纳米材料对阳离子型染料的吸附

发布时间：2023-08-25 21:55

　　染料工业发展迅速,已广泛应用于食品、医药、印染及化妆品中。随着染料的大规模应用,越来越多含有染料的废水在生产和使用中释放到环境中,带来的环境污染日趋严重。当染料废水排入水体时造成受污染水域色度增加,影响入射光线量,进而对水质、水体生物、人体健康和生态造成严重的危害。三苯甲烷类染料是合成染料中应用最广的染料类型之一,孔雀石绿和结晶紫作为此类染料的典型代表,已有研究表明该类染料对人体具有致癌、致畸和致突变的作用,对人类健康具有潜在危害。因此处理此类染料废水已成为亟待解决的重大问题。本文利用X射线衍射仪与X射线光电子能谱仪对零价纳米锌(购买)进行了表征,并研究了其对孔雀石绿水溶液的吸附。采用响应面实验设计方法,研究了pH、温度、反应时间及初始浓度对染料的吸附影响。并在响应面的基础上,采用神经网络结合粒子群和神经网络结合遗传算法模型预测其最优反应条件,获得最大去除率。结果表明,神经网络结合遗传算法预测的最佳吸附条件为:pH为5.70,温度为27.19℃,反应时间为110.62 min和初始浓度为607.03 mg/L。在上述条件下预测的去除率为94.12%,与之对应的实验结果为90.72%,两...

【文章页数】：97 页

【学位级别】：硕士

【文章目录】：
ABBREVIATION
中文摘要
Abstract
1. Introduction
    1.1. Hazardous dye of Malachite green and Crystal violet
    1.2. Classification of dyes
        1.2.1. Azo dyes
        1.2.2. Anthraquinone dyes
        1.2.3. Triarylmethane dyes
    1.3. Dye removal techniques
        1.3.1. Biological methods
        1.3.2. Chemical methods
        1.3.3. Physical methods
    1.4. Adsorption of dyes by nanoparticles
        1.4.1. Nano zerovalent iron
        1.4.2. Nanomaterials with magnetic properties
        1.4.3. Nano magnesium oxide
        1.4.4. Graphene oxide and reduced graphene oxide based nanomaterials
    1.5 Modelling and optimization techniques
    1.6. Main objectives of the present work
2. Preparation of reduced graphene oxide-supported bimetallic Fe/Ni composites (rGO/Fe/Ni)
    2.1. Experimental section
        2.1.1. Materials
        2.1.2. Experimental instruments
    2.2. Preparation of the nanomaterials
        2.2.1. Synthesis of graphene oxide (GO)
        2.2.2. Synthesis of Fe/Ni particles and rGO/Fe/Ni composites
    2.3. Characterization of the Commercially Available nZVZ and rGO/Fe/Ni
    2.4. Batch adsorption experiments
    2.5. Determine the zero point of charge of rGO/Fe/Ni composites
    2.6. Results and discussion
        2.6.1. Characterization of the commercially available nZVZ
        2.6.2. Characterization of rGO/Fe/Ni
        2.6.3 The zero point of charge for rGO/Fe/Ni composites
    2.7. Summary
3. Modeling and optimization
    3.1. Modeling and Optimization by RSM
        3.1.1. Modeling and Optimization for MG removal onto nZVZ by RSM
        3.1.2. Modeling and Optimization for CV removal onto rGO/Fe/Ni composites by RSM
    3.2. Prediction by BP-ANN
        3.2.1 Prediction for the adsorption of MG onto the commercially available nZVZ byBP-ANN
        3.2.2. Prediction for the adsorption of CV onto rGO/Fe/Ni composites by BP-ANN
    3.3. Modelling and optimization by ANN-PSO and ANN-GA
        3.3.1. Modelling and optimization for the adsorption of MG onto the commerciallyavailable nZVZ by ANN-PSO and ANN-GA
        3.3.2. Modeling and optimization for the removal of CV by rGO/Fe/Ni composites usingANN-PSO and ANN-GA
    3.4. Comparison with RSM, ANN-PSO and ANN-GA
        3.4.1 The adsorption of MG onto the commercially available nZVZ
        3.4.2. The adsorption of CV onto rGO/Fe/Ni composites
    3.5. Summary
4. Equilibrium isotherms, adsorption kinetic and adsorption thermodynamic
    4.1. Equilibrium Isotherms
        4.1.1. Equilibrium Isotherms for the adsorption of MG by the commercially availablenZVZ
        4.1.2. Equilibrium Isotherms for the adsorption of CV by rGO/Fe/Ni composites
    4.2. Adsorption kinetic
        4.2.1. Kinetic study for the adsorption of MG by the commercially available nZVZ
        4.2.2. Kinetic study for the adsorption of CV by rGO/Fe/Ni composites
    4.3. Thermodynamics study
        4.3.1. Thermodynamics study for the adsorption of MG onto the commercially availablenZVZ
        4.3.2. Thermodynamics study for the adsorption of CV by rGO/Fe/Ni composites
    4.4. Summary
5. Conclusion
6. Prospects
References
附录
致谢



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