Discriminative and quantitative color-coding analysis of fluoroquinolones with dual-emitting lanthanide metal-organic frameworks

判别式 颜色编码 镧系元素 对偶(语法数字) 金属 金属有机骨架 材料科学 计算机科学 人工智能 化学 艺术 文学类 离子 吸附 有机化学
作者
Xingyi Wang,Qiuju Li,Boyang Zong,Xian Fang,Meng Liu,Zhuo Li,Shun Mao,Kostya Ostrikov
出处
期刊:Sensors and Actuators B-chemical [Elsevier BV]
卷期号:373: 132701-132701 被引量:58
标识
DOI:10.1016/j.snb.2022.132701
摘要

Color-coding analysis from chemicals of concern is in great demand, but faces low sensitivity and specificity, low resolution, and complex processing among the many challenges. Here, this work resolves these issues to enable the elusive quantitative detection of a variety of fluoroquinolone (FQ) antibiotics. A fluorescent sensor based on the dual-emitting lanthanide metal-organic frameworks combining Tb 3+ and Eu 3+ as the luminescent center and 1,3,5-benzenetricarboxylic acid as the ligand is constructed. Due to the different sensitization effects to lanthanide metals and different inherent fluorescence emissions of FQs, the sensor exhibits characteristic color variations towards nine FQ and enables the discriminative detection of multiple antibiotics with self-calibrated signals. For the first time, a polynomial surface fitting process is developed to correlate the coordinates of color-coding map and target concentration for quantitative analysis. Moreover, a smartphone-enabled sensing system is demonstrated for on-site imaging analysis of antibiotics. The demonstrated innovative antibiotic detection and color-coding-based signal processing approach will inform the development of cutting-edge analysis systems for public health and environmental monitoring. • Dual-emitting Ln-MOF fluorescent sensor designed for discriminative analysis of structurally similar antibiotics. • Highly sensitive and selective detection of fluoroquinolones antibiotics. • A polynomial surface fitting process is developed to correlate fluorescence color and antibiotic concentration. • Fluorescence color-coding analysis implemented portable device for multi-target detection.
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
香蕉觅云应助煜琪采纳,获得10
刚刚
刚刚
1秒前
1秒前
2秒前
3秒前
殷晓阳发布了新的文献求助10
3秒前
张张完成签到,获得积分10
3秒前
Owen应助白羽采纳,获得10
5秒前
6秒前
6秒前
6秒前
ooo完成签到,获得积分10
7秒前
大个应助乐观的店员采纳,获得10
7秒前
8秒前
8秒前
贲问安发布了新的文献求助20
9秒前
chengzi完成签到,获得积分10
10秒前
ljhwahaha发布了新的文献求助10
10秒前
10秒前
顾矜应助科研通管家采纳,获得10
11秒前
FashionBoy应助科研通管家采纳,获得10
11秒前
woshi123应助科研通管家采纳,获得10
11秒前
Lucas应助科研通管家采纳,获得10
11秒前
领导范儿应助科研通管家采纳,获得10
12秒前
王大丫发布了新的文献求助10
12秒前
Jasper应助科研通管家采纳,获得10
12秒前
汉堡包应助科研通管家采纳,获得10
12秒前
今后应助科研通管家采纳,获得10
12秒前
dde给典雅的山灵的求助进行了留言
12秒前
woshi123应助科研通管家采纳,获得10
12秒前
12秒前
搜集达人应助科研通管家采纳,获得10
13秒前
13秒前
CipherSage应助今夜无人入眠采纳,获得10
13秒前
天天快乐应助科研通管家采纳,获得10
13秒前
13秒前
13秒前
梓越完成签到 ,获得积分10
14秒前
14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
Römisch-Germanische Forschungen 1000
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
The fast track to determining transfer functions of linear circuits: The student guide 500
The Analytical and Numerical Solution of Electric and Magnetic Fields 500
Green Fire Retardants for Polymeric Materials 400
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 7617483
求助须知:如何正确求助?哪些是违规求助? 9192767
关于积分的说明 19701622
捐赠科研通 7189946
什么是DOI,文献DOI怎么找? 3272020
关于科研通互助平台的介绍 2434795
邀请新用户注册赠送积分活动 2267143