Pattern-based discrimination and visualization of metal ions through RGB coding of multicolor-emitting carbon dots

Abstract

Herein, the single para-Phenylenediamine (PPD) source was used to synthesis three orange-, green-, and blue-emitting carbon dots (CDs) under different synthesis conditions. Due to the diverse fluorescence response of the synthesized CDs to heavy metal ions such as Au3+, Ag+, Cu2+, Fe3+, Hg2+, Cd2+, and Pb2+, a three-channel sensor array system for pattern-based discrimination and visualization of these metal ions was developed. The recorded fluorescence data was successfully classified into separate clusters without any overlapping through typical statistical methods such as principal component analysis (PCA) and hierarchical clustering analysis (HCA). We also introduced a new method of discrimination and determination by coding the fluorescence intensities of the three CDs into integer values from 0 to 255 and converting these values into a secondary color using the RGB additive mixing method to provide a single, unique, and visual fingerprint-like color for each metal ion. The colors obtained not only identified the selected metal ions and their binary and ternary mixed samples, but also provided a concentration-dependent trend of each specific color for metal ion quantification. Furthermore, the practicability of the constructed sensor array and the proposed RGB coding method was validated by the successful identification and quantification of unknown metal ions in real water samples.