Analytica chimica acta · 2025
Sensor array based on Cu-based metal-organic frameworks nanozymes for rapid identification of phenolic pollutants.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Mao Guanghua, Liu Xufei, Zhang Yahan, Deng Chunmeng, Wei Dali
Аннотация
BACKGROUND: Phenol and its derivatives pose a threat to aquatic organisms and human health even at low concentrations in environments, and their biotoxicity was related to their substituent groups and substitution positions, whereas the rapid identification of various phenolic contaminants is difficult with current methods.
RESULTS: Herein, a nanozyme sensor array based on copper-based metal-organic frameworks (Cu-MOFs) was designed for the effective identification of five phenolic contaminants (phenol, 2,4-dichlorophenol, 3-chlorophenol, o-chlorophenol, and p-chlorophenol). Wherein, three Cu-MOFs nanozymes (Cu@BDC-NH2, Cu@2-MI, and Cu@BTC) were prepared by using Cu2+ as metal centers and different ligands (BDC-NH2, 2-MI, and BTC), respectively, which all exhibited good laccase-like activity. More importantly, different ligands endowed three nanozymes based on Cu-MOFs with laccase-like activity to diverse recognition capability to phenolic compounds, thus a nanozyme sensor array was established for the differentiation of phenolic contaminants. To differentiate and categorize five phenolic contaminants and their mixtures, the colorimetric responses generated were analyzed using linear discriminant analysis (LDA) and hierarchical cluster analysis (HCA) methods. The developed sensor array also effectively identified phenolic contaminants in actual water samples, underscoring its potentials for environmental monitoring.
SIGNIFICANCE: Therefore, this study provided an emerging sensing strategy to identify phenolic pollutants, which opened a new avenue for the application of sensor array in pollutants detection.
RESULTS: Herein, a nanozyme sensor array based on copper-based metal-organic frameworks (Cu-MOFs) was designed for the effective identification of five phenolic contaminants (phenol, 2,4-dichlorophenol, 3-chlorophenol, o-chlorophenol, and p-chlorophenol). Wherein, three Cu-MOFs nanozymes (Cu@BDC-NH2, Cu@2-MI, and Cu@BTC) were prepared by using Cu2+ as metal centers and different ligands (BDC-NH2, 2-MI, and BTC), respectively, which all exhibited good laccase-like activity. More importantly, different ligands endowed three nanozymes based on Cu-MOFs with laccase-like activity to diverse recognition capability to phenolic compounds, thus a nanozyme sensor array was established for the differentiation of phenolic contaminants. To differentiate and categorize five phenolic contaminants and their mixtures, the colorimetric responses generated were analyzed using linear discriminant analysis (LDA) and hierarchical cluster analysis (HCA) methods. The developed sensor array also effectively identified phenolic contaminants in actual water samples, underscoring its potentials for environmental monitoring.
SIGNIFICANCE: Therefore, this study provided an emerging sensing strategy to identify phenolic pollutants, which opened a new avenue for the application of sensor array in pollutants detection.