化学
检出限
亚甲蓝
光热治疗
电化学
复合数
吸附
纳米技术
化学工程
色谱法
有机化学
催化作用
复合材料
物理化学
电极
工程类
光催化
材料科学
作者
Shao‐Hua Wen,Hengyuan Zhang,Sha Yu,Junping Ma,Jun‐Jie Zhu,Yuanzhen Zhou
出处
期刊:Analytical Chemistry
[American Chemical Society]
日期:2023-09-28
卷期号:95 (40): 14914-14924
被引量:16
标识
DOI:10.1021/acs.analchem.3c02171
摘要
Credible and on-site detection of organophosphorus pesticides (OPs) in complex matrixes is significant for food security and environmental monitoring. Herein, a novel COF/methylene blue@MnO2 (COF/MB@MnO2) composite featured abundant signal loading, a specific recognition unit, and robust oxidase-like activity was successfully prepared through facile assembly processes. The multifunctional composite acted as a homogeneous electrochemical and photothermal dual-mode sensing platform for OPs detection through stimuli-responsive regulation. Without the presence of OPs, the surface MnO2 coating could recognize thiocholine (TCh), originating from acetylcholinesterase (AChE)-catalyzed hydrolysis of acetylthiocholine (ATCh), and exhibited a distinctly amplified diffusion current due to the release of plentiful MB; while the residual MnO2 nanosheets could only catalyze less TMB into oxidized TMB (oxTMB) with a typical near-infrared (NIR) absorption, enabling NIR-driven photothermal assay with a low temperature using a portable thermometer. Based on the inhibitory effect of OPs on AChE activity and OP-regulated generation of TCh, chlorpyrifos as a model target can be accurately detected with a low limit of detection of 0.0632 and 0.108 ng/mL by complementary electrochemical and photothermal measurements, respectively. The present dual-mode sensor was demonstrated to be excellent for application to the reliable detection of OPs in complex environmental and food samples. This work can not only provide a complementary dual-mode method for convenient and on-site detection of OPs in different scenarios but also expand the application scope of the COF-based multifunctional composite in multimodal sensors.
科研通智能强力驱动
Strongly Powered by AbleSci AI