Defective Metal–Organic Framework Nanocrystals as Signal Amplifiers for Electrochemical Dopamine Sensing

The electrochemical sensing system has been recognized as a promising and facile approach to detect dopamine (DA), a crucial neurotransmitter in the human body. However, the rational design of electrode materials is important in order to selectively detect DA in the presence of coexisting interferents, such as ascorbic acid (AA) and uric acid (UA). In this study, a water-stable and nanoporous zirconium-based metal–organic framework (MOF), UiO-66, is synthesized with a tunable degree of missing-linker defects, and the corresponding crystallinity, morphology, porosity, and degree of defects are characterized. Although all the UiO-66 synthesized here is electrically insulating and electrochemically inactive, the thin film of defective UiO-66 deposited on the electrode surface can significantly amplify the electrochemical sensing signal for DA. The effect of the degree of defects on the resulting sensing response for DA is examined, and the origin of such a signal amplification effect, which is relevant to the hopping-based electrochemical process of the irreversibly adsorbed DA in the defective MOF, is investigated. By serving the defective UiO-66 as a signal amplifier casted on top of another electrically conductive active material capable for selective DA detection, the modified electrode for sensing DA with enhanced performances can be developed. As a proof-of-concept demonstration, the defective UiO-66 thin film was coated on the graphene oxide (GO) modified electrode. With the use of such a bi-layer thin film for DA sensing, a much higher sensitivity (6.4-fold), a much smaller limit of detection (0.23-fold), and a better selectivity toward DA against AA and UA (2.6-fold and 1.2-fold, respectively) can be achieved compared to those of the GO thin film. Experimental results here shed light on the use of such porous MOF coatings to effectively enhance the sensing performances of other developed electrochemical sensing systems for DA.