Adsorption of U(VI) from aqueous solution by using KMnO4-modified hazelnut shell activated carbon: characterisation and artificial neural network modelling

This study is based on U(VI) removal from wastewater by KMnO 4 -modified hazelnut shell activated carbon (KM–HSAC) using adsorption technology. A characterisation study of KM–HSAC was conducted through scanning electron microscope and energy-dispersive X-ray spectroscopy (EDS) analysis. The rough su...

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Bibliographic Details
Published in:Environmental science and pollution research international 2021-09, Vol.28 (34), p.47354-47366
Main Authors: Zhu, Mijia, Li, Fanxiu, Chen, Wu, Yin, Xianqing, Yi, Zhengji, Zhang, Shuyong
Format: Article
Language:English
Subjects:
Activated carbon
Adsorption
Aquatic Pollution
Aqueous solutions
Artificial neural networks
Atmospheric Protection/Air Quality Control/Air Pollution
Earth and Environmental Science
Ecotoxicology
Electron microscopes
Environment
Environmental Chemistry
Environmental Health
Environmental science
Hazelnuts
Microspores
Neural networks
Potassium permanganate
Research Article
Root-mean-square errors
Scanning electron microscopy
Statistical analysis
Training
Waste Water Technology
Wastewater
Wastewater treatment
Water Management
Water Pollution Control
X-ray spectroscopy
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Summary:This study is based on U(VI) removal from wastewater by KMnO 4 -modified hazelnut shell activated carbon (KM–HSAC) using adsorption technology. A characterisation study of KM–HSAC was conducted through scanning electron microscope and energy-dispersive X-ray spectroscopy (EDS) analysis. The rough surface of KM–HSAC contains many irregular microspores. The EDS pattern confirmed the U(VI) adsorption on the KM–HSAC. A batch study experiment gave optimum results for U(VI) at pH 6, contact time of 160 min, initial U(VI) concentration of 155.56 mg/L and KM–HSAC dosage of 4 g/L, with a maximum adsorption capacity of 22.27 mg/g. The prediction performance of artificial neural network models was validated through the low values of statistical error (2.708 and 8.241 for RMSE of training and testing data, respectively) and the high determination coefficient value (0.987 and 0.906 for training and testing data, respectively). Experimental results suggest that KM–HSAC has a high potential for the removal of U(VI) from wastewater.
ISSN:0944-1344
1614-7499
DOI:10.1007/s11356-021-14034-x