4.7 Article

Rank annihilation factor analysis using mean centering of ratio spectra for kinetic-spectrophotometric analysis of unknown samples

期刊

ANALYTICA CHIMICA ACTA
卷 639, 期 1-2, 页码 19-28

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ELSEVIER SCIENCE BV
DOI: 10.1016/j.aca.2009.02.032

关键词

Rank annihilation factor analysis; Kinetic; Spectrophotometric; Mean centering of ratio spectra

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In this work rank annihilation factor analysis (RAFA) using mean centering of ratio spectra was used to analyze the kinetic-spectrophotometric data. Annihilation of the contribution of one chemical component from the original data matrix is a general method in RAFA. However, sometimes, RAFA is not suitable for Studying rank-deficient data such as kinetic-spectrophotometric measurements which involves closure rank deficiency. On the other hand, in order to apply RAFA for the determination of an analyte in an unknown sample, a standard two-way matrix of the analyte of interest with rank-one should generally be available. This is not usually attainable for kinetic-spectrophotometric monitoring of complexation reactions when both reactant and product are absorbing species. In these systems, the exact contribution of absorbing reagent should be eliminated from both unknown sample and standard calibration data matrix of analyte otherwise ordinary RAFA fails to give correct concentration of analyte of interest. Mean centering of ratio spectra using the spectrum of absorbing reagent as divisor can be used to eliminate the correct contribution of reagent for both sample data and standard calibration data of analyte. The obtained mean centering of ratio spectra matrix of sample and that of analyte of interested are full-rank and rank-one, respectively. Therefore the system can be analyzed by RAFA. The proposed method was investigated with simulated data at the first stage. The method was then applied in the analysis of experimental kinetic-spectrophotometric data of complexation reactions of Co(II), and Ni(II) with PAN in order to do multi-component determination of these ions in various real samples. (C) 2009 Elsevier B.V. All rights reserved.

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