Synthesis And Modification Of Mercapto-Submicron Scavenger For Real-Time Extraction And Preconcentration Of As(Iii)

Abstract

The gradual increase of arsenic in aquatic layers over the last decades has necessitated the early detection of low levels of arsenic on real time due to its hazardous impact on health. Here, the mercapto-submicron scavenger was synthesized and utilized for solid-phase dispersion extraction technique for real-time extraction and preconcentration of arsenite As(iii). Because of particle size, they naturally dispersed without the need for any additional power. The formation of particles and the achievement of the modification of the particles were confirmed by SEM, TEM, size distributions, CHN analysis, FT-IR spectroscopy, micro-Raman spectroscopy, X-ray photoelectron spectroscopy (XPS), zeta potential, energy dispersive X-ray analysis and (EDX) and thermogravimetric analysis (TGA), which confirmed the formation of particles in the size of 253 ± 34 nm, the chemical implantation of the mercapto groups on the surface was successfully accomplished with a loading of 0.281 mmol g-1. The particles showed proper dispersion and stability in the aqueous phase before and after being associated with As(iii). The chelating process between As(iii) and mercapto groups was assessed by XPS which confirmed that the mercapto-submicron scavenger can sequestrate As(iii) from water with maximum efficiency. Several factors that could optimize the process were assessed such as the effect of sorbent dose, pH, contact time, sample volumes, eluents, and matrix interference. The As(iii) calibration curve showed a positive linear correlation in the range of 0-100 μg L-1 and coefficient of determination (r2 = 0.9981). Optimum recovery was obtained with an equilibrium time of 30 min at pH = 8.5. It was found that the release of As(iii) from the mercapto-submicron scavenger was eluent dependent and the maximum recovery at the optimum conditions was 98 ± 3%. The average recovery of As(iii) from three different ground water locations was 97.15%.

Publication Date

1-1-2018

Publication Title

Analytical Methods

Volume

10

Issue

2

Number of Pages

245-255

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1039/c7ay02490h

Socpus ID

85040183165 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/85040183165

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