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Treatment of direct black 22 azo dye in led reactor using ferrous sulfate and iron waste for Fenton process: reaction kinetics, toxicity and degradation prediction by artificial neural networks

Rayssa K. M. Gomes, Rayany M. R. Santana, Nathália F. S. de Moraes, Sérgio G. Santos Júnior, Alex L. A. de Lucena, Léa E. M. C. Zaidan, Diego R. M. Elihimas, and Daniella C. Napoleão

Universidade Federal de Pernambuco, Recife, Brazil



Received: 23 October 2020  Accepted: 23 November 2020


Due to the low efficiency of physical–chemical treatments, advanced oxidative processes (AOP) appear as an efficient treatment alternative for removing organic compounds. To replace some of the reagents used in the photo-Fenton AOP with low-cost materials, the present study evaluated the degradation of direct black dye 22 (DB22) under LED radiation in a homogeneous and heterogeneous medium (iron residue). The best treatments operational conditions were determined and kinetic study was carried out. Then, artificial neural networks (ANN) were used to predict the processes' degradation behavior. In addition, toxicity tests were performed with seeds and bacteria. The homogeneous treatment reached DB22 total degradation after 120 min (2 mg L−1 of Fe, pH between 3–4 and 80 mg L−1 of H2O2) and the same result was obtained for the heterogeneous process after 480 min (0.5 g L−1 of RFe, granulometric range of < 0.15 mm, pH between 3–4 and 120 mg L−1 of H2O2). Experimental data from both treatments also showed goodness of fit to kinetic models (R2 > 0.97). Furthermore, the toxicity tests indicated that the homogeneous process was the least aggressive to the species of seeds and the bacterial strains. The obtained results also allowed an efficient prediction of degradation through ANN application for both processes. Finally, the study showed that the application of heterogeneous photo-Fenton AOP using LED radiation and iron residue as the catalyst proved to be a cheap and effective alternative in the degradation of the dye, which indicates the possibility of its application on a large scale, improving the quality of the effluents released by the textile industry, without excessively increasing the cost of the process.

Keywords: AOP; Catalyst; Iron residue; Mathematical modeling; LED radiation

Full paper is available at

DOI: 10.1007/s11696-020-01451-4


Chemical Papers 75 (5) 1993–2005 (2021)

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