PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
June 12, 2024Advanced Functional Materials10 citations

Machine‐Learning‐Enabled Multi‐Frequency Synthesis of Space‐Time‐Coding Digital Metasurfaces

View Full Paper
MRMarco RossiLZLei ZhangXCXiao Qing Chen

Key Points

Key points are not available for this paper at this time.

Abstract

Abstract Digital metasurfaces based on space‐time coding have established themselves as a powerful and versatile platform for joint spatial/spectral control of electromagnetic waves. However, their advanced design remains a largely open problem with significant computational challenges. This study introduces a novel approach, based on deep neural networks, to address this challenge. The proposed technique enables the simultaneous and independent multi‐frequency synthesis of scattering patterns, allowing precise tailoring of the harmonic equivalent currents (both in magnitude and phase), and enhancing spectral efficiency. These results, experimentally validated at X‐band microwave frequencies, substantially broaden the capabilities of space‐time coding digital metasurfaces, paving the way for advanced applications in wireless communications, sensing, and imaging.

Ask AI
Helpful
Bookmark
Share
View Full Paper

Cite This Study

Rossi et al. (2024) studied this question.

synapsesocial.com/papers/68e64f8fb6db6435875e0752https://doi.org/10.1002/adfm.202403577
Ask AI
Helpful
Bookmark
Share
View Full Paper