Studies On The Removal Of Hg And Se From Aqueous Solutions By Graphene-supported Iron-based Composites

Environmental pollution is more and more serious in the recent years with the rapid industrialization,population expansion and accelerated urbanization.Lage amounts of wastewater contaminated with heavy metals and metalloid are discharged into the environment not only causing significant effects on the human life but also threat the eco-environment,Hg and Se??? can be accumulated in living organisms and can lead to a serious risk to human health.Thus,it is of pivotal importance to remediate wastewater pollution.In the present study,the Fe₃O₄/rGO composites and the nZVI/rGO magnetic composites were employed to the removal of Hg and Se??? from wastewater,which were successfully prepared and characterized by X-ray diffraction?XRD?,scanning electron microscopy?SEM?,transmission electron microscopy?TEM?,atomic force microscopy?AFM?,N₂-sorption,X-ray photoelectron spectroscopy?XPS?,Fourier transform infrared spectroscopy?FTIR?and superconduction quantum interference device?SQUID?.In order to improve the efficiency of the experiment and reduce cost,highly promising artificial intelligence tools,including neural network?ANN?,genetic algorithm?GA?and particle swarm optimization?PSO?,were applied to develop an approach for the evaluation of Hg ions and Se??? removal from aqueous solutions by Graphene-supported iron-based composites.Both GA and PSO were used to optimize the parameters of ANN.The effect of operational parameters?i.e.,initial pH,temperature,contact time and initial concentration?on the removal efficiency was examined using response surface methodology?RSM?,which was also utilized to obtain a dataset for the ANN training.For the removal of the low-concentration mercury from aqueous solutions by the Fe₃O₄/rGO composites,the ANN-GA model results?with a prediction error below 5%?show better agreement with the experimental data than the RSM model results?with a prediction error below 10%?.The removal process of the low-concentration mercury obeyed the Freudlich isotherm and the pseudo-second-order kinetic model.In addition,a regeneration experiment of the Fe₃O₄/rGO composites demonstrated that these composites can be reused for the removal of low-concentration mercury from aqueous solutions;For the evaluation of Se???removal from aqueous solutions by nZVI/rGO composites,the ANN-GA model results?with a prediction error of 2.88%?showed a better compatible with the experimental data than the ANN-PSO model results?with a prediction error of 4.63%?and the RSM model results?with a prediction error of5.56%?,thus the ANN-GA model was an ideal choice for modeling and optimizing the Se???removal by the nZVI/rGO composites due to its low prediction error.The analysis of the experimental data illustrates that the removal process of Se???obeyed the Langmuir isotherm and the pseudo-second-order kinetic model.Furthermore,the Se 3d and 3p peaks found in XPS spectra for the nZVI/rGO composites after removing treatment illustrates that the removal of Se???was mainly through the adsorption and reduction mechanisms.