已入深夜,您辛苦了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!祝你早点完成任务,早点休息,好梦!

Covalent organic frameworks (COFs)-based sensors: advances in environmental monitoring, food safety and biomedicine detection

生物医学 纳米技术 食品安全 环境化学 环境科学 化学 材料科学 生物信息学 生物 食品科学
作者
Rui Liu,Meng Han,Xin Zhang,Yuan Sun,Rijia Liu,Shuang Jin
出处
期刊:Microchemical Journal [Elsevier BV]
卷期号:215: 114529-114529 被引量:6
标识
DOI:10.1016/j.microc.2025.114529
摘要

Covalent organic frameworks (COFs) represent a groundbreaking class of porous crystalline materials that have attracted considerable attention in sensing applications due to their unique structural advantages. This review systematically examines the recent advances in COFs sensors across three critical domains. Specially, for environmental monitoring, their deployment in the detection of the heavy metal ions and organic pollutants , in the food safety applications were discussed. COFs sensors for the identification of the pesticide residues and microbial contaminants through the distinctive fluorescence quenching and colorimetric mechanisms were also analyzed. The biomedical section highlighted the importance of the COFs platforms for ultrasensitive detection of disease biomarkers via the innovative signal amplification strategies. Beyond the demonstrated superior analytical performance, these COFs sensors offer the transformative practical advantages including the field-deployable operation, the recyclability , and the integration with other devices. The development of COFs sensing technologies can not only provide the immediate solutions for pressing the detection challenges but also establish a new paradigm for designing the next-generation smart sensors with the enhanced selectivity, stability and multifunctionality . • The review highlights the applications in environmental, food safety and biomedical detection. • The review reveals functional modification strategies to enhance sensing capabilities. • The article comprehensively analyzes present challenges and outlines future research.
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
1秒前
许飞完成签到 ,获得积分10
1秒前
carryxu发布了新的文献求助30
1秒前
斯文败类应助nine采纳,获得10
2秒前
2秒前
3秒前
余铸海完成签到,获得积分10
4秒前
酷波er应助hhh采纳,获得10
4秒前
5秒前
6秒前
12发布了新的文献求助10
6秒前
6秒前
7秒前
快乐碱基对完成签到 ,获得积分10
9秒前
叉叉仔啊发布了新的文献求助10
10秒前
lulu发布了新的文献求助10
10秒前
khh完成签到 ,获得积分10
11秒前
liny发布了新的文献求助10
11秒前
Charlie完成签到,获得积分10
12秒前
12秒前
六一完成签到,获得积分10
13秒前
13秒前
小微发布了新的文献求助10
14秒前
14秒前
16秒前
Zr发布了新的文献求助20
19秒前
Orange应助高兴的故事采纳,获得10
21秒前
风趣的凌珍完成签到,获得积分10
22秒前
奇思妙想完成签到,获得积分10
22秒前
23秒前
ststxq完成签到,获得积分10
23秒前
24秒前
lulu完成签到,获得积分10
24秒前
24秒前
24秒前
evilcrisp发布了新的文献求助10
24秒前
zn完成签到 ,获得积分10
25秒前
李爱国应助Alxe采纳,获得10
25秒前
26秒前
无花果应助huang178485采纳,获得10
30秒前
高分求助中
Principles of Economics, 11th Edition 10000
University Physics with Modern Physics, 16th edition 10000
(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
Environmental Leverage in Times of Climate Crisis: Product Standards, Carbon Border Measures and Preferential Trade Agreements 1000
Matrix Methods in Data Mining and Pattern Recognition 510
Social Skills Improvement System-Rating Scales--Chinese Version 500
Dynamische Polarisation von H-1 und B-11 in (CH-3)-3NBH-3 500
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 7222915
求助须知:如何正确求助?哪些是违规求助? 8851927
关于积分的说明 18678485
捐赠科研通 6881718
什么是DOI,文献DOI怎么找? 3187594
关于科研通互助平台的介绍 2352407
邀请新用户注册赠送积分活动 2161915