Paper‐Based Optical Nose Using Green‐Synthesized Carbon Quantum Dots: Selective Detection of Heavy Metal Ions

Carbon quantum dots (CQDs) are widely used nanomaterials due to their low cost, photostability, and tunable surface chemistry. However, their inherently cross‐reactive nature often limits their applicability in real‐world sensing scenarios. In this study, we turn this limitation into an advantage by employing a cross‐reactive sensor array strategy. By doping CQDs with different heteroatoms, their interactions with target analytes can be modulated to produce distinct photoluminescence (PL) response patterns (fingerprints). Within a green‐chemistry framework, undoped and nitrogen‐, sulfur‐, and boron‐doped CQDs (N‐CQDs, S‐CQDs, and B‐CQDs) were synthesized via a microwave‐assisted method using pomegranate molasses as a renewable carbon source. These sensing elements were integrated into an optical nose platform for the detection of heavy metal ions. Rather than pursuing single‐ion specificity, the system relies on PL fingerprinting, and the resulting multidimensional data were analyzed using chemometric models: Linear Discriminant Analysis (LDA) for qualitative discrimination and Support Vector Machines (SVM) for quantitative prediction. To improve portability and cost‐efficiency, the sensor array was further implemented on a paper‐based platform. The environmental‐friendliness performance of the developed method was evaluated using the Analytical GREEnness (AGREE) metric, which confirmed a favorable green‐chemistry profile.