Development and evaluation of two different electronic tongues aiming to the discrimination of cutting agents found in cocaine seized samples

The screening and impurity profiling of drugs, like cocaine, is essential information that provides chemical and/or physical characterization to assist police agencies in understanding the trafficking and identifying drug origin. This work proposes to show the development and applications of two different electronic tongues (e-tongues) on the profiling study of cocaine seized samples. The developed intelligent devices' primary objective is the simple, quick, and remote cocaine classification samples based on the individual cutting agents added. The paper-based colorimetric sensor was fabricated in the lab using chromatographic paper as a substrate, wax printing to produce spot zones of reactions, a smartphone as image detection, and an editing image software to extract the chemical information through RBG values. The voltammetric e-tongue applied a boron-dopped diamond electrode to extract the cutting agents' electrochemical information through the square wave voltammetry (SWV) technique. In any case, both described sensors were coupled to chemometric tools for data analysis to construct the discrimination model. According to the objective, the unsupervised pattern recognition technique, Principal Component Analysis (PCA), was applied to test the capability of the device on individually discriminating the most common cutting agents of cocaine.