Application of general regression neural network and central composite design in fabrication and performance of magnetite (Fe3O4) modified carbon paste electrode for the electrochemical detection of Clomiphene

Publication date: June 2019Source: Microchemical Journal, Volume 147Author(s): Shabnam Mirzaei, Sajad Moradi, Hosna Ehzari, Negin Farhadian, Mohsen ShahlaeiAbstractIn this research, a novel, simple, sensitive and selective Carbon paste electrode (CPE) modified with Iron Oxide (Fe3O4) nanoparticles is constructed and used for the Voltammetric determination of Clomiphene. The synthesized Fe3O4 nanoparticles are characterized by routine methods such as scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FT-IR) and Atomic Force Microscope (AFM). Also, Clomiphene Redox behavior was examined by Differential pulse voltammetry (DPV) technique. An experimental Design model was developed to predict the behavior of a series of parameters including pH, concentration of modifier, step potential and amplitude on the electrochemical response of Clomiphene on the modified electrode. The obtained results showed that, the phosphate buffer with pH 4.0 was the best medium for reduction of Clomiphene on the modified carbon past electrode. The range of linearity was found to be from 1 to 727 μM (R2 = 0.9722). Finally, the response of electrode in the optimum conditions was modeled using general regression of neural networks and results were compared with common linear calibration.
Source: Microchemical Journal - Category: Chemistry Source Type: research