4.6 Article

Hollow molecular imprinted polymers towards rapid, effective and selective extraction of caffeic acid from fruits

Journal

JOURNAL OF CHROMATOGRAPHY A
Volume 1470, Issue -, Pages 27-32

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.chroma.2016.10.006

Keywords

Molecularly imprinted polymers; Hollow structure; Selective extraction; Caffeic acid; Fruit

Funding

  1. National Natural Science Foundation of China [21275163]
  2. Science and Technology Program of Hunan Province, China [2015NK3037]
  3. Project of Innovation-driven Plan in Central South University [2016CX036]

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Rapid and selective extraction and enrichment of trace bioactive analytes from complex matrices were of significant importance for efficient and accurate quantification. Here, novel hollow molecular imprinted polymers (HMIPs) were prepared using caffeic acid (CA) as template, 4-vinylpyridine (4-VP) as functional monomer, and Fe3O4@SiO2 as sacrificial support. Fourier transform infrared spectrometer (FT-IR), transmission electron microscopy (TEM), nitrogen adsorption and, thermo-gravimetric analysis (TGA) were used to verify the successful synthesis of HMIPs. Hollow structure with large surface area (325.8 m(2)/g) made most recognition sites locate on the surface of HMIPs, resulting in high binding capacity (21.10 mg/g) and fast kinetic binding (35 min) in comparison with magnetic MIPs (MMIPs) and solid MIPs. The equilibrium data fitted well to Freundlich equation and the adsorption process could be described by pseudo-second order model. The selectivity performance of HIVIIPs was favorable. Finally, HMIPs were successfully used as adsorbent to rapidly and selectively extract and enrich CA from fruits with a relatively satisfactory recovery (85.6-103.5%). Coupling with high-performance liquid chromatography (HPLC), the content of CA in four kinds of fruits (kiwifruit, apple, papaya and waxberry) was determined as less than 1.0 mu g/g fresh fruit. Results indicated the superiority of HMIPs in the selective extraction of target compound from complex matrices. (C) 2016 Elsevier B.V. All rights reserved.

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