Lysergic acid diethylamide (LSD) and two phenethylamine classes (NBOHs and NBOMes) are the main illicit drugs found in seized blotter papers. The preliminary identification of these substances is of great interest for forensic analysis. In this context, this work constitutes the inaugural demonstration of an efficient methodology for the selective detection of LSD, NBOHs, and NBOMes, utilizing a fully 3D-printed electrochemical double cell (3D-EDC). This novel 3D-EDC enables the use of two working electrodes and/or two supporting electrolytes (at different pHs) in the same detection system, with the possibility of shared or individual auxiliary and pseudo-reference electrodes. Thus, the selective voltammetric detection of these substances is proposed using two elegant strategies: (i) utilizing the same 3D-EDC platform with two working electrodes (boron-doped diamond (BDD) and 3D-printed graphite), and (ii) employing two pH levels (4.0 and 12.0) with 3D-printed graphite electrode. This comprehensive framework facilitates a fast, robust, and uncomplicated electrochemical analysis. Moreover, this configuration enables a rapid and sensitive detection of LSD, NBOHs, and NBOMes in seized samples, and can also provide quantitative analysis. The proposed method showed good stability of the electrochemical response with RSD <9 % for Ip and <5 % for Ep, evaluating all oxidation processes observed for studied analytes (n = 7) at two pH levels, using the same and different (n = 3) working electrodes. It demonstrates a broad linear range (20–100 and 20–70 μmol L−1) and a low LOD (1.0 μmol L−1) for quantification of a model molecule (LSD) at the two pHs studied. Hence, the 3D-EDC combined with voltammetric techniques using BDD and 3D-printed graphite electrodes on the same platform, or only with this last sensor at two pH values, provide a practical and robust avenue for preliminary identification of NBOHs, NBOMes, and LSD. This method embodies ease, swiftness, cost-efficiency, robustness, and selectivity as an on-site screening tool for forensic analysis.
Read full abstract