Square wave anodic stripping voltammetry(SWASV)is an effective method for the detection of Cd(II),but the presence of Pb(II)usually has some potential and negative interference on the SWASV detection of Cd(II).In this...Square wave anodic stripping voltammetry(SWASV)is an effective method for the detection of Cd(II),but the presence of Pb(II)usually has some potential and negative interference on the SWASV detection of Cd(II).In this paper,a novel method was proposed to predict the concentration of Cd(II)in the presence of Pb(II)based on the combination of chemically modified electrode(CME),machine learning algorithms(MLA)and SWASV.A Bi film/ionic liquid/screen-printed electrode(Bi/IL/SPE)was prepared and used for the sensitive detection of trace Cd(II).The parameters affecting the stripping currents were investigated and optimized.The morphologies and electrochemical properties of the modified electrode were characterized by scanning electron microscopy(SEM)and SWASV.The measured SWASV spectrograms obtained at different concentrations were used to build the mathematical models for the prediction of Cd(II),which taking the combined effect of Cd(II)and Pb(II)into consideration on the SWASV detection of Cd(II),and to establish a nonlinear relationship between the stripping currents of Pb(II)and Cd(II)and the concentration of Cd(II).The proposed mathematical models rely on an improved particle swarm optimization-support vector machine(PSO-SVM)to assess the concentration of Cd(II)in the presence of Pb(II)in a wide range of concentrations.The experimental results suggest that this method is suitable to fulfill the goal of Cd(II)detection in the presence of Pb(II)(correlation coefficient,mean absolute error and root mean square error were 0.998,1.63 and 1.68,respectively).Finally,the proposed method was applied to predict the trace Cd(II)in soil samples with satisfactory results.展开更多
Unlike natural organic matter(NOM), wastewater organic matter(WWOM) from wastewater treatment plant effluents has not been extensively studied with respect to complexation reactions with heavy metals such as copper or...Unlike natural organic matter(NOM), wastewater organic matter(WWOM) from wastewater treatment plant effluents has not been extensively studied with respect to complexation reactions with heavy metals such as copper or zinc. In this study, organic matter from surface waters and a wastewater treatment plant effluent were concentrated by reverse osmosis(RO) method. The samples were treated in the laboratory to remove trace metals and major cations. The zinc complexing properties of both NOM and the WWOM were studied by square wave anodic stripping voltammetry(SWASV). Experimental data were compared to predictions using the Windermere Humic Aqueous Model(WHAM) Version VI. We found that the zinc binding of WWOM was much stronger than that of NOM and not well predicted by WHAM. This suggests that in natural water bodies that receive wastewater treatment plant effluents the ratio of WWOM to NOM must be taken into account in order to accurately predict free zinc activities.展开更多
基金supported by General Program of National Natural Science Foundation of China(Grant No.31671578)National High Technology Research and Development Program of China(Grant No.2013AA102302).
文摘Square wave anodic stripping voltammetry(SWASV)is an effective method for the detection of Cd(II),but the presence of Pb(II)usually has some potential and negative interference on the SWASV detection of Cd(II).In this paper,a novel method was proposed to predict the concentration of Cd(II)in the presence of Pb(II)based on the combination of chemically modified electrode(CME),machine learning algorithms(MLA)and SWASV.A Bi film/ionic liquid/screen-printed electrode(Bi/IL/SPE)was prepared and used for the sensitive detection of trace Cd(II).The parameters affecting the stripping currents were investigated and optimized.The morphologies and electrochemical properties of the modified electrode were characterized by scanning electron microscopy(SEM)and SWASV.The measured SWASV spectrograms obtained at different concentrations were used to build the mathematical models for the prediction of Cd(II),which taking the combined effect of Cd(II)and Pb(II)into consideration on the SWASV detection of Cd(II),and to establish a nonlinear relationship between the stripping currents of Pb(II)and Cd(II)and the concentration of Cd(II).The proposed mathematical models rely on an improved particle swarm optimization-support vector machine(PSO-SVM)to assess the concentration of Cd(II)in the presence of Pb(II)in a wide range of concentrations.The experimental results suggest that this method is suitable to fulfill the goal of Cd(II)detection in the presence of Pb(II)(correlation coefficient,mean absolute error and root mean square error were 0.998,1.63 and 1.68,respectively).Finally,the proposed method was applied to predict the trace Cd(II)in soil samples with satisfactory results.
文摘Unlike natural organic matter(NOM), wastewater organic matter(WWOM) from wastewater treatment plant effluents has not been extensively studied with respect to complexation reactions with heavy metals such as copper or zinc. In this study, organic matter from surface waters and a wastewater treatment plant effluent were concentrated by reverse osmosis(RO) method. The samples were treated in the laboratory to remove trace metals and major cations. The zinc complexing properties of both NOM and the WWOM were studied by square wave anodic stripping voltammetry(SWASV). Experimental data were compared to predictions using the Windermere Humic Aqueous Model(WHAM) Version VI. We found that the zinc binding of WWOM was much stronger than that of NOM and not well predicted by WHAM. This suggests that in natural water bodies that receive wastewater treatment plant effluents the ratio of WWOM to NOM must be taken into account in order to accurately predict free zinc activities.
