Independent component analysis algorithms for spectral decomposition in UV/VIS analysis of metal-containing mixtures including multimineral food supplements and platinum concentrates

Abstract

Various independent component analysis (ICA) algorithms (MILCA, JADE, SIMPLISMA, RADICAL) are applied for simultaneous spectroscopic determination of two groups of transition metals: Co(II)–Fe(III)–Cu(II)–Zn(II)–Ni(II) and Pt(IV)–Pd(II)–Ir(IV)–Rh(III)–Ru(III)) in complex mixtures. The analysis is based on the decomposition of spectra of multicomponent mixtures in the UV-VIS region based on the natural absorbance of metal salts, or, when a better sensitivity is desirable, based on the absorbance of their complexes with 4-(2-pyridylazo)resorcinol (PAR) and ethylenediaminetetraacetic acid (EDTA). Good quality spectral resolution of up to seven-component mixtures was achieved (correlation coefficients between resolved and experimental spectra are not less than 0.90). In general, the relative errors in the recovered concentrations are at levels of only several percent. While being superior to other ICA algorithms, MILCA is comparable or even outperforms other classical chemometric methods for quantitative analysis that were used for comparison purposes (Partial Least Squares (PLS), Principal Component Regression (PCR), Alternating Least Squares (ALS)). Simultaneous quantitative analysis is possible for mixtures containing up to five metals in the broad concentration ranges even when individual spectra show 99% overlap. A small excess of derivatization reagent (till threefold excess to the sum of metal concentrations) is optimal to obtain good quantitative results. The proposed method was used for analysis of authentic samples (multimineral supplements and platinum concentrates). The resolved ICA concentrations match well with the labelled amounts and the results of other chemometric methods (ALS, PLS). ICA decomposition considerably improves the application range of spectroscopy for metal quantification in mixtures.