2012APCBEE ProcediaOpen access

Extraction and Simultaneous Determination Ions Copper and Cobalt by Spectrophotometric and Chemometrics Methods

Reza Moradi, Saeed Jameh‐Bozorghi, Али Ниази

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Abstract

Partial least squares modeling is a powerful multivariate statistical tool applied to extraction spectrophotometric simultaneous determination of mixtures of copper and cobalt. The method is based on the formation of complexes of 1-(2-Thiazolylazo)-2-naphthol (TAN) with copper and cobalt. The TAN complexes are quantitatively extracted into dichloromethane and the resolution of the mixtures is accomplished by partial least squares (PLS). Orthogonal signal correction (OSC) is a preprocessing technique used in the information unrelated to the target variables based on constrained principal component analysis. OSC is a suitable preprocessing method for partial least squares calibration of mixtures without loss of prediction capacity using spectrophotometric method. In this study, the calibration model is based on absorption spectra in the 350-750 nm range for 25 different mixtures of copper and cobalt. Calibration matrices ranges were 1.0-300.0 and 1.0-200 ng ml-1 for copper and cobalt, respectively. A series of synthetic solutions containing different concentrations of copper and cobalt was used to check the prediction ability of the PLS and OSC-PLS models. The RMSEP for copper and cobalt with OSC and without OSC was 0.266 and 0.378, 0.513 and 0.643, respectively. The method was successfully applied to the analysis of spiked water (river, tap and well) samples.

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Partial least squares modeling is a powerful multivariate statistical tool applied to extraction spectrophotometric simultaneous determination of mixtures of copper and cobalt. The method is based on the formation of complexes of 1-(2-Thiazolylazo)-2-naphthol (TAN) with copper and cobalt. The TAN complexes are quantitatively extracted into dichloromethane and the resolution of the mixtures is accomplished by partial least squares (PLS). Orthogonal signal correction (OSC) is a preprocessing technique used in the information unrelated to the target variables based on constrained principal component analysis. OSC is a suitable preprocessing method for partial least squares calibration of mixtures without loss of prediction capacity using spectrophotometric method. In this study, the calibration model is based on absorption spectra in the 350-750 nm range for 25 different mixtures of copper and cobalt. Calibration matrices ranges were 1.0-300.0 and 1.0-200 ng ml-1 for copper and cobalt, respectively. A series of synthetic solutions containing different concentrations of copper and cobalt was used to check the prediction ability of the PLS and OSC-PLS models. The RMSEP for copper and cobalt with OSC and without OSC was 0.266 and 0.378, 0.513 and 0.643, respectively. The method was successfully applied to the analysis of spiked water (river, tap and well) samples.

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Available abstract

Partial least squares modeling is a powerful multivariate statistical tool applied to extraction spectrophotometric simultaneous determination of mixtures of copper and cobalt. The method is based on the formation of complexes of 1-(2-Thiazolylazo)-2-naphthol (TAN) with copper and cobalt. The TAN complexes are quantitatively extracted into dichloromethane and the resolution of the mixtures is accomplished by partial least squares (PLS). Orthogonal signal correction (OSC) is a preprocessing technique used in the information unrelated to the target variables based on constrained principal component analysis. OSC is a suitable preprocessing method for partial least squares calibration of mixtures without loss of prediction capacity using spectrophotometric method. In this study, the calibration model is based on absorption spectra in the 350-750 nm range for 25 different mixtures of copper and cobalt. Calibration matrices ranges were 1.0-300.0 and 1.0-200 ng ml-1 for copper and cobalt, respectively. A series of synthetic solutions containing different concentrations of copper and cobalt was used to check the prediction ability of the PLS and OSC-PLS models. The RMSEP for copper and cobalt with OSC and without OSC was 0.266 and 0.378, 0.513 and 0.643, respectively. The method was successfully applied to the analysis of spiked water (river, tap and well) samples.

Key concepts: Partial least squares regression, Cobalt, Chemometrics, Copper, Calibration, Analytical Chemistry (journal), Chemistry, Chromatography

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