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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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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
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author Taherkhani, Samira
Darvishmotevalli, Mohammad
Karimyan, Kamaleddin
Bina, Bijan
Fallahi, Adibeh
Karimi, Hossein
author_facet Taherkhani, Samira
Darvishmotevalli, Mohammad
Karimyan, Kamaleddin
Bina, Bijan
Fallahi, Adibeh
Karimi, Hossein
author_sort Taherkhani, Samira
collection PubMed
description 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.
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spelling pubmed-61411472018-09-18 Dataset on photodegradation of tetracycline antibiotic with zinc stannate nanoflower in aqueous solution – Application of response surface methodology Taherkhani, Samira Darvishmotevalli, Mohammad Karimyan, Kamaleddin Bina, Bijan Fallahi, Adibeh Karimi, Hossein Data Brief Environmental Science 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. Elsevier 2018-06-22 /pmc/articles/PMC6141147/ /pubmed/30229073 http://dx.doi.org/10.1016/j.dib.2018.06.030 Text en © 2018 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Environmental Science
Taherkhani, Samira
Darvishmotevalli, Mohammad
Karimyan, Kamaleddin
Bina, Bijan
Fallahi, Adibeh
Karimi, Hossein
Dataset on photodegradation of tetracycline antibiotic with zinc stannate nanoflower in aqueous solution – Application of response surface methodology
title Dataset on photodegradation of tetracycline antibiotic with zinc stannate nanoflower in aqueous solution – Application of response surface methodology
title_full Dataset on photodegradation of tetracycline antibiotic with zinc stannate nanoflower in aqueous solution – Application of response surface methodology
title_fullStr Dataset on photodegradation of tetracycline antibiotic with zinc stannate nanoflower in aqueous solution – Application of response surface methodology
title_full_unstemmed Dataset on photodegradation of tetracycline antibiotic with zinc stannate nanoflower in aqueous solution – Application of response surface methodology
title_short Dataset on photodegradation of tetracycline antibiotic with zinc stannate nanoflower in aqueous solution – Application of response surface methodology
title_sort dataset on photodegradation of tetracycline antibiotic with zinc stannate nanoflower in aqueous solution – application of response surface methodology
topic Environmental Science
url 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
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