Visual Sensor Array for Multiple Aromatic Amines via Specific Ascorbic Acid Oxidase Mimic Triggered Schiff-Base...

Area of Science:

• Nanomaterials Science
• Environmental Chemistry
• Analytical Chemistry

Background:

• Redox nanozymes show promise for environmental pollutant detection.
• Aromatic amines are significant environmental pollutants, yet their detection using nanozymes remains underdeveloped.
• Existing methods for aromatic amine detection often lack sensitivity or specificity.

Purpose of the Study:

• To synthesize novel copper-based nanozymes capable of detecting aromatic amines.
• To develop a visual sensor array for the sensitive and selective identification of various aromatic amines and their mixtures.
• To validate the sensor's performance in real-world environmental water samples.

Main Methods:

• Synthesis of copper-tryptophan (Cu-Trp) nanozymes as ascorbic acid oxidase mimics.
• Catalysis of ascorbic acid (AA) oxidation to dehydroascorbic acid (DHAA).
• Reaction of DHAA with aromatic amines and their derivatives to produce fluorescent Schiff bases.
• Construction of a visual sensor array utilizing two sensing channels (Cu-Trp + AA and Cu-Arg + AA) and RGB color analysis.
• Discrimination of single analytes, mixtures, and unknown samples, followed by validation in environmental water.

Main Results:

• Cu-Trp nanozymes effectively catalyzed ascorbic acid oxidation.
• A visual sensor array successfully distinguished six aromatic amines (OPD, NDA, 4-NO2-OPD, 4-F-OPD, 4-Cl-OPD, 4-Br-OPD) down to 10 μM.
• The sensor array demonstrated high accuracy in identifying complex mixtures, unknown samples, and quantifying single aromatic amines.
• Effective validation of the sensor's discriminating ability in environmental water samples.

Conclusions:

• Novel copper-based nanozymes, utilizing amino acids as linkers, can be designed as effective enzyme mimics for pollutant detection.
• The developed visual sensor array provides a sensitive, selective, and visual method for detecting multiple aromatic amines.
• This approach offers a promising tool for large-scale environmental monitoring of aromatic amine contamination.