Assessment of Cu(II) Removal from Aqueous Solutions by Modified Pomelo Peels: Experiments and Modelling

被引:2
|
作者
Zhang, Ruixue [1 ]
Jiao, Mengqing [1 ]
Zhao, Nan [1 ,2 ]
Jacquemin, Johan [3 ]
Zhang, Yinqin [4 ]
Liu, Honglai [2 ]
机构
[1] Hebei GEO Univ, Hebei Prov Key Lab Sustained Utilizat & Dev Water, Shijiazhuang 050031, Peoples R China
[2] East China Univ Sci & Technol, Sch Chem & Mol Engn, Shanghai 200237, Peoples R China
[3] Mohammed VI Polytech Univ, Mat Sci & Nanoengn MSN Dept, Lot 660 Hay Moulay Rachid, Ben Guerir 43150, Morocco
[4] Hebei Univ Engn, Sch Water Conservancy & Hydroelect Power, Handan 056038, Peoples R China
来源
MOLECULES | 2023年 / 28卷 / 08期
关键词
agricultural wastes bio-sorbents; wastewater treatment; heavy metal adsorption; artificial neural network; adsorption mechanism; NEURAL-NETWORK; ADSORPTION; IONS; OPTIMIZATION; BIOSORPTION; ADSORBENTS; CELLULOSE; COPPER;
D O I
10.3390/molecules28083438
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
In this study, low-cost pomelo peel wastes were used as a bio-sorbent to remove copper ions (e.g., Cu(II)) from aqueous solutions. Prior to testing its Cu(II) removal capability, the structural, physical and chemical characteristics of the sorbent were examined by scanning electron microscope (SEM), Fourier transform infrared (FTIR) spectroscopy, and Brunauer-Emmett-Teller (BET) surface area analysis. The impacts of the initial pH, temperature, contact time and Cu(II) feed concentration on the Cu(II) biosorption using modified pomelo peels were then assessed. Thermodynamic parameters associated to the biosorption clearly demonstrate that this biosorption is thermodynamically feasible, endothermic, spontaneous and entropy driven. Furthermore, adsorption kinetic data were found to fit very well with the pseudo-second order kinetics equation, highlighting that this process is driven by a chemical adsorption. Finally, an artificial neural network with a 4:9:1 structure was then established for describing the Cu(II) adsorption using modified pomelo peels with R-2 values close to 0.9999 and to 0.9988 for the training and testing sets, respectively. The results present a big potential use of the as-prepared bio-sorbent for the removal of Cu(II), as well as an efficient green technology for ecological and environmental sustainability.
引用
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页数:15
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