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Removal of inorganic contaminant phosphate from aqueous solutions by bimetallic Ficus-ZVFe/Cu nanoparticles
被引:5
作者
:
Abdel-Aziz, Hossam Mohammed
论文数:
0
引用数:
0
h-index:
0
机构:
Chemical Industries Development (CID) Company, Giza, Egypt
Chemical Industries Development (CID) Company, Giza, Egypt
Abdel-Aziz, Hossam Mohammed
[
1
]
Farag, Rabie Saad
论文数:
0
引用数:
0
h-index:
0
机构:
Chemistry Department, Faculty of Science, Al-Azhar University, Cairo, Egypt
Chemical Industries Development (CID) Company, Giza, Egypt
Farag, Rabie Saad
[
2
]
Abdel-Gawad, Soha Ali
论文数:
0
引用数:
0
h-index:
0
机构:
Chemistry Department, Faculty of Science, Cairo University, Giza, Egypt
Chemical Industries Development (CID) Company, Giza, Egypt
Abdel-Gawad, Soha Ali
[
3
]
机构
:
[1]
Chemical Industries Development (CID) Company, Giza, Egypt
[2]
Chemistry Department, Faculty of Science, Al-Azhar University, Cairo, Egypt
[3]
Chemistry Department, Faculty of Science, Cairo University, Giza, Egypt
来源
:
International Journal of Environmental Engineering
|
2021年
/ 11卷
/ 01期
关键词
:
Iron compounds - X ray spectroscopy - Regression analysis - Fourier transform infrared spectroscopy - Scanning electron microscopy;
D O I
:
10.1504/IJEE.2021.113775
中图分类号
:
学科分类号
:
摘要
:
Green chemistry approach has become the eco-friendliest and effective technique by using Ficus Benjamina for preparing bimetallic nanoscale zerovalent Fe/Cu particles and removal of phosphates from the aqueous solutions. Scanning electron microscope (SEM), Fourier transform infrared spectroscopy (FTIR), and dispersive X-ray spectroscopy (EDAX) were used for characterisation. The removal adequacy of phosphates (5 mg L-1) reached to 73% under the condition of 0.3 g L-1, 30 min, and pH 4. The adsorption results are more appropriate by the Langmuir model [R2 = 0.998], with qmax = 17.42 mg g-1. The results of adsorption kinetics indicate that, phosphates uptake on Ficus-nZVFeCu is following the pseudo-second order model. Overall, Benjamina nZVFe/Cu is a committed green substance to remove phosphates. Operating parameters effect was investigated using a SPSS-linear regression analysis and found that more than 97% of the variables have an effect on the removal process. © 2021 Inderscience Enterprises Ltd.
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页码:53 / 68
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