A dual action electrochemical molecularly imprinted aptasensor for ultra-trace detection of carbendazim

Carbendazim is often used in agriculture to prevent crop diseases, even though it has been associated with health concerns. To ensure the safety of food products and comply with environmental regulations, an ultrasensitive method for carbendazim determination must be developed. In this study, a new electrochemical molecularly imprinted polymer-aptasensor based on hemin-Al-metal organic framework@gold nanoparticles (H-Al-MOF@AuNPs) was developed for sensitive and selective carbendazim detection. Hemin linked to the surface of the Al-metal organic framework also possesses outstanding peroxidase-like qualities that can electrocatalyse the reduction of H2O2. Thus, H-Al-MOF functions as an in-situ probe. Additionally, AuNPs offer many binding sites to load carbendazim aptamers and create an imprinted polymer-aptasensing interface. Dopamine is the chemical functional monomer in the electropolymerised film, while carbendazim is the template molecule. Thus, compared to the molecularly imprinted polymer or aptasensor alone, the molecularly imprinted polymer-aptasensor showed greater selectivity due to the synergistic action of the polymer and carbendazim aptamer towards carbendazim. A decrease in peak current was observed by differential pulse voltammetry (DPV) and chronoamperometry (CA) as the concentration of carbendazim increased. This possibly resulted from carbendazim connecting to the carbendazim aptamer and simultaneously blocking the imprinted polymer cavities on the surface of the modified electrode, which reduced the transfer of electrons. Signals were observed for hemin DPV and H2O2 catalytic reduction CA. DPV and CA showed that the linear ranges for carbendazim were 0.3 fmol L-1-10 pmol L-1 and 0.7 fmol L-1-10 pmol L-1, respectively, with limits of detection of 80 and 300 amol L-1. Satisfactory recoveries were obtained with tap water, apple juice, and tomato juice samples, demonstrating that the proposed sensor has potential for food and environmental analysis.