期刊
CHEMICAL ENGINEERING JOURNAL
卷 431, 期 -, 页码 -出版社
ELSEVIER SCIENCE SA
DOI: 10.1016/j.cej.2021.134107
关键词
Chemosensor assay; Cross-responsive strategy; Metal ion detection; Water-quality monitoring; Biomimetic synthesis
资金
- Major Science and Technology Innovation Project of Shandong Province of China [2019JZZY020231, 2019JZZY020232]
- Sichuan Province Science and Technology Support Program [2020YFN0029]
- One Thousand-Talents Scheme in Sichuan Province, Scientific Start-up Research Fund of Chengdu University of Information Technology [KYTZ201714]
A colorimetric sensor array based on enzyme response analysis was developed for pattern recognition of various metal ions in water quality monitoring. The sensor array successfully identifies and distinguishes 11 species of metal ions using principal component analysis (PCA), and can also distinguish different concentrations of single model analyte and mixtures of contaminants in tap water.
Numerous detection strategies have been undertaken for quantitative analysis of single metal ion in the field of water-quality monitoring, whereas the complexity in the types and concentrations of potential contaminant leads us to should focus on groups of contaminants than to individual contaminants. To the best of our knowledge, there are few strategies to explore cross response-based semiselective sensor array in the area of water-quality monitoring. In this study, a colorimetric sensor array based on enzyme response analysis was innovatively developed for pattern recognition of various metal ions. Three types of metal phosphates-acetylcholinesterase nanoflowers (MP-AChE NFs) were prepared by using a green, facile, cost-efficient enzyme immobilization technology to construct the sensor array. With the help of a multivariate statistical analysis that can concentrate the most significant characteristics (variance) of the data into a lower dimensional space, principal component analysis (PCA) successfully identifies and distinguishes 11 species of metal ions, and gives unique fingerprint information for each analyte. Moreover, the sensor array can distinguish different concentrations of single model analyte, as well as a mixture of different contaminants in tap water.
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