4.7 Article

Highly sensitive and selective detection of dopamine using overoxidized polypyrrole/sodium dodecyl sulfate-modified carbon nanotube electrodes

期刊

出版社

ELSEVIER SCIENCE SA
DOI: 10.1016/j.jelechem.2019.113295

关键词

Dopamine; Polypyrrole; Carbon nanotubes; Overoxidation; Electrochemical sensor; In vitro monitoring

资金

  1. Engineering Research Center of Excellence (ERC) Program
  2. National Research Foundation of Korea (NRF), Korean Ministry of Science ICT (MSIT) [NRF-2017R1A5A1014708]
  3. National Research Foundation of Korea (NRF)
  4. MSIT
  5. MOTIE
  6. ME
  7. NFA [2017M3D9A073509]
  8. KRIBB Initiative Research Program
  9. KNPA

向作者/读者索取更多资源

Dopamine (DA), an organic chemical neurotransmitter in the human brain, plays important roles in neuronal reward, motor control, and decision making. Thus, accurate quantification of DA concentration is essential for the investigation of various dopaminergic neural circuits and diagnosis of neurological diseases. Herein, we report an overoxidized polypyrrole/sodium dodecyl sulfate (SDS)-modified multi-walled carbon nanotube (OPPy/SDS-CNT) electrode which allows detection of DA with high resolution and selectivity. By using SDS as a dopant and sodium hydroxide (NaOH) as an oxidizing agent, highly sensitive detection of DA down to 5 nM with a detection limit of 136 pM is achieved. Moreover, due to the strong electrostatic interaction between the negatively-charged electrode and the positively-charged DA molecules, selective electrochemical detection of DA is successfully demonstrated in the presence of ascorbic acid (AA) and glucose (Glc). Lastly, by demonstrating in vitro detection of DA secreted from dopaminergic cells (PC12 cells) and examining biocompatibility of the electrode, we show the potential of our OPPy/SDS-CNT electrode as a promising candidate for a functional neural interface for in vitro and in vivo monitoring of DA concentrations.

作者

我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。

评论

主要评分

4.7
评分不足

次要评分

新颖性
-
重要性
-
科学严谨性
-
评价这篇论文

推荐

暂无数据
暂无数据