Direct Quantification of Cd²⁺ in the Presence of Cu²⁺ by a Combination of Anodic Stripping Voltammetry Using a Bi-Film-Modified Glassy Carbon Electrode and an Artificial Neural Network.

ABSTRACT: Abstract: In this study, a novel method based on a Bi/glassy carbon electrode (Bi/GCE) for quantitatively and directly detecting Cd²⁺ in the presence of Cu²⁺ without further electrode modifications by combining square-wave anodic stripping voltammetry (SWASV) and a back-propagation artificial neural network (BP-ANN) has been proposed. The influence of the Cu²⁺ concentration on the stripping response to Cd²⁺ was studied. In addition, the effect of the ferrocyanide concentration on the SWASV detection of Cd²⁺ in the presence of Cu²⁺ was investigated. A BP-ANN with two inputs and one output was used to establish the nonlinear relationship between the concentration of Cd²⁺ and the stripping peak currents of Cu²⁺ and Cd²⁺. The factors affecting the SWASV detection of Cd²⁺ and the key parameters of the BP-ANN were optimized. Moreover, the direct calibration model (i.e., adding 0.1 mM ferrocyanide before detection), the BP-ANN model and other prediction models were compared to verify the prediction performance of these models in terms of their mean absolute errors (MAEs), root mean square errors (RMSEs) and correlation coefficients. The BP-ANN model exhibited higher prediction accuracy than the direct calibration model and the other prediction models. Finally, the proposed method was used to detect Cd²⁺ in soil samples with satisfactory results.

SUBMITTER: Zhao G 

PROVIDER: S-EPMC5539607 | biostudies-literature | 2017 Jul

REPOSITORIES: biostudies-literature