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Performance Benchmarking of Machine Learning Models for Terahertz Metamaterial Absorber Prediction
Nafisa Anjum, Robiul Hasan
https://arxiv.org/abs/2508.08611 https://

Performance Benchmarking of Machine Learning Models for Terahertz Metamaterial Absorber Prediction
This study presents a polarization-insensitive ultra-broadband terahertz metamaterial absorber based on vanadium dioxide (VO2) and evaluates machine learning methods for predicting its absorption performance. The structure consists of a VO2 metasurface, a MF2 dielectric spacer, and a gold ground plane. It achieves more than 90% absorption between 5.72 and 11.11 THz, covering a 5.38 THz bandwidth with an average absorptance of 98.15%. A dataset of 9,018 samples was generated from full-wave simul…

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