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◆ International journal of molecular sciences2026-07-24

Visible Light-Activated Persulfates Towards Dyes Decolorization: Performance, Kinetics, and Statistical Optimization.

Piotr Zawadzki, Łukasz Pierzchała

原始摘要(英文原文)· Original abstract
This article aims to investigate the effects of operational factors on methylene blue (MB) decolorization in a visible light advanced oxidation process (AOP). Response surface methodology was applied to evaluate variable interactions and identify the best operational conditions of the process. The response surface analysis of the expected increase in methylene blue decolorization at different levels of the variable parameters was employed. The experiment evaluated the influence of the following parameters: pH, glucose dose, Na2S2O8 (SPS) concentration, and initial dye concentration. The model confirmed that the optimal conditions for MB decolorization in the visible light-driven advanced oxidation process were: SPS dose = 30 mM, glucose dose = 230 mM, pH = 4. The highest decolorization level was obtained at a concentration of C0[MB] = 5 ppm (R = 63%). The kinetics of the process followed pseudo-first-order (R2 = 97-99%). The radical scavenger test showed that both sulfate and hydroxy radicals are involved in MB decolorization. The test confirmed that the proposed method is effective even at a broad range of MB concentrations (1-10 ppm). The analysis showed that the proposed method is highly efficient across various dye concentrations, which is particularly significant from a practical perspective. Summarizing, this study fills a research gap in the optimization of methylene blue decolorization within the scope of advanced oxidation processes driven by visible light and glucose, demonstrating high efficiency across a range of different environmental variables. The study showed that the SPS/Vis/glucose process can serve as a valuable alternative to conventional decolorization methods.
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Visible Light-Activated Persulfates Towards Dyes Decolorization: Performance, Kinetics, and Statistical Optimization. — 科研速览 Science Skim