Surface facet Fe2O3-based visible light photocatalytic activation of persulfate for the removal of RR120 dye: nonlinear modeling and optimization
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Photocatalytic activation of persulfate (PS) is recently emerged as an energy-efficient and environmentally sustainable approach for pollutants degradation, which enables to leverage the strengths of low-cost solar energy and heterogeneous catalysis. Herein, we investigated the photocatalytic decomposition of reactive red 120 (RR120) dye using PS-activated Fe2O3 nanoparticles and elucidated the effect of their facets, α–Fe2O3 (001), β–Fe2O3 (100), and γ–Fe2O3 (111). β–Fe2O3 not only boosted the charge carrier separation but also provided more active sites for PS activation resulting in 6- and 3.5-fold higher photocatalytic activities compared to α–Fe2O3 and γ–Fe2O3, respectively. Response surface methodology and artificial neural network coupled with genetic algorithm models were utilized to optimize and foresee Fe2O3/PS system under visible light. Almost 100% color removal and 82% organic removal were observed under the optimum conditions at 20 mg/L RR120, 22 mg/L β–Fe2O3, 18 mg/L PS, and pH: 3. Scavenger test indicated that both sulfate and hydroxyl radicals are responsible for the observed RR120 removal. Although cell viability test indicated that cytotoxicity of wastewater is not significantly reduced after treatment. All the results proposed that β–Fe2O3/PS at relatively low doses has a great potential to decompose and mineralize recalcitrant dyes in wastewater under invisible light.
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Artificial neural network, Facet engineering, Fe2O3 photocatalyst, Persulfate activation, Response surface methodology
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Environmental Science and Pollution Research.
