Tunable Fano Resonances in Thin-Film Metamaterials

We study three different material platforms to modulate the response of Fano-resonant optical coatings (FROCs): Sb<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf>Se<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</inf>, VO<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf>, and Indium-Tin Oxide (ITO), whose optical properties can be tuned via phase transitions or charge doping. We develop a theoretical framework to estimate the Fano parameter and, thus, directly design Fano-resonant thin-film stacks with engineered optical response, i.e. to match targeted wavelengths, display transitions between Fano and Fabry-Perot-type responses, among other responses. In addition to theory, we develop a machine-learning-based inverse design method to find optimal stacks.

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Published
2025-08-13
DOI
https://doi.org/10.1109/rapid64712.2025.11151433
Primary Topic
Metamaterials and Metasurfaces Applications
Type
article
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Tunable Fano Resonances in Thin-Film Metamaterials

Jimmy H. Ni, Sheng‐Wei Wang, Yi‐Siou Huang, Chih‐Yu Lee et al.
Metamaterials and Metasurfaces Applications
article

Tunable Fano Resonances in Thin-Film Metamaterials

Jimmy H. Ni, Sheng‐Wei Wang, Yi‐Siou Huang, Chih‐Yu Lee, Carlos Rı́os
article en

Abstract

We study three different material platforms to modulate the response of Fano-resonant optical coatings (FROCs): Sb<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf>Se<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">3</inf>, VO<inf xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</inf>, and Indium-Tin Oxide (ITO), whose optical properties can be tuned via phase transitions or charge doping. We develop a theoretical framework to estimate the Fano parameter and, thus, directly design Fano-resonant thin-film stacks with engineered optical response, i.e. to match targeted wavelengths, display transitions between Fano and Fabry-Perot-type responses, among other responses. In addition to theory, we develop a machine-learning-based inverse design method to find optimal stacks.

DEVCOM Army Research Laboratory (US), United States Army Combat Capabilities Development Command (US), University of Maryland, College Park (US)
Openalex Percentile: Top 84%
Metamaterials and Metasurfaces Applications
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