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采用响应面法对磁性NiFeO/RGO纳米复合材料吸附偶氮染料进行建模。

Modeling of azo dyes adsorption on magnetic NiFeO/RGO nanocomposite using response surface methodology.

作者信息

Bazgir Ayoub, Khorshidi Alireza, Kamani Hossein, Ashrafi Seyed Davoud, Naghipour Dariush

机构信息

1Student of School of Health, Guilan University of Medical Sciences, Rasht, Iran.

2Department of Chemistry, Faculty of Sciences, University of Guilan, P.O. Box 41335-1914, Rasht, Guilan Iran.

出版信息

J Environ Health Sci Eng. 2019 Dec 5;17(2):931-947. doi: 10.1007/s40201-019-00409-3. eCollection 2019 Dec.

Abstract

BACKGROUND

Azo group dyes are the largest group of synthetics dyes that widely used in industries, especially in textile industry. The presence of these organic compounds in wastewaters and their discharge into environment without efficient treatment may cause adverse effect on human, living and aquatic environment. The purpose of this study was to optimize the adsorption of azo dye of Direct Red 81 (anionic dye) and Basic Blue 41 (cationic dye) from aqueous solution onto magnetic NiFeO/RGO nanocomposite.

METHODS

In this study the response surface methodology (RSM) based on the central composite design (CCD), was used to optimization and modeling of adsorption process DR81 and BB41 dye on NiFeO/RGO. in order to investigating the effect of the operating parameters on the adsorption efficiency DR81 and BB41, four influential factors were chosen that includes of pH (3-9), contact time (5-25 min), adsorbent amount (0.02-0.05 g) and initial dye concentration (40-200 mg/L). A total of 30 experiments were performed for each dye in this study. The concentration of dye in solution was measured by spectrophotometer. The structure of synthesized adsorbent was investigated using Scanning Electron Microscope (SEM), X-ray diffraction (XRD), Fourier transform irradiation (FTIR), transmission electron microscope (TEM) and vibrating sample magnetometer (VSM).

RESULTS

Analysis of variance (ANOVA) showed that regression model for both dye adsorption with value of value <0.001 is significant statistically. The correlation coefficient (R) for DR81 (R = 0.9968) and BB41 (R = 0.9948) indicated which there is a good agreement between predicted values and the results of the experiments and the model also well predict the adsorption efficiency. Furthermore, the factors of pH, dye concentration and adsorbent dose, have the greatest effect on adsorption, respectively, while contact time have the lowest effect on adsorption of both dyes. The adsorption behavior of the DR81 and BB41 onto NiFeO/RGO was best described by the Langmuir and Freundlich isotherm, respectively. The optimum conditions for maximum removal of DR81 (96.41%) was found to be at pH 3, contact time 19.68 min, adsorbent dose 0.02 g and initial dye concentration 40 mg/L. However, the optimum conditions for maximum removal of BB41 (97.87%) was found to be at pH 9 contact time 18.16 min, adsorbent dose 0.02 g and initial dye concentration 40 mg/L.

CONCLUSION

The present study shows that magnetic NiFeO/RGO nanocomposite have much potential as a powerful adsorbent for the rapid adsorption of anionic (DR81) and cationic dyes (BB41) from aqueous solution.

摘要

背景

偶氮类染料是合成染料中最大的一类,广泛应用于工业领域,尤其是纺织工业。废水中这些有机化合物的存在以及未经有效处理就排放到环境中,可能会对人类、生物和水生环境造成不利影响。本研究的目的是优化磁性NiFeO/RGO纳米复合材料对水溶液中直接红81(阴离子染料)和碱性蓝41(阳离子染料)的吸附。

方法

本研究采用基于中心复合设计(CCD)的响应面方法(RSM),对DR81和BB41染料在NiFeO/RGO上的吸附过程进行优化和建模。为了研究操作参数对DR81和BB41吸附效率的影响,选择了四个影响因素,包括pH值(3 - 9)、接触时间(5 - 25分钟)、吸附剂用量(0.02 - 0.05克)和初始染料浓度(40 - 200毫克/升)。本研究中每种染料总共进行了30次实验。用分光光度计测量溶液中染料的浓度。使用扫描电子显微镜(SEM)、X射线衍射(XRD)、傅里叶变换红外光谱(FTIR)、透射电子显微镜(TEM)和振动样品磁强计(VSM)研究合成吸附剂的结构。

结果

方差分析(ANOVA)表明,两种染料吸附的回归模型,其p值<0.001,在统计学上具有显著性。DR81(R = 0.9968)和BB41(R = 0.9948)的相关系数(R)表明,预测值与实验结果之间有很好的一致性,并且该模型也能很好地预测吸附效率。此外,pH值、染料浓度和吸附剂剂量因素分别对吸附有最大影响,而接触时间对两种染料吸附的影响最小。DR81和BB41在NiFeO/RGO上的吸附行为分别用Langmuir和Freundlich等温线能得到最佳描述。发现去除DR81达到最大值(96.41%)的最佳条件是pH值为3、接触时间19.68分钟、吸附剂用量0.02克和初始染料浓度40毫克/升。然而,去除BB41达到最大值(97.87%)的最佳条件是pH值为9、接触时间18.16分钟、吸附剂用量0.02克和初始染料浓度40毫克/升。

结论

本研究表明,磁性NiFeO/RGO纳米复合材料作为一种强大的吸附剂,在从水溶液中快速吸附阴离子(DR81)和阳离子染料(BB41)方面具有很大潜力。

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