Direct Cu, Fe, and Ni Ions Multicomponent Analysis Using UV-Vis Spectrophotometric Method

Abstract

This study presents a direct multicomponent analysis method using UV-Vis spectrophotometry to determine Cu(II), Fe(III), and Ni(II) ion content without prior complexation or separation. Single and multivariate regression was used to predict metal ion content, and the resulting model was trained and validated using a dataset of 25 multi-component samples. The mean recoveries for Cu(II), Fe(III), and Ni(II) using linear and ridge regression based only on absorbance at 805 nm were 99.97% and 101.6%, 95.42% and 95.65%, and 99.43% and 99.99%, respectively, for the 20% test data. The mean recoveries for Cu(II), Fe(III), and Ni(II) using linear and ridge regression based only on absorbance at 805 nm were 92.27% and 95.03%, 125.3% and 124.11%, and 104.15% and 105.52%, respectively, for the test solution outside of the training data. These results demonstrate the effectiveness of the multivariate UV-Vis spectrophotometric method for the simultaneous determination of Cu(II) and Ni(II) in multicomponent samples, which meets the analysis standard and can be successfully applied. Finally, the study sheds light on the influence of spectral interference on the accuracy of regression models. It highlights the importance of carefully selecting the wavelengths used as predictors in such models. This can have significant implications for developing and validating analytical methods, particularly in cases where multiple analytes were present in a sample.

Keywords

• UV-Vis Spectrometry
• Multicomponent Analysis
• Multivariate Regression
• Cu(II)
• Fe(III)
• Ni(II)