Concurrent manipulation of competitive mechanisms to construct glutathione-stabilized gold nanocluster-based dual-channel molecular classifier for metal ions detection and information steganography.

Understanding charge transport in metal ion-mediated glutathione-stabilized gold nanoclusters (GSH-Au NCs) has proved difficult due to the presence of various competitive mechanisms, such as electron transfer (ET) and aggregation induction effect (AIE). In this paper, we present a dual-channel fluorescence (FL) and second-order Rayleigh scattering (SRS) sensing method for high-throughput classification of metal ions, relying on the competition between ET and AIE using GSH-Au NCs. The SRS signals show significant enhancement when Pb, Ag, Al, Cu, Fe, and Hg are present, as a result of the aggregation of GSH-Au NCs. Notably, the fluorescence signal exhibits the opposite trend. The FL intensities of GSH-Au NCs are enhanced by Pb, Ag, and Al through the AIE mechanism, while they are quenched by Cu, Fe, and Hg, which is dominated by the ET mechanism. By employing principal component analysis and hierarchical cluster analysis, these signals are transformed into unique fingerprints and Euclidean distances, respectively, enabling successful distinction of six metal ions and their mixtures with a low detection limit of 30 nM. This new strategy has successfully addressed interference from impurities in the testing of real water samples, demonstrating its strong ability to detect multiple metal ions. Impressively, we have achieved molecular cryptosteganography, which involves encoding, storing, and concealing information by transforming the selective response of GSH-Au NCs to binary strings. This research is anticipated to advance utilization of nanomaterials in logic sensing and information safety, bridging the gap between molecular sensors and information systems.