Effect of different precursors on generation of reference spectra for structural molecular background correction by solid sampling high-resolution continuum source graphite furnace atomic absorption spectrometry: Determination of antimony in cosmetics

Abstract

Different precursors were evaluated for the generation of reference spectra and correction of the background caused by SiO molecules in the determination of Sb in facial cosmetics by high-resolution continuum source graphite furnace atomic absorption spectrometry employing direct solid sample analysis. Zeolite and mica were the most effective precursors for background correction during Sb determination using the 217.581nm and 231.147nm lines. Full 2 factorial design and central composite design were used to optimize the atomizer temperature program. The optimum pyrolysis and atomization temperatures were 1500 and 2100°C, respectively. A Pd(NO)/Mg(NO) mixture was employed as the chemical modifier, and calibration was performed at 217.581nm with aqueous standards containing Sb in the range 0.5-2.25ng, resulting in a correlation coefficient of 0.9995 and a slope of 0.1548s ng. The sample mass was in the range 0.15-0.25mg. The accuracy of the method was determined by analysis of Montana Soil (II) certified reference material, together with addition/recovery tests. The Sb concentration found was in agreement with the certified value, at a 95% confidence level (paired t-test). Recoveries of Sb added to the samples were in the range 82-108%. The limit of quantification was 0.9mgkg and the relative standard deviation (n=3) ranged from 0.5% to 7.1%. From thirteen analyzed samples, Sb was not detected in ten samples (blush, eye shadow and compact powder); three samples (two blush and one eye shadow) presented Sb concentration in the 9.1-14.5mgkg range.

Traditional Calibration Methods in Atomic Spectrometry and New Calibration Strategies for Inductively Coupled Plasma Mass Spectrometry

“…Direct solid sampling and HR-CS GF AAS determination using aqueous standard solutions and EC may significantly improve sample throughput, as minimal sample preparation is required. As examples of such a strategy we have elemental analysis of cheese (Tinas et al, 2017 ), fertilizers (Souza et al, 2015 ), spices (Virgilio et al, 2015 ), eye shadow (Barros et al, 2014 , 2015 , 2016 ), incense (Coco et al, 2017 ), high-purity silicon (Bechlin et al, 2016 ), and soil (Babos et al, 2017 ; Table 1 ).…”