Functionalized chitosan-magnetic flocculants for heavy metal and dye removal modeled by an artificial neural network

Yongjun Sun, Yuanyuan Yu, Shengbao Zhou, Kinjal J. Shah, Wenquan Sun, Jun Zhai, Huaili Zheng

科研成果: 期刊稿件文章同行评审

24 引用 (Scopus)

摘要

In this study, an amphoteric magnetic chitosan (CS)-based flocculant MFe3O4@CS-g-PIA was prepared from CS, Fe3O4, and itaconic acid (IA), and its apparent morphology and characteristic structure were systematically studied. The flocculation performance and mechanism of the fabricated material were also investigated in different pollution systems, and the effects of total monomer concentration, m(CS):m(IA), IA pre-neutralization degree, reaction temperature, reaction time, and initiator concentration on the synthesis of MFe3O4@CS-g-PIA were studied. Characterization results showed that MFe3O4@CS-g-PIA forms a three-dimensional network with excellent magnetic induction. The optimal removal rates of Cu(II) and Disperse Blue 56 (DB56; 90.2% and 97.0%, respectively) were obtained under the conditions of 150 mg·L−1 MFe3O4@CS-g-PIA, pH 6.0, and 300 rpm stirring speed. MFe3O4@CS-g-PIA maintained removal rates of over 80.0% for Cu(II) and DB56 after five consecutive cycles of regeneration/flocculation and demonstrated excellent acid resistance stability. Changes in the particle size distribution, fractal dimensions, and zeta potentials of the flocs indicated that the relevant flocculation mechanism involves the synergistic functions of chelation, charge neutralization, and adsorption bridging. An artificial neural network model was finally established on the basis of the experimental flocculation data to predict the removal rates of Cu(II) (R = 0.97) and DB56 (R = 0.98) accurately.

源语言英语
文章编号120002
期刊Separation and Purification Technology
282
DOI
出版状态已出版 - 1 2月 2022

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