Deep learning assisted inverse design of metamaterial microwave absorber

To accelerate the design of metamaterial microwave absorbers (MMAs), in this work, we developed a deep neural network model to predict the spectrum based on the known structural parameters at the beginning. Then, a tandem network was constructed, which can predict the geometries of an unknown MMA ba...

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Veröffentlicht in:	Applied physics letters 2023-10, Vol.123 (18)
Hauptverfasser:	Xie, Chen, Li, Haonan, Cui, Chenyang, Lei, Haodong, Sun, Yingjie, Zhang, Chi, Zhang, Yaqiang, Dong, Hongxing, Zhang, Long
Format:	Artikel
Sprache:	eng
Schlagworte:	Absorbers (materials) Absorption Applied physics Artificial neural networks Inverse design Machine learning Metamaterials Microwave absorbers
Online-Zugang:	Volltext
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