Sensitive and selective electrochemical sensor for the detection of dopamine by using AuPd@Fe2O3 nanoparticles as catalyst

This study is led by Dr. Qunyan Zhu (Changchun Institute of Applied Chemistry, Chinese Academy of Sciences). Dopamine (DA) is an important neurotransmitter that affects the central nervous system by regulating various functions, such as memory, learning, nervous system endocrine, cognition, and motor control. Abnormal levels of DA in biological fluids are largely associated with learning disabilities, affective disorders, Parkinson's disease, Huntington's disease, etc. Therefore, it is important to accurately quantify the amount of active ingredient in DA-related drugs as well as the level and fluctuation of DA in human body fluids.

In the past decades, various methods/techniques have been developed for the detection of DA, including optical assays, electrochemical (EC) sensors, mass spectrometry, capillary electrophoresis, etc. Among these methods, EC sensors have several advantages, such as fast response speed, simple operation steps and easy miniaturization. However, in normal human body fluids, the physiological levels of DA are much lower (c.a., 100 to 1000 times) than those of ascorbic acid (AA), the major interferer during EC measurement of DA. The phenomenon requires that the DA EC sensors must have superior sensitivity and selectivity. Due to slow electron transfer, unmodified electrode is normally unable to effectively and selectively detect DA. To overcome the drawbacks, the electrode surface needs to be modified with a suitable material with unique EC properties. Up to date, various materials including metal nanoparticles (NPs), metal organic frameworks, metal complexes, conducting polymers and carbon based materials have been used to modify electrode surfaces for the enhancement of EC detection performance of DA. For example, Song et al. prepared a DA-imprinted chitosan film electrode, which provided abundant active sites for the detection of DA, at the same time, the electrode pores could be specific to DA, achieving the selective detection of DA. In particular, the interference of AA can be easily eliminated by employing nanomaterial modified electrodes. Using Pt₃Ni nanoalloy modified GCE, the current signal response of the DA can be easily distinguished from those of AA and other interfering substances.

As one of catechols, the phenolic hydroxyl group of DA can generate semiquinone or quinone structure through the oxidation pathway of losing one electron or two electrons, respectively. Based on the molecular structure, the reaction principle of the EC oxidation reaction process of DA can be simplified as the oxidation process of two adjacent hydroxyl groups (-OH) on the benzene ring to ketone groups. Due to their outstanding lattice conductivity and abundant active sites, transition metals have good electrocatalytic activity for the oxidation of hydroxyl functional groups. Iron oxide NPs and their hybrids have attracted much attention in the fabrication of non-enzymatic EC sensors because of their tunable band gaps, stable physicochemical properties and excellent electrocatalytic performance. However, there are few examples on the application of iron oxide NPs and their hybrids-modified electrodes for the detection of DA in complex samples.

In this work, AuPd@Fe₂O₃ NPs with excellent catalytic performance were prepared by a facile one-pot method at room temperature. The AuPd@Fe₂O₃ NPs-based EC sensor (AuPd@Fe₂O₃ NPs/GCE) was prepared conveniently by dropping the mixture of AuPd@Fe₂O₃ NPs and Nafion on glassy carbon electrode (GCE), and firstly utilized for the detection of DA. Compared with bare GCE, the as-prepared AuPd@Fe₂O₃ NPs/GCE shows high sensitivity and anti-interference for detection of DA by chronoamperometry measurement, which can be used to accurately determine the levels of DA in pharmaceuticals and actual biological samples.

See the article:

Sensitive and selective electrochemical sensor for the detection of dopamine by using AuPd@Fe₂O₃ nanoparticles as catalyst

https://doi.org/10.1016/j.asems.2023.100048