4.5 Article

Application of ionic liquid-based microwave-assisted extraction of malachite green and crystal violet from water samples

期刊

JOURNAL OF SEPARATION SCIENCE
卷 36, 期 6, 页码 1112-1118

出版社

WILEY-V C H VERLAG GMBH
DOI: 10.1002/jssc.201200835

关键词

Crystal violet; Ionic liquid; Malachite green; Microwave assisted extraction

资金

  1. National Natural Science Foundation of China [21177055, 50938004]
  2. Environment Monitoring Fund of Jiangsu Province [1115]
  3. Graduate Education Innovation of Jiangsu Province [CXZZ11_0050]
  4. Special Fund for Environmental Protection Research in the Public Interest [201209016]

向作者/读者索取更多资源

A simple, environment friendly and efficient technique, ionic liquid-based microwave-assisted extraction was first used to determine malachite green and crystal violet (CV) from water samples coupled to HPLC. The key parameters influencing extraction efficiency were investigated, such as the type of ionic liquids, the volume of ionic liquid, extraction time, and so on. Under the optimum conditions, good reproducibility of the extraction performance was obtained (RSD, 1.0% for malachite green (MG) and 5.9% for CV, n = 5). Good linearity (0.10-25 mu g L-1) was observed with correlation coefficients between 0.9991 and 0.9964. The detection limits of MG and CV were 0.080 and 0.030 mu g L-1, respectively. The proposed method had been successfully applied to determine MG and CV in real water samples with recoveries ranging from 95.4 to 102.8%. Compared with the previous technologies, the proposed method required less extraction time (2 min), and provided lower detection limits and higher enrichment factors. Moreover, there were no volatile and hazardous organic solvents released. Based on these simple, environment friendly, rapid, and highly efficient results, the proposed approach provides a new and promising alternative for simultaneously extracting trace amounts of MG and CV from water.

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。

评论

主要评分

4.5
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据