Rich‐defect carbon nanotubes for highly sensitive detection of Dopamine

Author:

Jiang Li Ke12,Li Juan12,Shi Fan23,Peng Gan Li12,Sun Wei3,Song Lu Zhi1,Zou Zhuo24,Ming Li Chang2ORCID

Affiliation:

1. School of Materials and Energy Southwest University Chongqing 400715 China

2. Institute of Materials Science and Devices Suzhou University of Science and Technology Suzhou 215011 China

3. College of Chemistry and Chemical Engineering Hainan Normal University Haikou 571158 China

4. Faculty of Psychology Southwest University Chongqing 400715 China

Abstract

AbstractDopamine (DA) plays an essential role in the central nervous, renal, hormonal and cardiovascular systems. Various modified carbon nanotubes (CNT)‐based dopamine sensors have been reported, but inexpensive, highly sensitive plain CNT‐based ones are seldom studied. In this work, a facile and inexpensive CNT‐based DA sensor is made by rich‐defect multi‐walled carbon nanotubes (RD‐CNT) via an ultrasound method. The defect and elemental states of the RD‐CNT are systematically studied by transmission electron microscopy (TEM), high‐resolution transmission electron microscopy (HR‐TEM), Raman spectroscopy, X‐ray powder diffraction (XRD) and X‐ray‐photoelectron spectroscopy (XPS). Results show that massive holes and cracks exist in RD‐CNT. The level of defects increases from the additional exposed edges. The electrochemical characterizations indicate that the electrochemical sensor has the highest sensitivity of 438.4 μA/(μM ⋅ cm2) among all carbon materials‐based DA sensors while well meeting the clinically required detection range and selectivity. The DA sensor was further used to detect live healthy human serum and live PC12 cells with satisfactory results, thus holding great promise for an inexpensive but sensitive DA sensor in practical applications of clinical diagnosis and biological research.

Publisher

Wiley

Subject

Electrochemistry,Analytical Chemistry

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3