期刊
JOURNAL OF ANALYTICAL ATOMIC SPECTROMETRY
卷 38, 期 2, 页码 315-324出版社
ROYAL SOC CHEMISTRY
DOI: 10.1039/d2ja00273f
关键词
-
This work describes a novel and highly sensitive method for the determination of cadmium at ultratrace levels. The method combines dispersive magnetic solid phase extraction (DMSPE), direct magnetic sorbent sampling (DMSS), and flame furnace atomic absorption spectrometry (FF-AAS). The method showed significantly higher analytical performance compared to other techniques, with a remarkable increase in sensitivity. Under the optimized conditions, the method demonstrated excellent accuracy and precision for cadmium determination in various samples.
A novel and highly sensitive method for cadmium determination at ultratrace levels combining dispersive magnetic solid phase extraction (DMSPE), direct magnetic sorbent sampling (DMSS), and flame furnace atomic absorption spectrometry (FF-AAS) is described in this work. A magnetic carbon-based nanocomposite (Fe3O4@C) was used as the sorbent for cadmium preconcentration using DMSPE. The Fe3O4@C particles were easily separated from the aqueous medium by employing a magnetic stainless steel rod and directly inserting it inside a nickel tube heated by a flame. The method (DMSS-FF-AAS) showed substantially higher analytical performance when compared to FAAS, TS-FF-AAS (direct analysis), and TS-FF-AAS using preconcentration and elution steps, evidenced by a remarkable increase in the sensitivity of 2502, 151 and 41 times, respectively. Under the optimized conditions, the limit of detection, linearity, and the precision in terms of repeatability (n = 10) assessed as the relative standard deviation (RSD%) were found to be 5 ng L-1, 15-750 ng L-1, and 1-4%, respectively. The accuracy of the method was attested by analysis of certified reference materials, CRM-1643e (water) and CRM-1573a (tomato leaves). The proposed method was successfully applied for cadmium determination in mineral and lake water samples ranging from 16 to 465 ng L-1.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据