Preparation and Application of a Chloramphenicol Electrochemical Sensor Based on Molecularly Imprinted Polymer
  
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KeyWord:chloramphenicol  molecular imprinting  electrochemical detection  bifunctional monomer  hydroxylated multi-walled carbon nanotubes  aluminium oxide
  
AuthorInstitution
HUANG Xiang-jin, LI Jian-wen, WEI Shou-lian,ZHANG Hua-sheng 1. Zhaoqing Institute for Food Control, Zhaoqing , China;2. Guangdong Food and Drug Vocational College, Guangzhou , China;3. College of Environmental and Chemical Engineering, Zhaoqing University, Zhaoqing , China
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Abstract:
      A novel molecularly imprinted electrochemical sensor sensitized with aluminium oxide (Al2O3) and hydroxylated multi-walled carbon nanotubes(MWCNTs) was prepared for the sensitive determination of chloramphenicol(CAP) by using CAP as template molecule, m-aminophenol(MAP) and β-cyclodextrin(β-CD) as binary functional monomers. The surface morphology and electrochemical performance of the imprinted sensor were characterized by scanning electron microscopy(SEM), differential pulse voltammetry(DPV) and electrochemical impedance spectroscopy(EIS). The experimental parameters influencing the response of the imprinted sensor, such as modification amount of MWCNTs and Al2O3, molar ratio of template molecule to functional monomer, number of electropolymerization cycles, eluent type, elution time, pH value and incubation time were also optimized. Results showed that the prepared sensor exhibited high selectivity and sensitivity in the detection of CAP, which was attributed to the synergistic effect of Al2O3 and MWCNTs to significantly enhance the surface area and catalytic performance of the modified electrode, as well as high affinity and selectivity of imprinted membrane prepared with the binary functional monomers. Under the optimal conditions, the peak current was linearly related to the CAP concentration in the range of 1.0-60.0 nmol/L, with a detection limit(3S/k) of 0.14 nmol/L. The sensor was applied to detect CAP in tap water, chicken feedstuff and milk samples, with recoveries of 88.0%-110% and relative standard deviations less than 10%. The proposed method is simple, accurate and reliable.
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