Copper nanoclusters-based fluorescent sensor array to identify metal ions and dissolved organic matter

Area of Science:

• Environmental Chemistry
• Nanotechnology
• Analytical Chemistry

Background:

• Water pollution, particularly metal ions and dissolved organic matter (DOM), poses significant environmental and health risks.
• Effective water quality management requires simple, rapid, and sensitive detection methods for various pollutants.
• Existing detection methods can be complex, time-consuming, or lack the sensitivity needed for comprehensive environmental monitoring.

Purpose of the Study:

• To develop a novel fluorescent sensor array for the simultaneous detection of multiple metal ions and DOM.
• To utilize copper nanoclusters (CuNCs) as the core sensing material for enhanced sensitivity and selectivity.
• To establish a robust analytical framework for identifying and quantifying water pollutants in diverse environmental samples.

Main Methods:

• Synthesis of copper nanoclusters (CuNCs) using polyethyleneimine (PEI), histidine (His), and glutathione (GSH).
• Fabrication of a fluorescent sensor array based on the differential fluorescence responses of CuNCs to various analytes.
• Application of multivariate statistical analysis, including principal component analysis (PCA) and linear discriminant analysis (LDA), for data interpretation and pattern recognition.
• Validation of the sensor array's performance in buffer solutions, tap water, and natural water samples (riverine and seawater).

Main Results:

• The synthesized CuNCs demonstrated distinct binding affinities and fluorescence quenching/enhancement patterns with 12 different metal ions and DOM components.
• The sensor array successfully identified and classified the 12 metal ions with a limit of detection as low as 1.5 μM.
• Quantification of specific metal ions, such as Zn²⁺, was achieved at concentrations as low as 0.83 μM.
• The array exhibited excellent performance in real-world samples, accurately detecting metal ions in tap water and differentiating between various water bodies.

Conclusions:

• The developed CuNCs-based fluorescent sensor array provides a simple, rapid, and effective platform for the simultaneous detection of multiple metal ions and DOM.
• This technology holds significant promise for advancing environmental monitoring, enabling real-time water quality assessment and pollution control.
• The use of CuNCs combined with advanced data analysis offers a versatile approach for developing next-generation chemical sensors.