Optimization of iron-ZIF-8 catalysts for degradation of tartrazine in water by Fenton-like reaction

• Tipo: Artigo em Revista Científica Internacional
• Data: 2023

Autores

Assila, O (Autor) Outra; Vilaça, N (Autor) Outra; Bertão, R (Autor) Outra; Fonseca, M (Autor) Outra; Parpot, P (Autor) Outra; O.S.G.P. Soares (Autor) FEUP; Manuel Fernando R Pereira (Autor) FEUP; Baltazar, F (Autor) Outra; Bañobre López, M (Autor) Outra; Neves, C (Autor) Outra

Revista

Título: Chemosphere

Vol. 339

ISSN: 0045-6535

Editora: Elsevier

Indexação

Scopus - 0 Citações

Outras Informações

ID Authenticus: P-00Y-W1Y

DOI: 10.1016/j.chemosphere.2023.139634

Abstract (EN): Optimization of iron zeolitic imidazole framework-8 (FeZIF-8) nanoparticles, as heterogeneous catalysts, were synthesized and evaluated by the Fenton-like reaction for to degrade tartrazine (Tar) in aqueous environment. To achieve this, ZIF-8 nanoparticles were modified with different iron species (Fe2+ or Fe3O4), and subsequently assessed through the Fenton-like oxidation. The effect of different parameters such as the concentration of hydrogen peroxide, the mass of catalyst and the contact time of reaction on the degradation of Tar by Fenton-like oxidation was studied by using the Box-Behnken design (BBD). The BBD model indicated that the optimum catalytic conditions for Fenton-like reaction with an initial pollutant concentration of 30 ppm at pH 3.0 were T = 40 °C and 12 mM of H2O2, 2 g/L of catalyst and 4 h of reaction. The maximum Tar conversion value achieved with the best catalyst, Fe1ZIF-8, was 66.5% with high mineralization (in terms of decrease of total organic carbon ¿ TOC), 44.2%. To assess phytotoxicity, the germination success of corn kernels was used as an indicator in the laboratory. The results show that the catalytic oxidation by Fenton-like reaction using heterogeneous iron ZIF-8 catalysts is a viable alternative for treating contaminated effluents with organic pollutants and highlighted the importance of the validation of the optimized experimental conditions by mathematical models. © 2023 The Authors

Idioma: Inglês

Tipo (Avaliação Docente): Científica