Metasurface-integrated optofluidic sensing enabled by artificial vision intelligence for identifying liquid chemicals
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Li, Hongliang
Kim, Jin Tae
Kim, Jin-Soo
Choi, Duk
Lee, Sang-Shin
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IEEE
Abstract
The currently used liquid identification techniques are costly, cumbersome, and spectrometer-reliant. In this study, a compact, accurate, and cost-effective method for identifying liquids was presented using visual intelligence algorithms and a metasurface-incorporated optofluidic device incorporated.
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Proceedings of the 2023 Conference on Lasers and ELectro-Optics Europe (CLEO Europe-EQEC)
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Restricted until
2099-12-31