Studies On The Treatment Of Dyes(Methylene Blue,Methyl Orange) From Simulated Wastewater With Graphene Based Nanomaterials

With a rapid rise in demand,dyes have been widely adopted in many industries such as textile,medicine,paper,leather and cosmetics.Although dyes bring great economic benefits to people's lives,they also produce a large amount of dye wastewater discharged into environmental water bodies,resulting in increasingly serious pollution.Dyes have the characteristics of heavy pollution,wide variety,complex structure and difficulty to biochemical degradation.Methylene blue?MB?and methyl orange?MO?are typical azo dyes.The toxic and high chroma of these dyes wastewater can be identified by eyes,which can cause a range of hazards to humans and animals.Therefore,it is of great significance to find an effective method to treat dyes wastewater.In this study,the mesoporous rGO/Fe/Co nanohybrids prepared by the co-precipitation method were used to decontaminate MB from simulated wastewater.The obtained products were systematically characterized with X-ray diffraction,scanning electron microscopy,Raman spectroscopy,energy dispersive spectroscopy,N2-sorption,and X-ray photoelectron spectroscopy.It was found that these nanohybrids possessed a surface area of 108.445 m²/g and a narrow pore size distribution with a center of 3.94 nm.The effect of initial pH,temperature,contact time,initial concentration on the extent of decontamination by the material was investigated and modeled with artificial intelligence?AI?.The optimum conditions were predicted and the maximum decontamination efficiency obtained by response surface methodology?RSM?and AI,i.e.artificial neural network-particle swarm?ANN-PSO?,artificial neural network-genetic algorithm?ANN-GA?.The optimum values of independent parameters for central composite design?CCD?are 300 mg/L for initial MB concentration,5.0 for initial pH,35.00 ? for temperature and 12 min for contact time.The maximum decontamination efficiency predicted under this condition was 91.25%,while the corresponding experimental value was 88.37%.The maximum percentage decontamination predicted by using ANN-PSO model is 93.47% and the corresponding experimental value is 92.95% under the following condition: initial concentration of 200 mg/L,pH of 6.0,temperature of 34.17 ? and contact time of 15 min.The performance of the ANN-GA model indicates that the predicted decontamination efficiency is 89.29% and the corresponding experimental value is 90.64% under the condition: initial concentration of 214 mg/L,pH of 3.8,temperature of 25.5 ? and contact time of 10.7 min.Among the three models developed,the ANN-PSO model has the highest R² value and the lowest mean square error value,thus this model has the best performance.The experimental equilibrium data were analyzed with Langmuir,Freundlich,Temkin and D-R isothermal models.It was exhibited that the data were well presented by Langmuir model with a maximum adsorption capacity of 909.10 mg/g at 298 K for the model.The kinetic study demonstrated that the decontamination processes could be well described by the pseudo-second-order model.In addition,thermodynamic parameters were calculated,which include Gibbs free energy change??G⁰?,entropy change??S⁰?,and enthalpy change??H⁰?.It was observed that the spontaneous and endothermic nature of the decontamination of MB by the nanohybrids.Overall,this material could be potentially used as a low cost and fast decontaminant to treat organic contaminants in wastewater or other pollutants.The mesoporous Fe₃O₄/rGO/N-F codoped TiO₂ nanocomposites were successfully synthesized and characterized with UV-visible diffuse reflectance spectroscopy and photoluminescence spectroscopy etc.Then,photocatalytic degradation of MO using this material has been studied under various process conditions.The effects of initial concentration?30-50 mg/L?,initial pH?3-5?,dosage?0.1-0.16 g?,and contact time?50-70 min?on the degree of degradation of MO by the material were investigated through RSM and AI?e.g.,radial basis function neural network?RBF?,and random forest?RF??was used for modeling.The results show that the ANN-PSO model was more accurate than the RSM and ANN-GA models.The prediction value of MO photogradation efficiency?95.8%?was determined by ANN-PSO model,which was consistent with the experimental value?93.78%?.This indicates that mesoporous Fe₃O₄/rGO/N-F codoped TiO₂ nanocomposites can effectively degrade MO under certain conditions.In addition,the experimental data were fitted well with the pseudo-first order kinetic model.The regeneration experiments indicate that the material can degrade MO circularly.In summary,these mesoporous nanocomposites have the advantages of large specific surface area,low cost and high removal capacity for MB and MO dyes,and optimization of the removal process with the AI technologies was successful.