Electrochemical sensor based on molecularly imprinted polymer film via sol–gel technology and multi-walled carbon nanotubes-chitosan functional layer for sensitive determination of quinoxaline-2-carboxylic acid

• A novel MIP sensor for quinoxaline-2-carboxylic acid detection was established.
• MWNTs-CS functional layer was introduced to improve performance of the sensor.
• Sol–gel technology was applied to form recognition element of the sensor.
• In detail, performance of the sensor was discussed through various methods.
• The established MIP sensor could be promising in food safety analysis.

Quinoxaline-2-carboxylic acid (QCA) is difficult to measure since only trace levels are present in commercial meat products. In this study, a rapid, sensitive and selective molecularly imprinted electrochemical sensor for QCA determination was successfully constructed by combination of a novel modified glassy carbon electrode (GCE) and differential pulse voltammetry (DPV). The GCE was fabricated via stepwise modification of multi-walled carbon nanotubes (MWNTs)-chitosan (CS) functional composite and a sol–gel molecularly imprinted polymer (MIP) film on the surface. MWNTs-CS composite was used to enhance the electron transfer rate and expand electrode surface area, and consequently amplify QCA reduction electrochemical response. The imprinted mechanism and experimental parameters affecting the performance of MIP film were discussed in detail. The resulting MIP/sol–gel/MWNTs-CS/GCE was characterized using various electrochemical methods involving cyclic voltammetry (CV), electrochemical impedance spectroscopy (EIS) and DPV. The sensor using MIP/sol–gel/MWNTs-CS/GCE as working electrode showed a linear current response to the target QCA concentration in the wide range from 2.0×10−6 to 1.0×10−3 mol L−1 with a low detection limit of 4.4×10−7 mol L−1 (S/N=3). The established sensor with excellent reproductivity and stability was applied to evaluate commercial pork products. At five concentration levels, the recoveries and standard deviations were calculated as 93.5–98.6% and 1.7–3.3%, respectively, suggesting the proposed sensor is promising for the accurate quantification of QCA at trace levels in meat samples.