危险废物
污染物
纳米孔
有害空气污染物
环境科学
电化学
环境化学
纳米技术
材料科学
化学
废物管理
工程类
电极
物理化学
有机化学
作者
Wenhao Ma,Wanyi Xie,Shaoxi Fang,Shixuan He,Bohua Yin,Yongjia Wang,Changjun Hou,Danqun Huo,Deqiang Wang
标识
DOI:10.1016/j.electacta.2023.143678
摘要
Nanopore electrochemical sensors have been developed to detect various emerging pollutants at the single-molecule level with high sensitivity and specificity due to their high resolution in past three decades, which is of great significance for emerging hazardous pollutants control. Electrochemical detection methods based on nanopore technology are primarily divided into two categories: resistive-pulse and rectification sensing. The main detection mechanism of the resistive-pulse method is based on the volume exclusion effect generated when the analyte enters through the nanopore, and it involves three primary detection strategies. The first approach involves nanopore technology for direct pollutant detection, where pollutant structure and concentration information is assessed based on nanopore-generated ionic current's blockade strength, duration, and frequency. The second strategy relies on weak intermolecular interactions when direct detection of pollutants is challenging. Molecular probes interact with target molecules to enhance detection sensitivity and achieve specific recognition. The third strategy is based on the biological/chemical reaction of pollutant molecules, through indirect detection method to achieve specific detection of target pollutant molecules. Additionally, relies on changes in surface charge polarity or nanopore spatial structure induced by the analyte molecules to achieve the detection of target molecules within the nanopore. This work demonstrates the research progress achieved in the application of nanopore electrochemical sensing technology to high-sensitivity detection of hazardous pollutants, utilizing the unique confined spatial characteristics of nanopores, combined with biorecognition techniques and principles of electrochemical reactions.
科研通智能强力驱动
Strongly Powered by AbleSci AI