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Dataset on photodegradation of tetracycline antibiotic with zinc stannate nanoflower in aqueous solution – Application of response surface methodology

Removal of pharmaceutical ingredients such as tetracycline from aqueous solution has a great importance. The aim of the current study was to investigate the degradation of tetracycline antibiotic in the presence of a triode semiconductor oxide as well as modeling of the photocatalytic degradation pr...

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Detalles Bibliográficos
Autores principales: Taherkhani, Samira, Darvishmotevalli, Mohammad, Karimyan, Kamaleddin, Bina, Bijan, Fallahi, Adibeh, Karimi, Hossein
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6141147/
https://www.ncbi.nlm.nih.gov/pubmed/30229073
http://dx.doi.org/10.1016/j.dib.2018.06.030
Descripción
Sumario:Removal of pharmaceutical ingredients such as tetracycline from aqueous solution has a great importance. The aim of the current study was to investigate the degradation of tetracycline antibiotic in the presence of a triode semiconductor oxide as well as modeling of the photocatalytic degradation process in order to determine optimal condition Zinc stannate nanoflower (Zn(2)SnO(4)) was synthesized by hydrothermal process and characterized by X-ray diffraction (XRD), Fourier transform infrared (FT-IR), and scanning electron microscopy (SEM) techniques. Response surface methodology (RSM) was used to model and optimize four key independent variables, including photocatalyst dosage, initial concentration of tetracycline antibiotic (TC) as model pollutant, pH and reaction time of photocatalytic degradation. The proposed quadratic model was in accordance with the experimental results with a correlation coefficient of 98%. The obtained optimal experimental conditions for the photodegradation process were the following: zinc stannate (ZTO) dosage=300 mg L(-1), initial concentration of TC= 10 mg L(-1), reaction time= 100 min and pH=4.5. Under the optimal conditions, the predicted degradation efficiency was 95.45% determined by the proposed model. In order to evaluate the accuracy of the optimization procedure, the confirmatory experiment was carried out under the optimal conditions and the degradation efficiency of 93.54% was observed, which closely agreed with the predicted value.