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Artificial Intelligence-Enhanced Metasurfaces for Instantaneous Measurements of Dispersive Refractive Index.
Badloe, Trevon; Yang, Younghwan; Lee, Seokho; Jeon, Dongmin; Youn, Jaeseung; Kim, Dong Sung; Rho, Junsuk.
Afiliación
  • Badloe T; Graduate School of Artificial Intelligence, Pohang University of Science and Technology (POSTECH), Pohang, 37673, Republic of Korea.
  • Yang Y; Department of Electronics and Information Engineering, Korea University, Sejong, 30019, Republic of Korea.
  • Lee S; Department of Mechanical Engineering, Pohang University of Science and Technology (POSTECH), Pohang, 37673, Republic of Korea.
  • Jeon D; Department of Mechanical Engineering, Pohang University of Science and Technology (POSTECH), Pohang, 37673, Republic of Korea.
  • Youn J; Department of Mechanical Engineering, Pohang University of Science and Technology (POSTECH), Pohang, 37673, Republic of Korea.
  • Kim DS; Department of Mechanical Engineering, Pohang University of Science and Technology (POSTECH), Pohang, 37673, Republic of Korea.
  • Rho J; Department of Mechanical Engineering, Pohang University of Science and Technology (POSTECH), Pohang, 37673, Republic of Korea.
Adv Sci (Weinh) ; 11(39): e2403143, 2024 Oct.
Article en En | MEDLINE | ID: mdl-39225343
ABSTRACT
Measurements of the refractive index of liquids are in high demand in numerous fields such as agriculture, food and beverages, and medicine. However, conventional ellipsometric refractive index measurements are too expensive and labor-intensive for consumer devices, while Abbe refractometry is limited to the measurement at a single wavelength. Here, a new approach is proposed using machine learning to unlock the potential of colorimetric metasurfaces for the real-time measurement of the dispersive refractive index of liquids over the entire visible spectrum. The platform with a proof-of-concept experiment for measuring the concentration of glucose is further demonstrated, which holds a profound impact in non-invasive medical sensing. High-index-dielectric metasurfaces are designed and fabricated, while their experimentally measured reflectance and reflected colors, through microscopy and a standard smartphone, are used to train deep-learning models to provide measurements of the dispersive background refractive index with a resolution of ≈10-4, which is comparable to the known index as measured with ellipsometry. These results show the potential of enabling the unique optical properties of metasurfaces with machine learning to create a platform for the quick, simple, and high-resolution measurement of the dispersive refractive index of liquids, without the need for highly specialized experts and optical procedures.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Adv Sci (Weinh) Año: 2024 Tipo del documento: Article Pais de publicación: Alemania

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Idioma: En Revista: Adv Sci (Weinh) Año: 2024 Tipo del documento: Article Pais de publicación: Alemania