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Updated: Jun 28, 2026

High Resolution Physical Characterization of Single Metallic Nanoparticles
Published on: June 28, 2019
Extending the dynamic range of copper determination in differential pulse adsorption cathodic stripping voltammetry
T Khayamian1, Ali A Ensafi, A Benvidi
1College of Chemistry, Isfahan University of Technology, Isfahan, Iran.
Abstract:
A wavelet neural network (WNN) model is proposed for extending the dynamic range of Cu(II) determination by differential pulse adsorption cathodic stripping voltammetry (DP-AdSV) using xylenol orange (XO) as a suitable ligand. All of voltammograms data consisting of Cu(II) and Cu(II)-XO peak currents were used in WNN model. The WNN model consisted of three layers (2-8-1) with the Morlet mother wavelet transfer function in the hidden layer. The model was able to extend the dynamic range of Cu(II) from its narrow linear range (1-50 ng ml(-1)) to the higher dynamic range (1-1500 ng ml(-1)). The results of the WNN model was also compared with artificial neural network (ANN) model and it was demonstrated the superiority of the WNN model relative to ANN model.
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