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• W2100196984 abstract "Most heavy metals are present in trace concentrations in many matrices whereas concomitants are, generally, several orders of magnitude higher. Thus, when Sb was determined in water samples by electrothermal atomic absorption spectrometry (ETAAS), typical major concomitant ions Ca2+, Fe3+, Na+, Mg2+, Cl−, PO43− and SO42− induced displacement, depletion and division of its atomic peak. These interferences were handled with partial least squares regression (PLS). Plackett–Burman experimental designs were implemented to develop the calibration matrix and assess which concomitants modified the atomic signal the most. Despite the concentration-dependent effects induced by the concomitants, linear PLS was a reliable way to predict the concentration of Sb in aqueous samples (standard error of prediction = 1.44 ng mL−1). Polynomial PLS regression was also studied but it did not outperform the linear models. The multivariate-derived figures of merit were calculated: sensitivity (0.014 absorbance/(ng mL−1)), characteristic mass (6.2 pg) and selectivity (using the net analyte signal concept, 83%); limit of detection (considering 5% of type-α and type-β risks, 5.6 ng mL−1) and quantification (10.6 ng mL−1), following recent IUPAC and ISO guidelines. The method was validated studying its robustness to current ETAAS problems and analysing several certified reference waters." @default.
• W2100196984 created "2016-06-24" @default.
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• W2100196984 date "2006-01-01" @default.
• W2100196984 modified "2023-09-27" @default.
• W2100196984 title "Linear PLS regression to cope with interferences of major concomitants in the determination of antimony by ETAAS" @default.
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• W2100196984 doi "https://doi.org/10.1039/b506783a" @default.
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