- Electrochemiluminescence sensor based on upconversion nanoparticles and oligoaniline-crosslinked gold nanoparticles imprinting recognition sites for the determination of dopamine.
Electrochemiluminescence sensor based on upconversion nanoparticles and oligoaniline-crosslinked gold nanoparticles imprinting recognition sites for the determination of dopamine.
For the determination of dopamine (DA) in serum samples, a quenching-type electrochemiluminescence sensor (MIECLS) was constructed in this study. Upconversion nanoparticles (UCNPs) enhanced by covalent organic frameworks (COFs)-based hybrid and oligoaniline-crosslinked gold nanoparticles (AuNPs) imprinting recognition sites were introduced in electrochemiluminescence (ECL) system at the first time. The porous COFs-based hybrid with large specific surface area was modified on the electrode firstly to hold more UCNPs and imprinting recognition sites. AuNPs was employed in the developed sensor for two objectives: 1) AuNPs on the COFs-based hybrid enabled the hybrid to tunnel the electrons, which helped to improve the ECL intensity; 2) AuNPs-based thioaniline units (PATP@AuNPs) electropolymerized on the electrode in the presence of template to form oligoaniline-crosslinked AuNPs matrix. Then the exclusion of template from matrix yielded the molecularly three-dimensional imprinted contours with conductivity, which facilitated specific recognition and further amplified the ECL. The double recognition mode in this work involves the recognition effect of imprinted contours and quenching effect of o-benzoquinone species. The quantum chemical calculation was performed to analyze the possible recognition and the binding mechanisms of molecularly three-dimensional imprinted contours. The results showed imprinted contours could bind the targets by complementary spatial cavities and weak interactions. The proposed approach yielded a wide detection range (10-14-10-6 M), low limit of detection (LOD = 2 ×10-15 M) and acceptable recoveries (93.25-112.97%) in rat serum sample, demonstrating that the developed method holds great promise to be applied to DA detection in practical samples.