4.5 Article

Magnetic solid-phase extraction based on magnetic carbon nanotube for the determination of estrogens in milk

Journal

JOURNAL OF SEPARATION SCIENCE
Volume 34, Issue 18, Pages 2498-2504

Publisher

WILEY-V C H VERLAG GMBH
DOI: 10.1002/jssc.201100323

Keywords

Aggregation wrap; Carbon nanotube; Estrogen; Magnetic nanoparticle; Magnetic solid-phase extraction

Funding

  1. National Nature Science Foundation [91019013, 31070327]
  2. NSFC [20921062]
  3. Fundamental Research Funds for the Central Universities

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In this work, a novel method for the fabrication of magnetic carbon nanotubes based on 'aggregation wrap' was proposed. When carbon nanotubes and magnetic nanoparticles were vortically mixed in a solvent, the magnetic nanoparticles were wrapped into the carbon nanotube bundles that formed during the aggregation process, leading to the formation of magnetic carbon nanotubes. Thus, the resultant material can be separated from the solvent rapidly and conveniently by a magnet. Our investigation demonstrated that the 'aggregation wrap' mechanism for the preparation of magnetic composite is also applicable to other self-aggregated micro/nanomaterials, including graphene, graphite, C-60, etc. To testify the feasibility of the magnetic composites in sample preparation, the resultant magnetic carbon nanotubes were applied as sorbents for magnetic solid-phase extraction (MSPE) of estrogens in milk samples. Under optimized conditions, a rapid, convenient and efficient method for the determination of estrogens in milk samples was established by the combination of MSPE with high-performance liquid chromatography with fluorescence detector. The linearity range of the proposed method was 5-2000 mu g/L with correlation coefficients (R) of 0.9983-0.9994. The limit of detection (LOD) for three estrogens ranged from 1.21 to 2.35 mu g/L. The intra-and inter-day relative standard deviations (RSDs) were <9.3%. The reproducibility of the MSPE with different batches of magnetic carbon nanotubes was acceptable with RSD values <3.6%.

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