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

Sumbel Ijaz, Sadia Noureen, Bacha Rehman, Muhammad Zubair, Muhammad Qasim Mehmood, Yehia Massoud

Research output: Chapter in Book/Report/Published conference proceedingConference contributionpeer-review

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.
Original languageEnglish
Title of host publicationProceedings of the 2022 Conference on Lasers and Electro-Optics Pacific Rim
PublisherOptica Publishing Group
Publication statusPublished - 2022

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