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Issue 44, 2018
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Experimental design for metal extraction from facial cosmetics samples and determination by square wave voltammetry

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Abstract

An alternative microwave-assisted sample preparation procedure is proposed for the rapid, reliable and easy extraction of metals from facial cosmetics samples (lipstick, compact powder and eyeshadow). The mass of the sample and the nitric acid and hydrochloric acid volumes were optimised taking into account a 33 Box–Behnken design and 32 factorial with a triplicate central point. The determination of the metals (copper, lead and zinc) by square wave voltammetry (SWV) was performed, with an electrochemical system consisting of a cell with three electrodes, and hydrochloric acid and acetate buffer (pH = 4.7) as the supporting electrolytes. The extraction with microwaves presented a lower relative standard deviation and greater efficiency, since it gave higher percentages of recovery. A quantitative analysis was carried out by the method of standard additions. Good linearity was obtained in the range of the concentrations examined. Detection limits of 0.10, 0.05 and 0.22 μg g−1 were found for copper, lead and zinc, respectively, in the facial cosmetics samples. The average values found for the nine samples analysed were in the range of 14.0–26.7 μg g−1 for copper, 1.3–9.7 μg g−1 for lead and 7.1–42 064 μg g−1 for zinc. The facial cosmetics samples were also analysed by flame and graphite furnace atomic absorption spectrometry (F AAS and GF AAS), demonstrating an excellent correlation between the results.

Graphical abstract: Experimental design for metal extraction from facial cosmetics samples and determination by square wave voltammetry

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Supplementary files

Article information


Submitted
30 Jul 2018
Accepted
11 Oct 2018
First published
12 Oct 2018

Anal. Methods, 2018,10, 5327-5334
Article type
Paper

Experimental design for metal extraction from facial cosmetics samples and determination by square wave voltammetry

L. Vinicius de Faria, T. P. Lisboa, R. Arromba de Sousa, G. S. Gonçalves de Carvalho, M. A. Costa Matos and R. C. Matos, Anal. Methods, 2018, 10, 5327
DOI: 10.1039/C8AY01696H

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