4.2 Article

Selective Electrochemical Detection of Dopamine Using Reduced Graphene Oxide Sheets-Gold Nanoparticles Modified Electrode

期刊

JOURNAL OF NANOSCIENCE AND NANOTECHNOLOGY
卷 17, 期 11, 页码 8012-8018

出版社

AMER SCIENTIFIC PUBLISHERS
DOI: 10.1166/jnn.2017.15073

关键词

Dopamine; Electrochemical Sensor; Graphene; Gold Nanoparticles

资金

  1. National Research Foundation of Korea (NRF) - Korean Government (MSIP) [2015R1A2A2A01007843]
  2. Sogang University [201710007]
  3. National Research Foundation of Korea [2015R1A2A2A01007843] Funding Source: Korea Institute of Science & Technology Information (KISTI), National Science & Technology Information Service (NTIS)

向作者/读者索取更多资源

Dopamine (DA) is one of the most significant neurotransmitters, and it has a major role in the central nervous system, such as in cognition, motivation, and memory. Some neural diseases, including Alzheimer's disease (AD) and Parkinson's diseases (PD), are related with a lack of DA. Thus, the detection of DA is necessary for the early diagnosis of such diseases. In this study, we fabricate an electrochemical sensor by modifying an electrode with reduced graphene oxide sheet (rGS)-gold nanoparticle (GNP) complexes to determine DA and ascorbic acid (AA) in a mixture within a range of 0.1-100 mu M. The rGS was used to improve the selectivity of the sensor by having pi-pi interaction with DA, and the GNPs improved the sensitivity due to their great conductivity and large surface area. As a result, when the GNPs were immobilized on the rGS surface, the sensor exhibited greatly improved electrocatalytic activity compared with other cases, such as the individual application of rGS or GNPs. The performance of the sensor with the modified electrode was confirmed by scanning electron microscopy (SEM), cyclic voltammetry (CV), and differential pulse voltammetry (DPV) measurements. The results showed that it had linearity in the range of 0.1-100 mu M of DA and the limit of detection was 0.098 mu M in the presence of AA 400 mu M. Therefore, it could be applied to medical biosensors to diagnose neural diseases.

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