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Preconcentration Techniques

Ultrasensitive Determination of Arsenic in Juvenile Eyeshadow by Novel Dispersive Magnetic Solid-Phase Extraction (MSPE) and Flow Injection Analysis – Hydride Generation Atomic Absorption Spectrometry (FIA-HG-AAS)

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Pages 132-147 | Received 02 Apr 2022, Accepted 15 Jun 2022, Published online: 27 Jun 2022
 

Abstract

A new procedure is reported for arsenic preconcentration in juvenile eyeshadow using maghemite nanoparticles (γ-Fe2O3) and determination by flow injection analysis – hydride generation atomic absorption spectrometry (FIA-HG-AAS). Maghemite nanoparticles were synthesized and characterized using X-ray diffraction (XRD), Fourier-transform infrared spectroscopy (FTIR), and N2 adsorption measurements at −196 °C. The results showed a crystalline size of 9.1 nm and a surface area of 106 m2 g−1. The experimental conditions for the hydride generation system and the preconcentration process were optimized using a central composite design. For hydride generation, the levels of the concentration of the factors HCl, NaBH4, and flow of carrier gas were optimized, with optimal conditions of 4 mol L−1, 1.1% (m/v), and 145 mL min−1, respectively. The optimized conditions obtained for the adsorption process were a pH equal to 5.3, a mass of γ-Fe2O3 of 184 mg, and stirring time of 41 min in the presence of the sample matrix. The enrichment factor was 50, and the limit of detection was 0.9 μg g−1. Recovery values ranged from 75 to 99%.

Disclosure statement

The authors report there are no competing interests to declare.

Additional information

Funding

This work was supported by the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq); Coordenação de Aperfeiçoamento de Pessoal de Nível Superior - Brazil (CAPES) Finance Code 001; and Fundação de Amparo à Pesquisa no Rio de Janeiro (FAPERJ) under grant numbers E-26/202.552/2019, E-26/202.755/2019, E-26/010.002212/2019; and the Universidade do Estado do Rio de Janeiro (Programa Pró-Ciência). JSG and ASL have research scholarship from UERJ (Programa Pró-Ciência), and CNPq (grant numbers 302465/2018-9, 304869/2019-8).

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