SnSe/SnO2 Heterojunction-Based Single-Sensor Virtual Electronic Nose with Low Reaction Barrier for Trace Identification of Volatile Sulfur Compounds toward Illicit Methamphetamine Trafficking Traceability

Illicit methamphetamine (MA, ice) trafficking poses a severe global threat to public security, while non-contact on-site detection of MA remains a grand challenge due to its ultra-low saturated vapor pressure at room temperature (25 ° C). Volatile sulfur compounds (VSCs), including hydrogen sulfide (H 2 S), methanethiol (CH 3 SH), and dimethyl sulfide (C 2 H 6 S, DMS), are stable characteristic markers released throughout the entire MA production, purification, storage, and transportation chain. Herein, we develop a single-sensor virtual electronic nose based on SnSe/SnO 2 p-n heterojunction for precise VSC identification in illicit MA scenarios. The SnSe/SnO 2 heterojunction, synthesized via a facile liquid-phase ultrasonic method, exhibits significantly enhanced room-temperature H 2 S sensing adsorption kinetics, delivering a high response of 2.57 (response = R a / R g , where R a is the resistance in air and R g is the resistance in the atmosphere, including H 2 S and air) to 2.5 ppm H 2 S in air, a low detection limit of 75 ppb, excellent anti-sulfur poisoning ability, and long-term stability. Combined with density functional theory (DFT) calculations, we reveal that interfacial charge redistribution in SnSe/SnO 2 optimizes reactant adsorption energy, lowers the energy barrier of electronic modulation during H 2 S interactions to only 0.157 eV, and amplifies the adsorption–desorption kinetic differences between distinct VSCs. By extracting 12-dimensional static features from single-device response curves without any external modulation, we construct a PCA-KNN machine learning framework that achieves an overall identification accuracy of 79.65% for six VSC systems, with an ultra-high accuracy of 96.7% for target H 2 S even in complex mixtures. By circumventing the inter-sensor variance and complexities typical of multi-sensor arrays, this single-sensor virtual electronic nose provides a highly integrated, physically compact, and high-precision solution for on-site non-contact traceability of illicit MA trafficking.