Smart Portable Device Based on the Utilization of a 2D Disposable Paper Stochastic Sensor for Fast Ultrasensitive Screening of Food Samples for Bisphenols

计算机科学 工艺工程 嵌入式系统 工程类
作者
Raluca‐Ioana Stefan‐van Staden,Irina-Alina Chera-Anghel,Damaris‐Cristina Gheorghe,Jacobus Frederick van Staden,Marius Bădulescu
出处
期刊:Sensors [Multidisciplinary Digital Publishing Institute]
卷期号:23 (1): 314-314 被引量:4
标识
DOI:10.3390/s23010314
摘要

Since the determination of the high toxicity of bisphenol A, alternative structures for bisphenols have been synthesized, resulting in bisphenols C, E, F, S, and Z. These bisphenols have replaced bisphenol A in plastic bottles, toys, and cans used for preserving food. Later, the toxicity and negative effects of all of these bisphenols on people’s health were proven. Therefore, there is a need for a fast ultrasensitive screening method that is able to detect the presence of these bisphenols in any condition directly from food samples. This paper presented a disposable device based on the utilization of a 2D disposable paper stochastic sensor for the fast ultrasensitive screening of food samples for bisphenols A, C, E, F, S, and Z. The 2D disposable sensor was obtained by the deposition of graphene and silver nanolayers on paper using cold plasma. Furthermore, the active side of the sensor was modified using 2,3,7,8,12,13,17,18-octaethyl-21H,23H Mn porphyrin. The limits of quantification of these bisphenols were 1 fmol L−1 for bisphenols C and E, 10 fmol L−1 for bisphenols A and F, 10 pmol L−1 for bisphenol S, and 1 pmol L−1 for bisphenol Z. The recoveries of these bisphenols in milk, canned fruits, vegetables, and fish were higher than 99.00% with RSD (%) values lower than 1.50%.
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
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
刚刚
科研小白完成签到,获得积分10
1秒前
张豪祥发布了新的文献求助10
1秒前
Mollyshimmer完成签到 ,获得积分10
2秒前
3秒前
青椒黑蒜发布了新的文献求助10
3秒前
烟花应助dengbing2000采纳,获得10
3秒前
4秒前
梦在远方完成签到 ,获得积分10
5秒前
谢太郎发布了新的文献求助10
5秒前
领导范儿应助何香稳采纳,获得10
5秒前
Mingda完成签到,获得积分10
6秒前
8秒前
追寻的怜容完成签到,获得积分10
9秒前
9秒前
12秒前
12秒前
12秒前
12秒前
13秒前
钉钉完成签到 ,获得积分10
13秒前
14秒前
15秒前
缓慢逍遥完成签到 ,获得积分10
15秒前
15秒前
15秒前
壮观又亦发布了新的文献求助10
16秒前
sirhai发布了新的文献求助10
17秒前
非法所得发布了新的文献求助10
18秒前
18秒前
Hero发布了新的文献求助10
19秒前
整齐的梦露完成签到 ,获得积分10
19秒前
何香稳发布了新的文献求助10
19秒前
20秒前
20秒前
Bo完成签到,获得积分10
21秒前
XuChaogang完成签到 ,获得积分10
23秒前
23秒前
23秒前
科研通AI6.3应助pokexuejiao采纳,获得10
24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
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Discerning Saints: Moralization of Intrinsic Motivation and Selective Prosociality at Work 500
Handbuch Trainingswissenschaft – Trainingslehre 500
Additive Manufacturing Design and Applications (ASM Handbook, Volume 24A) 500
Variations: A More Diverse Picture of Contemporary Art 400
Induction Heating and Heat Treatment (ASM Handbook, Volume 4C) 300
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7587328
求助须知:如何正确求助?哪些是违规求助? 9165768
关于积分的说明 19616489
捐赠科研通 7167781
什么是DOI,文献DOI怎么找? 3266875
关于科研通互助平台的介绍 2431813
邀请新用户注册赠送积分活动 2258705