Graphene-Fiber Microelectrodes for Ultrasensitive Neurochemical Detection

微电极 石墨烯 化学 神经化学 纳米技术 电极 电子转移 纤维 循环伏安法 生物传感器 电化学 材料科学 医学 有机化学 物理化学 内分泌学
作者
Yuxin Li,Romana Jarošová,Moriah E. Weese‐Myers,Ashley E. Ross
出处
期刊:Analytical Chemistry [American Chemical Society]
卷期号:94 (11): 4803-4812 被引量:16
标识
DOI:10.1021/acs.analchem.1c05637
摘要

Here, we have synthesized and characterized graphene-fiber microelectrodes (GFME's) for subsecond detection of neurochemicals with fast-scan cyclic voltammetry (FSCV) for the first time. GFME's exhibited extraordinary properties including faster electron transfer kinetics, significantly improved sensitivity, and ease of tunability that we anticipate will have major impacts on neurochemical detection for years to come. GF's have been used in the literature for various applications; however, scaling their size down to microelectrodes and implementing them as neurochemical microsensors is significantly less developed. The GF's developed in this paper were on average 20–30 μm in diameter and both graphene oxide (GO) and reduced graphene oxide (rGO) fibers were characterized with FSCV. Neat GF's were synthesized using a one-step dimension-confined hydrothermal strategy. FSCV detection has traditionally used carbon-fiber microelectrodes (CFME's) and more recently carbon nanotube fiber electrodes; however, uniform functionalization and direct control of the 3D surface structure of these materials remain limited. The expansion to GFME's will certainly open new avenues for fine-tuning the electrode surface for specific electrochemical detection. When comparing to traditional CFME's, our GFME's exhibited significant increases in electron transfer, redox cycling, fouling resistance, higher sensitivity, and frequency independent behavior which demonstrates their incredible utility as biological sensors.

科研通智能强力驱动
Strongly Powered by AbleSci AI
更新
PDF的下载单位、IP信息已删除 (2025-6-4)

科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
1秒前
12366666完成签到,获得积分10
1秒前
1秒前
2秒前
Dr_Zhan完成签到 ,获得积分10
3秒前
孙傲发布了新的文献求助10
3秒前
FU发布了新的文献求助10
5秒前
xucc完成签到,获得积分10
5秒前
6秒前
小皮发布了新的文献求助10
6秒前
6秒前
隐形曼青应助ZeSheng采纳,获得10
7秒前
gy完成签到,获得积分10
8秒前
不将就发布了新的文献求助10
9秒前
10秒前
11秒前
11秒前
铭仔发布了新的文献求助10
12秒前
gxc关闭了gxc文献求助
12秒前
跳羚完成签到,获得积分10
14秒前
donk完成签到,获得积分10
15秒前
任性的诗兰完成签到,获得积分10
16秒前
17秒前
梅子黄时雨完成签到,获得积分10
18秒前
mk91发布了新的文献求助10
18秒前
孙傲完成签到,获得积分10
18秒前
铭仔完成签到,获得积分10
18秒前
小线团黑桃完成签到,获得积分10
19秒前
19秒前
科研小白完成签到,获得积分10
20秒前
PEI完成签到,获得积分10
21秒前
萱棚发布了新的文献求助10
22秒前
YOMU完成签到,获得积分10
22秒前
龙腾万里完成签到,获得积分10
23秒前
24秒前
我是老大应助青年才俊采纳,获得10
24秒前
大胆初雪发布了新的文献求助10
25秒前
25秒前
梵低发布了新的文献求助30
27秒前
无花果应助魔幻的忆南采纳,获得10
27秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
人脑智能与人工智能 1000
King Tyrant 720
Silicon in Organic, Organometallic, and Polymer Chemistry 500
Principles of Plasma Discharges and Materials Processing, 3rd Edition 400
Pharmacology for Chemists: Drug Discovery in Context 400
El poder y la palabra: prensa y poder político en las dictaduras : el régimen de Franco ante la prensa y el periodismo 400
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5604106
求助须知:如何正确求助?哪些是违规求助? 4688956
关于积分的说明 14857141
捐赠科研通 4696700
什么是DOI,文献DOI怎么找? 2541175
邀请新用户注册赠送积分活动 1507328
关于科研通互助平台的介绍 1471851