Experimental study demonstrates rapid opioid classification using carbon nanotube field-effect transistor arrays and deep learning, indicating a scalable approach for drug screening.
Opioid Sensing Public concern about opioid abuse is growing rapidly. In Research Article e74244, Alexander Star and co-workers constructed a carbon nanotube field-effect transistor sensor array for the rapid screening of opioids using machine learning methods. The deep learning model achieved good accuracy in classifying fentanyl, codeine, hydrocodone, and morphine, and revealed unexpected molecular sensing mechanisms underlying the discrimination of opioid compounds.
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Liu et al. (2026) studied this question.
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