Handling complex effects in slurry-sampling-electrothermal atomic absorption spectrometry by multivariate calibration

• Published in: Analytica chimica acta Vol. 571; no. 2; pp. 315 - 323
• Main Authors: Felipe-Sotelo, M., Cal-Prieto, M.J., Gómez-Carracedo, M.P., Andrade, J.M., Carlosena, A., Prada, D.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 07.07.2006; Elsevier
• Subjects: Analytical chemistry; Antimony; Applied sciences; Artificial neural networks; Chemical interferences; Chemistry; Electrothermal atomic absorption spectrometry; Environmental solid sample slurries; Exact sciences and technology; Global environmental pollution; Partial least squares; Pollution; Spectrometric and optical methods; Antimony; Partial least squares; Chemical interferences; Environmental solid sample slurries; Artificial neural networks; Electrothermal atomic absorption spectrometry; Multivariate analysis; Fly ash; Coal; Robustness; Sampling; Graphite furnace; Interference; Calibration; Neural network; Particle suspension; Sediments; Certified reference material; PLS regression; Soils; Chemical modification; Experimental design; Linearity; Non linear model; Thermoelectric atomization; Environment; Slurries; Atomic absorption spectrometry
• ISSN: 0003-2670; 1873-4324
• DOI: 10.1016/j.aca.2006.05.004

Analysis of solid samples by slurry-sampling-electrothermal atomic absorption spectrometry (SS-ETAAS) can imply spectral and chemical interferences caused by the large amount of concomitants introduced into the graphite furnace. Sometimes they cannot be solved using stabilized temperature platform furnace (STPF) conditions or typical approaches (previous sample ashing, use of chemical modifiers, etc.), which are time consuming and quite expensive. A new approach to handle interferences using multivariate calibrations (partial least squares, PLS, and artificial neural networks, ANN) is presented and exemplified with a real problem consisting on determining Sb in several solid matrices (soils, sediments and coal fly ash) as slurries by ETAAS. Experimental designs were implemented at different levels of Sb to develop the calibration matrix and assess which concomitants (seven ions were considered) modified the atomic signal mostly. They were Na + and Ca 2+ and they induced simultaneous displacement, depletion (enhancement) and broadening of the atomic peak. Here it is shown that these complex effects can be handled in a reliable, fast and cost-effective way to predict the concentration of Sb in slurry samples of several solid matrices. The method was validated predicting the concentrations of five certified reference materials (CRMs) and studying its robustness to current ETAAS problems. It is also shown that linear PLS can handle eventual non-linearities and that its results are comparable to more complex (non-linear) models, as those from ANNs.