BPN927: CeO2/Au Nanostructured Material for Electrochemical Detection of Dopamine

Abstract: 

Dopamine (DA) plays a significant role in the central nervous system, the loss of which is linked to various problems, e.g., schizophrenia, drug addiction and Parkinsons disease. Accordingly, the development of sensitive and selective detection method for DA is of great interest. Electrochemical DA detection has gained increasing attention due to its operation simplicity and rapid response. Despite these advantages, electrochemical methods often lack sensitivity and selectivity. This is specially challenging given that the normal concentration of DA in human body is less than 10 nM, which is much less than the concentration of interferences (such as ascorbic acid and uric acid), which have similar electrochemical oxidation potential to DA. Here, the goal of this research is to develop active electrode material that has high sensitivity and selectivity toward electrochemical detection of dopamine. Electrode surface structure and functional modification with higher catalytic response are of great interest in electrochemistry. Numerous studies have focused on the structural design of nano- catalysts to achieve higher electrochemically active surface area and doping to optimize the electronic properties with higher electrocatalytic activity. Cerium oxide is a redox active material due to the co-existence of partially reduced Ce3+ and Ce4+, and its redox state can be further adjusted via changing its chemical structure, thus showing potential application in electrochemical detection. This work aims at designing highly efficient nano-structured CeO2 based electrochemical catalyst. Using the calixarene capped gold nanocluster as precusor, the gold can be deposited onto the CeO2 surface via hydrothermal methods. Then, different post treatment methods can be applied to change the composition, surface morphology and chemistry of the CeO2/Au compound, allowing its electrochemical properties to be adjusted correspondingly for efficient and effective sensing.

Project end date: 11/27/19

Author: 
Yuhui Xie
Publication date: 
August 7, 2019
Publication type: 
BSAC Project Materials (Final/Archive)
Citation: 
PREPUBLICATION DATA - ©University of California 2019

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