Design of Pixelated Wideband Metasurface Absorber Using Transfer Learning and Generative Adversarial Networks Article Swipe
Yun He
,
Zhiming Zhang
,
Ke Fang
,
Xun Ye
,
Mingyu Li
,
Yulu Zhang
·
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/app15179642
YOU?
·
· 2025
· Open Access
·
· DOI: https://doi.org/10.3390/app15179642
In this paper, a wideband metasurface absorber is proposed by utilizing transfer learning and a conditional deep convolutional generative adversarial network (CDCGAN). This approach involves introducing a forward prediction neural network to predict the spectral curve of a metasurface absorber, as well as a generative adversarial network for the inverse design of a metasurface absorber. After comparing different pre-trained models, a transfer learning network (TLN) based on GoogleNet-InceptionV3 is incorporated into the design process to reduce the amount of training data required. Based on the pixelated metasurface with a common effect of metallic pixels and resistive film pixels, a broadband electromagnetic absorber was designed through the CDCGAN model. For the application target of the C-band, a pixelated broadband metasurface Absorber I has been designed, which can achieve an absorption effect of less than −8 dB in the range of 6.5–8 GHz, and the absorption performance reaches less than −15 dB near the resonant frequency point of 7 GHz. Further lightweight optimization design was carried out, and the metasurface Absorber II was designed for application in the X-band, which has an absorption bandwidth below −8 dB at 9–12 GHz. The reflectivity curve measured by the experiment is in good agreement with that of the simulation result. Of note, our methodology aims to reversely engineer suitable absorbing structures based on customer-defined spectrums, which may bear some significance to the rapid design of broadband metasurface absorbers.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.3390/app15179642
- https://www.mdpi.com/2076-3417/15/17/9642/pdf?version=1756800604
- OA Status
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- References
- 39
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- OpenAlex ID
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https://openalex.org/W4413940982Canonical identifier for this work in OpenAlex
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https://doi.org/10.3390/app15179642Digital Object Identifier
- Title
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Design of Pixelated Wideband Metasurface Absorber Using Transfer Learning and Generative Adversarial NetworksWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2025Year of publication
- Publication date
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2025-09-02Full publication date if available
- Authors
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Yun He, Zhiming Zhang, Ke Fang, Xun Ye, Mingyu Li, Yulu ZhangList of authors in order
- Landing page
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https://doi.org/10.3390/app15179642Publisher landing page
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https://www.mdpi.com/2076-3417/15/17/9642/pdf?version=1756800604Direct link to full text PDF
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YesWhether a free full text is available
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goldOpen access status per OpenAlex
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https://www.mdpi.com/2076-3417/15/17/9642/pdf?version=1756800604Direct OA link when available
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Wideband, Adversarial system, Computer science, Generative grammar, Materials science, Optics, Artificial intelligence, PhysicsTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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| referenced_works | https://openalex.org/W2077151136, https://openalex.org/W2319819490, https://openalex.org/W3010110523, https://openalex.org/W2027029957, https://openalex.org/W2790915754, https://openalex.org/W3037924704, https://openalex.org/W2121607567, https://openalex.org/W2335776074, https://openalex.org/W2137938289, https://openalex.org/W2070161878, https://openalex.org/W2168912599, https://openalex.org/W2027409326, https://openalex.org/W4401246712, https://openalex.org/W3088126065, https://openalex.org/W3014951743, https://openalex.org/W2040234138, https://openalex.org/W2912787970, https://openalex.org/W4385575001, https://openalex.org/W4405179372, https://openalex.org/W4318426198, https://openalex.org/W2082432933, https://openalex.org/W2900701156, https://openalex.org/W2806536390, https://openalex.org/W3020788828, https://openalex.org/W2804787033, https://openalex.org/W3163907945, https://openalex.org/W2962914006, https://openalex.org/W2803281408, https://openalex.org/W3023907686, https://openalex.org/W3008967825, https://openalex.org/W3048475504, https://openalex.org/W2183341477, https://openalex.org/W2962816100, https://openalex.org/W3025967384, https://openalex.org/W4385799835, https://openalex.org/W3209880867, https://openalex.org/W4405877713, https://openalex.org/W3104646322, https://openalex.org/W3098350469 |
| referenced_works_count | 39 |
| abstract_inverted_index.7 | 156 |
| abstract_inverted_index.I | 120 |
| abstract_inverted_index.a | 3, 14, 26, 37, 43, 52, 60, 88, 98, 115 |
| abstract_inverted_index.II | 169 |
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| abstract_inverted_index.The | 188 |
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| abstract_inverted_index.GHz. | 157, 187 |
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| abstract_inverted_index.this | 1 |
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| abstract_inverted_index.with | 87, 199 |
| abstract_inverted_index.−8 | 133, 183 |
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| abstract_inverted_index.based | 65, 216 |
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| abstract_inverted_index.curve | 35, 190 |
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| abstract_inverted_index.rapid | 227 |
| abstract_inverted_index.which | 124, 177, 220 |
| abstract_inverted_index.−15 | 148 |
| abstract_inverted_index.9–12 | 186 |
| abstract_inverted_index.CDCGAN | 106 |
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| abstract_inverted_index.model. | 107 |
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| abstract_inverted_index.reduce | 75 |
| abstract_inverted_index.target | 111 |
| abstract_inverted_index.6.5–8 | 139 |
| abstract_inverted_index.C-band, | 114 |
| abstract_inverted_index.Further | 158 |
| abstract_inverted_index.X-band, | 176 |
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| abstract_inverted_index.carried | 163 |
| abstract_inverted_index.forward | 27 |
| abstract_inverted_index.inverse | 49 |
| abstract_inverted_index.models, | 59 |
| abstract_inverted_index.network | 20, 30, 46, 63 |
| abstract_inverted_index.pixels, | 97 |
| abstract_inverted_index.predict | 32 |
| abstract_inverted_index.process | 73 |
| abstract_inverted_index.reaches | 145 |
| abstract_inverted_index.result. | 204 |
| abstract_inverted_index.through | 104 |
| abstract_inverted_index.Absorber | 119, 168 |
| abstract_inverted_index.absorber | 6, 101 |
| abstract_inverted_index.approach | 23 |
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| abstract_inverted_index.training | 79 |
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| abstract_inverted_index.wideband | 4 |
| abstract_inverted_index.(CDCGAN). | 21 |
| abstract_inverted_index.absorber, | 39 |
| abstract_inverted_index.absorber. | 54 |
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| abstract_inverted_index.electromagnetic | 100 |
| abstract_inverted_index.customer-defined | 218 |
| abstract_inverted_index.GoogleNet-InceptionV3 | 67 |
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| citation_normalized_percentile.is_in_top_10_percent | False |