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

In recent years, the prevention and control of water pollution has received extensive attention. There is a need to develop simple and effective strategies for the rapid detection of metal ions and dissolved organic matter (DOM) in order to improve water quality. To this end, the first copper nanoclusters (CuNCs)-based fluorescent sensor array was done to identify 12 metal ions (Pb2+, Fe3+, Cu2+, Cd2+, Cr3+, Co2+, Ni2+, Zn2+, Ag+, Fe2+, Hg2+, and Al3+) and DOM (humic substances, lipids, fatty acids, amino acids, and lignans). The results revealed that CuNCs that were synthesized with polyethyleneimine (PEI), histidine (His), and glutathione (GSH) exhibited different binding abilities to metal ions and DOM. These unique fluorescence responses were analyzed using principal component analysis (PCA) and linear discriminant analysis (LDA) to identify metal ions and DOM in the buffer. The aforementioned 12 metal ions were classified at a limit concentration of 1.5 mu M. Moreover, quantification of metal ions was achieved even at a low concentration of 0.83 mu M (Zn2+). This array also worked well in the recognition of metal ions in tap water as well as distinguishing riverine and seawater samples of different regions, which was of great significance in environmental monitoring.

Automated summary

In recent years, the prevention and control of water pollution has received extensive attention. This study developed a fluorescent sensor array based on copper nanoclusters for the identification of metal ions and dissolved organic matter (DOM), with successful results in both classification and quantification.