Artificial neural network assisted kinetic spectrophotometric technique for simultaneous determination of paracetamol and p-aminophenol in pharmaceutical samples using localized surface plasmon resonance band of silver nanoparticles

Abstract

Spectrophotometric analysis method based on the combination of the principal component analysis (PCA) with the feed-forward neural network (FFNN) and the radial basis function network (RBFN) was proposed for the simultaneous determination of paracetamol (PAC) and p-aminophenol (PAP). This technique relies on the difference between the kinetic rates of the reactions between analytes and silver nitrate as the oxidizing agent in the presence of polyvinylpyrrolidone (PVP) which is the stabilizer. The reactions are monitored at the analytical wavelength of 420nm of the localized surface plasmon resonance (LSPR) band of the formed silver nanoparticles (Ag-NPs). Under the optimized conditions, the linear calibration graphs were obtained in the concentration range of 0.122–2.425μgmL−1 for PAC and 0.021–5.245μgmL−1 for PAP. The limit of detection in terms of standard approach (LODSA) and upper limit approach (LODULA) were calculated to be 0.027 and 0.032μgmL−1 for PAC and 0.006 and 0.009μgmL−1 for PAP. The important parameters were optimized for the artificial neural network (ANN) models. Statistical parameters indicated that the ability of the both methods is comparable. The proposed method was successfully applied to the simultaneous determination of PAC and PAP in pharmaceutical preparations.