4.7 Article

Preparation of molecularly imprinted polymers using theanine as dummy template and its application as SPE sorbent for the determination of eighteen amino acids in tobacco

期刊

TALANTA
卷 150, 期 -, 页码 388-398

出版社

ELSEVIER SCIENCE BV
DOI: 10.1016/j.talanta.2015.12.038

关键词

Dummy template; Surface molecularly imprinted polymers; Solid phase extraction; Amino acids; Tobacco

资金

  1. Ministry of Science and Technology of the People's Republic of China
  2. General Administration of Quality Supervision, Inspection and Quarantine of the People's Republic of China (AQSIQ) [201210071]

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In this paper, a novel dummy template molecularly imprinted polymer (DMIP) based on a vinyl-SiO2 microspheres surface for the simultaneous selective recognition and enrichment of 18 amino acids was prepared via a surface molecular imprinting technique using theanine as a dummy template. Compared to the imprinted polymers prepared using traditional polymerization techniques, the obtained DMIPs exhibited a regular spherical shape and were relatively monodisperse. The maximal sorption capacity (Q(max)) of the resulting DMIPs for the 18 amino acids was up to 14443 mg g(-1). A kinetic binding study showed that the sorption capacity reached 85.40% of Q(max) in 25 min and sorption equilibrium at 30 min. The imprint factors of the sorbents ranged from 2.86 to 6.9 for the 18 amino acids, which indicated that the DMIP sorbents have high selectivity. An HPLC-UV method for the simultaneous determination of 18 amino acids in tobacco and tobacco smoke was developed using the DMIPs as sorbents for solid phase extraction (SPE) in the sample pretreatment procedure. Under the optimum experimental conditions, the materials had enrichment factors of up to 200 for the amino acids, and the recoveries of the 18 amino acids in tobacco smoke were in the range from 79% to 104% with relative standard deviations of less than 7.4%. It indicated that the obtained DMIP sorbents could specifically recognize the amino acids from complicated samples. (C) 2015 Elsevier B.V. All rights reserved.

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