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Adsorption of As(V) Using Modified Magnetic Nanoparticles with Ascorbic Acid: Optimization by Response Surface Methodology

机译:用抗坏血酸修饰的磁性纳米粒子吸附As(V):响应面法优化

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摘要

In the present study, response surface methodology (RSM) was applied to maximize As(V) removal from aqueous solutions by using modified magnetic nanoparticles with ascorbic acid (AA-MNPs). The structural features of the produced material were characterized by means of X-ray diffraction (XRD), adsorption desorption, Fourier transform infrared (FTIR), vibmting sample magnetometer (VSM), thermogravimetric analyses (TGA), and scanning electron microscopy (SEM). More specifically, the effects of pH, temperature, arsenic ion concentration, and sorbent dosage were investigated on the arsenic adsorption. A total of 20 sets of experiments were designed by the software to achieve maximum adsorption capacity (q(e)) and removal efficiency (R). Analysis of variance (ANOVA) of the two-factor interaction (2FI) model suggested that the predicted values were in good agreement with experimental data. The best local maximum values for pH, arsenic concentration, and sorbent dosage were found to be 2, 5 mg L-1, and 0.1 g L-1, respectively, that yielding maximum q(e) of 44.99 mg g(-1) and a maximum R of 42.69 %. Additionally, the obtained value for desirability was equal to 0.862. The results indicated that the Langmuir model provided the best correlation of the equilibrium data. Moreover, the obtained results revealed that the pseudo-second-order kinetic model could best describe the adsorption kinetics.
机译:在本研究中,通过使用抗坏血酸修饰的磁性纳米粒子(AA-MNPs),应用响应表面方法(RSM)最大限度地去除水溶液中的As(V)。通过X射线衍射(XRD),吸附解吸,傅立叶变换红外(FTIR),振动样品磁强计(VSM),热重分析(TGA)和扫描电子显微镜(SEM)表征了所生产材料的结构特征。更具体地说,研究了pH,温度,砷离子浓度和吸附剂用量对砷吸附的影响。该软件设计了总共20套实验,以实现最大吸附容量(q(e))和去除效率(R)。两因素相互作用(2FI)模型的方差分析(ANOVA)表明,预测值与实验数据吻合良好。 pH,砷浓度和吸附剂剂量的最佳局部最大值分别为2、5 mg L-1和0.1 g L-1,产生的最大q(e)为44.99 mg g(-1)最大R为42.69%。另外,获得的期望值等于0.862。结果表明,Langmuir模型提供了平衡数据的最佳相关性。此外,获得的结果表明,伪二级动力学模型可以最好地描述吸附动力学。

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