Fe3O4/GO对水溶液中Cd(II)去除的影响因素

为探索高效且快速去除水溶液中Cd （Ⅱ）污染方法，采用自制磁性四氧化三铁负载氧化石墨烯（Fe₃O₄/GO）纳米复合材料对水溶液中Cd （Ⅱ）进行去除，利用单因素实验确定影响因素水平范围（初始Cd （Ⅱ）浓度、温度、反应时间、初始pH值），并采用响应面法（RSM）及人工神经网络-遗传算法（ANN-GA）对去除水溶液中Cd （Ⅱ）的影响因素（4因素3水平）进行优化，利用等温吸附、动力学及热力学参数研究吸附剂性能.通过扫描电子显微镜（SEM）、X射线衍射仪及超导量子干涉器件（SQUID）对复合材料表征.结果表明，平均粒径为30.9nm的磁性Fe₃O₄/GO纳米复合材料被成功制备.RSM用于磁性Fe₃O₄/GO纳米复合材料对水溶液中Cd （Ⅱ）去除条件优化，预测去除率达到86.451%，验证试验为82.220%，对应条件：温度为20.14℃，反应时间为57.78min，初始pH值为6.41和初始Cd （Ⅱ）浓度为11.18mg/L； ANN-GA优化条件后的预测去除率为89.722%，验证试验为87.723%，相应条件：温度为29.96℃，pH值为5.49，初始Cd （Ⅱ）浓度为28.36mg/L，反应时间为65.78min.根据模型R²值，预测的最大去除率及验证试验，ANN-GA模型性能及预测能力均高于RSM.RSM方差分析表明4个因素对磁性Fe₃O₄/GO纳米复合材料去除水溶液中Cd （Ⅱ）的影响大小为：初始Cd （Ⅱ）浓度>温度>反应时间>pH值.吸附机理分析结果显示，Fe₃O₄/GO纳米复合材料对Cd （Ⅱ）吸附过程同时存在着物理吸附和化学吸附.结合ANN-GA优化，利用磁铁实现且快速分离，磁性Fe₃O₄/GO纳米复合材料用于去除Cd （Ⅱ）是可行的.关键字：Cd （Ⅱ）；四氧化三铁负载氧化石墨烯；单因素实验；响应面法；人工神经网络-遗传算法中图分类号：X53

Influencing factors of Cd(II) removal from aqueous solution by Fe3O4/GO

To explore efficient and rapid method for removing Cd (Ⅱ) from aqueous solution, the prepared graphene oxide-supported ferroferric oxide (Fe₃O₄/GO) nanocomposites were used to remove Cd(Ⅱ) from aqueous solutions. Single factor experiments were used to determine the level of operating factors (initial Cd(Ⅱ) concentration, operating temperature, contact time and initial pH). The operating parameters (4-factor-3-level) of removal Cd(Ⅱ) from aqueous solution were optimized by response surface methodology (RSM) and artificial neural network-genetic algorithm (ANN-GA), the adsorbent performance was researched by isothermal adsorption, kinetics and thermodynamic parameters. Fe₃O₄/GO nanocomposites, the average size of 30.09nm, were successfully prepared by the characterization of X-ray diffraction (XRD), scanning electron microscopy (SEM) and superconducting quantum interference device (SQUID). The predicted and confirmed values of removal Cd (Ⅱ) from aqueous solution were 86.451% and 82.220% with temperature=20.14℃, contact time=57.78min, initial pH=6.41 and initial Cd(Ⅱ) concentration=11.18mg/L using RSM, respectively. However, the predicted and confirmed values were 89.722% and 87.723% using ANN-GA with temperature=29.96℃, initial pH=5.49, initial Cd(Ⅱ) concentration=28.36mg/L and contact time=65.78min. According to R² value, the predicted maximum efficiency and confirmed experiment, the performance and predicted ability of ANN-GA model was better than that of RSM. RSM analysis of variance showed that the effects of four factors on the removal of Cd(Ⅱ) from aqueous solution of Fe₃O₄/GO nanocomposites were as follows:initial Cd(Ⅱ) concentration > temperature > reaction time > pH. The results of adsorption mechanism analysis showed that the adsorption process of Fe₃O₄/GO nanocomposites for removal Cd(Ⅱ) existed simultaneously physical and chemical adsorption. Combined with ANN-GA optimization, Fe₃O₄/GO nanocomposites can be used to remove Cd(Ⅱ) by using magnets to achieve rapid separation.