4.7 Article

Poly(N-isopropylacrylamide-co-N,N′-methylene bisacrylamide) monolithic column embedded with γ-alumina nanoparticles microextraction coupled with high-performance liquid chromatography for the determination of synthetic food dyes in soft drink samples

期刊

TALANTA
卷 105, 期 -, 页码 386-392

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.talanta.2012.10.065

关键词

Polymer monolithic column; gamma-Alumina nanoparticles; High-performance liquid chromatography; Synthetic food dyes

资金

  1. National Natural Science Foundation of China [21205047]
  2. Jilin Provincial Science & Technology Department [201105102]
  3. Open Project of State Key Laboratory of Supramolecular Structure and Materials, Jilin University [sklssm201218]

向作者/读者索取更多资源

The present work proposes a study of the synthesis of poly(N-isopropylacrylamide-co-N,N'-methylene bisacrylamide) monolithic column embedded with gamma-alumina nanoparticles and its applications to the extraction of synthetic food dyes in soft drink samples. The monolithic column was synthesized inside fused silica capillaries using thermally initiated free-radical polymerization with N-isopropylacrylamide (NIPAAm) as the monomer, N,N'-methylene bisacrylamide (MBAAm) as the cross-linker, dimethylsulfoxide (DMSO) and dodecanol as the porogen. gamma-Alumina nanoparticles were introduced to prevent the swelling of the organic polymer and enhance the loading capacity. In order to obtain optimum experimental conditions, sample pH, sample flow rate, sample volume, eluent flow rate were investigated. Under the optimum conditions, we obtained acceptable linearities, low limits of detection, and good intra-day/inter-day relative standard deviations. When applied to the determination of four synthetic food dyes (Tartrazine, Sunset Yellow, Allura Red, and Azorubine) in soft drink samples, satisfactory recoveries were obtained in the range of 90.4-109.2%. (C) 2012 Elsevier B.V. All rights reserved.

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

4.7
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