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  • Title: Strong π-Metal Interaction Enables Liquid Interfacial Nanoarray-Molecule Co-assembly for Raman Sensing of Ultratrace Fentanyl Doped in Heroin, Ketamine, Morphine, and Real Urine.
    Author: Ding Z, Wang C, Song X, Li N, Zheng X, Wang C, Su M, Liu H.
    Journal: ACS Appl Mater Interfaces; 2023 Mar 08; 15(9):12570-12579. PubMed ID: 36808908.
    Abstract:
    Toward the challenge on reliable determination of trace fentanyl to avoid opioid overdose death in drug crisis, here we realize rapid and direct detection of trace fentanyl in real human urine without pretreatment by a portable surface enhanced Raman spectroscopy (SERS) strategy on liquid/liquid interfacial (LLI) plasmonic arrays. It was observed that fentanyl could interact with the gold nanoparticles (GNPs) surface, facilitate the LLI self-assembly, and consequently amplify the detection sensitivity with a limit of detection (LOD) as low as 1 ng/mL in aqueous solution and 50 ng/mL spiked in urine. Furthermore, we achieve multiplex blind sample recognition and classification of ultratrace fentanyl doped in other illegal drugs, which has extremely low LODs at mass concentrations of 0.02% (2 ng in 10 μg of heroin), 0.02% (2 ng in 10 μg of ketamine), and 0.1% (10 ng in 10 μg of morphine). A logic circuit of the AND gate was constructed for automatic recognition of illegal drugs with or without fentanyl doping. The data-driven analog soft independent modeling model could quickly distinguish fentanyl-doped samples from illegal drugs with 100% specificity. Molecular dynamics (MD) simulation elucidates the underlying molecular mechanism of nanoarray-molecule co-assembly through strong π-metal interactions and the differences in the SERS signal of various drug molecules. It paves a rapid identification, quantification, and classification strategy for trace fentanyl analysis, indicating broad application prospects in response to the opioid epidemic crisis.
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