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A Machine Learning-based Approach to Model Highly-thermally Robust Metasurface Absorber

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Abstract

For accelerating design procedure of compact and efficient on-chip nano-photonics and to aid computationally expensive, time-exhaustive state-of-the-art iterative simulation schemes, regression-based machine-learning models are demonstrated that predict the optical response and structural parameters of the meta-atoms.

© 2022 IEEE

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