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13 March 2024 Machine learning assisted label-free detection of opioids using nanophotonic sensor
John X. J. Zhang
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Proceedings Volume PC12832, Optics and Biophotonics in Low-Resource Settings X; PC128320G (2024) https://doi.org/10.1117/12.3005588
Event: SPIE BiOS, 2024, San Francisco, California, United States
Abstract
The U.S. faced a record 110,000 drug overdose deaths in 2022, primarily due to opioids, underscoring the need for efficient detection. Current methods suffer from poor accuracy or high costs. We aim to address this with a portable, high-throughput nanophotonic sensor that uses Ag/Au nanoparticles decorated on ZnO nanoarray to detect multiple drugs, like opioids, cocaine, and methadone from biofluids such as urine or blood. Amplified signals from surface-enhanced Raman scattering (SERS) are interpreted by machine learning, allowing automated, multiplex drug detection without expert supervision. This breakthrough approach could significantly advance understanding and control of the drug overdose crisis.
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John X. J. Zhang "Machine learning assisted label-free detection of opioids using nanophotonic sensor", Proc. SPIE PC12832, Optics and Biophotonics in Low-Resource Settings X, PC128320G (13 March 2024); https://doi.org/10.1117/12.3005588
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KEYWORDS
Sensors
Machine learning
Nanophotonics
Gold
Gold nanoparticles
Silver
Silica
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