOVA). Membrane surface morphology was analysed using Scanning Electron Microscopy (SEM) in determining membrane structures such as macrovoids, finger-like and spongy.
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More From: IOP Conference Series: Earth and Environmental Science
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