A sensitive ZIF-67/ MWCNTs composite-based sensor for the detection of sunset yellow in food and beverages

化学 电化学 检出限 分析物 碳纳米管 电化学气体传感器 电极 复合数 氧化还原 纳米技术 化学工程 无机化学 色谱法 物理化学 材料科学 复合材料 工程类
作者
Gloria Ebube Uwaya,Krishna Bisetty
出处
期刊:Journal of Electroanalytical Chemistry [Elsevier BV]
卷期号:951: 117899-117899 被引量:1
标识
DOI:10.1016/j.jelechem.2023.117899
摘要

This study introduces an innovative sensing platform designed for the detection of sunset yellow (SY). The platform employs a composite electrode material comprising of a zeolitic imidazole framework (ZIF-67) and multiwalled carbon nanotubes (MWCNTs) on a glassy carbon electrode (GCE). The synergy between ZIF-67 and MWCNTs leads to an enhancement in the electrochemical sensing behaviour for SY oxidation. Notably, the electrostatic interaction between ZIF-67 particles and MWCNTs results in a 6.26-fold increase in the current response. Additionally, the charge transfer resistance (Rct) was remarkably low, measuring at only 114 Ω. Under ideal conditions, the SY sensor demonstrated a minimum detectable concentration (LOD) and quantifiable concentration (LOQ) of 0.103 and 0.343 µM, respectively. The detection of SY was effectively conducted in snacks and beverages, showcasing its practical applicability. The results obtained demonstrate exceptional mean relative standard deviations (RSDs) < 1%, indicating high precision. Additionally, the recovery ranges achieved, ranging from 95% to 105%, validate the sensor’s reliability and accuracy. Furthermore, the chemical reactivity of SY was investigated through density functional theory (DFT) calculations, which identifies the redox-reactive site in SY, aligning with the postulated reaction mechanism observed in cyclic voltammograms. Monte Carlo (MC) simulations provide insight into the electrostatic and covalent interactions between the functional groups of the analyte and the designed sensor. This novel sensing approach demonstrates significant promise in the identification and surveillance of artificial food colourants in the food manufacturing sector.
最长约 10秒,即可获得该文献文件

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
YGYANG发布了新的文献求助10
1秒前
3秒前
翠花发布了新的文献求助10
3秒前
王359发布了新的文献求助10
3秒前
bias完成签到,获得积分10
3秒前
秀丽的依云完成签到 ,获得积分10
3秒前
深味i完成签到,获得积分10
4秒前
华仔应助科研通管家采纳,获得10
6秒前
李健应助科研通管家采纳,获得10
6秒前
丘比特应助科研通管家采纳,获得10
6秒前
无花果应助科研通管家采纳,获得10
6秒前
科研通AI2S应助科研通管家采纳,获得10
6秒前
Hello应助科研通管家采纳,获得10
6秒前
斯文败类应助科研通管家采纳,获得10
6秒前
大模型应助科研通管家采纳,获得10
6秒前
NexusExplorer应助科研通管家采纳,获得10
6秒前
TJC发布了新的文献求助10
7秒前
ZHX完成签到 ,获得积分10
7秒前
ymf完成签到 ,获得积分10
8秒前
9秒前
华新完成签到,获得积分10
10秒前
pluto应助le000000采纳,获得10
10秒前
11秒前
ymf关注了科研通微信公众号
12秒前
12秒前
13秒前
c1302128340完成签到,获得积分10
15秒前
池鱼完成签到,获得积分10
16秒前
hahahalha完成签到,获得积分10
16秒前
XIAODI发布了新的文献求助10
16秒前
荔枝发布了新的文献求助10
16秒前
lvlv发布了新的文献求助10
18秒前
19秒前
打打应助wweiyyulling采纳,获得30
20秒前
20秒前
胡捷完成签到,获得积分10
21秒前
21秒前
qqshown发布了新的文献求助10
22秒前
25秒前
高分求助中
A new approach to the extrapolation of accelerated life test data 1000
Cognitive Neuroscience: The Biology of the Mind 1000
Technical Brochure TB 814: LPIT applications in HV gas insulated switchgear 1000
Immigrant Incorporation in East Asian Democracies 600
Nucleophilic substitution in azasydnone-modified dinitroanisoles 500
不知道标题是什么 500
A Preliminary Study on Correlation Between Independent Components of Facial Thermal Images and Subjective Assessment of Chronic Stress 500
热门求助领域 (近24小时)
化学 材料科学 医学 生物 工程类 有机化学 生物化学 物理 内科学 纳米技术 计算机科学 化学工程 复合材料 遗传学 基因 物理化学 催化作用 冶金 细胞生物学 免疫学
热门帖子
关注 科研通微信公众号,转发送积分 3967175
求助须知:如何正确求助?哪些是违规求助? 3512515
关于积分的说明 11163672
捐赠科研通 3247423
什么是DOI,文献DOI怎么找? 1793810
邀请新用户注册赠送积分活动 874616
科研通“疑难数据库(出版商)”最低求助积分说明 804488