Nitrogen-Doped Graphdiyne Quantum-dots as an Optical-Electrochemical sensor for sensitive detection of dopamine

Nitrogen-doped graphdiyne dots (N-GDQDs) are firstly synthesized by hydrothermal method. The prepared N-GDQDs are used for constructing a dual-mode optical-electrochemical nanosensor for sensitive and selective detection of dopamine (DA). • Graphdiyne quantum dots (N-GDQDs) are successfully prepared by hydrothermal method. • The doping N greatly improves the quantum yield, electron transport ability and conductivity of N-GDQDs. • N-GDQDs are used for constructing a dual-mode (optical-electrochemical) nanosensor for dopamine detection. Graphdiyne quantum dots (GDQDs) have attracted increasing attentions due to its unique electronic, optical, and electrochemical properties. However, the low conductivity and quantum yield of GDQDs limit their application. Here, nitrogen-doped graphdiyne dots (N-GDQDs) are firstly synthesized by a simple, friendly and one-step hydrothermal method. The N-GDQDs show a maximum emission at 410 nm under the excitation wavelength of 319 nm. The doping N modifies the surface defect of N-GDQDs and further greatly improves their quantum yield (from 14.6% to 48.6%). In addition, the doping N induces a strong electron transport ability and good conductivity of N-GDQDs. Subsequently, the prepared N-GDQDs are used for constructing an optical-electrochemical nanosensor for sensitive and selective detection of dopamine (DA). DA can quench the fluorescence of N-GDQDs by forming a ground-state non-fluorescent complex between phenoxy anions (in PBS solution) in DA and pyridinic N sites of N-GDQDs, which leads to a highly sensitive and selective detection of DA with a limit of detection (LOD) of 0.14 μM and a linear range of 0.32–500 μM. In the electrochemical detection, DA can be oxidized to DA-quinone under the electric field through N-GDQDs/GCE, which shows a big affinity to N-GDQDs. The LOD for DA is 0.02 μM with a linear range of 0.05–240 μM. Finally, the spiked application for DA detection in human serum samples is investigated, the results show that the method has high accuracy. Our work provides a new carbon quantum dots based sensing platform, which shows great potential in practical application.