The Adsorption Of Cationic Dyes Onto Nanomaterials

With the fast development of the dyestuff industry,dyes have been widely used in some areas such as food,medicine,printing and cosmetics.This results in the massive dyes releasing,which poses a potential threat to the environment.The discharge of coloured wastes into streams can lead to undesirable danger to the aquatic life such as reducing sunlight penetration and resisting photochemical reactions.Triarylmethane dyes are one of the most commonly used dyes,especially for Malachite green(MG)and Crystal violet(CV).These dyes are carcinogenic,mutagenic and teratogenic,and thus have a severe effect on humans and animals.Thereby,the removal of these dyes from wastewater before being discharged into surface water bodies is indispensible and significant.The commercially available nanoscale zerovalent zinc(nZVZ)was used as an adsorbent for the removal of MG from aqueous solutions.This material was characterized by X-ray diffraction(XRD)and X-ray photoelectron spectroscopy(XPS).The advanced experimental design tools were adopted to study the effect of process parameters(viz.initial pH,temperature,contact time and initial concentration)and to reduce number of trials and cos.artificial neural network coupled with particle swarm optimization(ANN-PSO)and artificial neural network coupled with genetic algorithm(ANN-GA)were employed for predicting the optimum process variables and obtaining the maximum removal efficiency of MG.The results showed that the removal efficiency predicted by ANN-GA(94.12%)was compatible with the experimental value(90.72%).Furthermore,the Langmuir isotherm was found to be the best model to describe the adsorption of MG onto nZVZ,while the maximum adsorption capacity was calculated to be 1000.00 mg/g.The kinetics for adsorption of MG onto nZVZ was found to follow the pseudo-second-order kinetic model.Thermodynamic parameters(ΔG~0,ΔH~0 andΔS~0)were calculated from the Van’t Hoff plot of lnKc vs.1/T in order to discuss the removal mechanism of MG.The reduced graphene oxide supported bimetallic Fe/Ni composites were synthesized as an adsorbent for the removal of CV dye from aqueous solutions.This material was characterized by X-ray diffraction(XRD),scanning electron microscopy(SEM),X-ray photoelectron spectroscopy(XPS)analysis,N~2-sorption and Raman spectroscopy.The influence of independent parameters,i.e.initial pH,contact time,temperature and initial dye concentration concentration,on removal efficiency were investigated via response surface methodology(RSM).The maximum removal efficiency was 75.8%by using the RSM model under following condition:initial pH of 3.0,temperature of 40.6°C,contact time of 18.0 min and initial concentration of369.9 mg/L.The corresponding experimental value was 75.8%.Artificial intelligence,i.e.artificial neural network,genetic algorithm and particle swarm optimization,were used to optimize and predict the optimum conditions and obtained the maximum removal efficiency.The maximum removal efficiency predicted by ANN-PSO model is 88.0%under the condition,initial pH for 4.0,temperature for 45℃,contact time for18 min and initial concentration for 300 mg/L,but the corresponding experimental values is 84.5%.The performance of ANN-GA model indicates the prediction removal efficiency is 86.9%under the following condition:initial pH for 3.3,temperature for 36.1℃,contact time for 15.8 min and initial concentration for 331.2mg/L.The absolute errors between predicted and experimental results are 12.4,3.5and 5.6 for RSM,ANN-PSO and ANN-GA models,respectively.It was found that ANN-PSO is suitable for the prediction the removal efficiency of CV onto rGO/Fe/Ni composites.The experimental equilibrium data were fitted well to the Freundlich model for evaluation of the actual behavior of adsorption of CV,and the Langmuir isotherm predicted the maximum monolayer adsorption capacity of 2000.00 mg/g.The kinetic study at various time intervals reveals that the adsorption processes can be satisfactorily described by pseudo-second-order.The adsorption of CV onto rGO/Fe/Ni composites was found to be spontaneous and endothermic in nature.