A guidance to intelligent metamaterials and metamaterials intelligence
Abstract The bidirectional interactions between metamaterials and artificial intelligence have recently attracted immense interest to motivate scientists to revisit respective communities, giving rise to the proliferation of intelligent metamaterials and metamaterials intelligence. Owning to the str...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2025-01-01
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| Series: | Nature Communications |
| Online Access: | https://doi.org/10.1038/s41467-025-56122-3 |
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| _version_ | 1832571549619585024 |
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| author | Chao Qian Ido Kaminer Hongsheng Chen |
| author_facet | Chao Qian Ido Kaminer Hongsheng Chen |
| author_sort | Chao Qian |
| collection | DOAJ |
| description | Abstract The bidirectional interactions between metamaterials and artificial intelligence have recently attracted immense interest to motivate scientists to revisit respective communities, giving rise to the proliferation of intelligent metamaterials and metamaterials intelligence. Owning to the strong nonlinear fitting and generalization ability, artificial intelligence is poised to serve as a materials-savvy surrogate electromagnetic simulator and a high-speed computing nucleus that drives numerous self-driving metamaterial applications, such as invisibility cloak, imaging, detection, and wireless communication. In turn, metamaterials create a versatile electromagnetic manipulator for wave-based analogue computing to be complementary with conventional electronic computing. In this Review, we stand from a unified perspective to review the recent advancements in these two nascent fields. For intelligent metamaterials, we discuss how artificial intelligence, exemplified by deep learning, streamline the photonic design, foster independent working manner, and unearth latent physics. For metamaterials intelligence, we particularly unfold three canonical categories, i.e., wave-based neural network, mathematical operation, and logic operation, all of which directly execute computation, detection, and inference task in physical space. Finally, future challenges and perspectives are pinpointed, including data curation, knowledge migration, and imminent practice-oriented issues, with a great vision of ushering in the free management of entire electromagnetic space. |
| format | Article |
| id | doaj-art-dd04b95a672d4f828868713a3699da11 |
| institution | Kabale University |
| issn | 2041-1723 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Nature Communications |
| spelling | doaj-art-dd04b95a672d4f828868713a3699da112025-02-02T12:31:44ZengNature PortfolioNature Communications2041-17232025-01-0116112310.1038/s41467-025-56122-3A guidance to intelligent metamaterials and metamaterials intelligenceChao Qian0Ido Kaminer1Hongsheng Chen2ZJU-UIUC Institute, Interdisciplinary Center for Quantum Information, State Key Laboratory of Extreme Photonics and Instrumentation, Zhejiang UniversityDepartment of Electrical and Computer Engineering, Technion-Israel Institute of TechnologyZJU-UIUC Institute, Interdisciplinary Center for Quantum Information, State Key Laboratory of Extreme Photonics and Instrumentation, Zhejiang UniversityAbstract The bidirectional interactions between metamaterials and artificial intelligence have recently attracted immense interest to motivate scientists to revisit respective communities, giving rise to the proliferation of intelligent metamaterials and metamaterials intelligence. Owning to the strong nonlinear fitting and generalization ability, artificial intelligence is poised to serve as a materials-savvy surrogate electromagnetic simulator and a high-speed computing nucleus that drives numerous self-driving metamaterial applications, such as invisibility cloak, imaging, detection, and wireless communication. In turn, metamaterials create a versatile electromagnetic manipulator for wave-based analogue computing to be complementary with conventional electronic computing. In this Review, we stand from a unified perspective to review the recent advancements in these two nascent fields. For intelligent metamaterials, we discuss how artificial intelligence, exemplified by deep learning, streamline the photonic design, foster independent working manner, and unearth latent physics. For metamaterials intelligence, we particularly unfold three canonical categories, i.e., wave-based neural network, mathematical operation, and logic operation, all of which directly execute computation, detection, and inference task in physical space. Finally, future challenges and perspectives are pinpointed, including data curation, knowledge migration, and imminent practice-oriented issues, with a great vision of ushering in the free management of entire electromagnetic space.https://doi.org/10.1038/s41467-025-56122-3 |
| spellingShingle | Chao Qian Ido Kaminer Hongsheng Chen A guidance to intelligent metamaterials and metamaterials intelligence Nature Communications |
| title | A guidance to intelligent metamaterials and metamaterials intelligence |
| title_full | A guidance to intelligent metamaterials and metamaterials intelligence |
| title_fullStr | A guidance to intelligent metamaterials and metamaterials intelligence |
| title_full_unstemmed | A guidance to intelligent metamaterials and metamaterials intelligence |
| title_short | A guidance to intelligent metamaterials and metamaterials intelligence |
| title_sort | guidance to intelligent metamaterials and metamaterials intelligence |
| url | https://doi.org/10.1038/s41467-025-56122-3 |
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