Evidence map›Paper›PMID 39679235›Full record

ArticleNanophotonics (Berlin, Germany)2024

On-demand Doppler-offset beamforming with intelligent spatiotemporal metasurfaces.

Xiaoyue Zhu, Chao Qian, Jie Zhang, Yuetian Jia, Yaxiong Xu, Mingmin Zhao, Minjian Zhao, Fengzhong Qu, Hongsheng Chen

Abstract read
In one paragraph

Article in Nanophotonics (Berlin, Germany), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Anti-radar based on metasurface.Nature communications · 2025
    Article
  2. Review
  3. Harnessing the Missing Spectral Correlation for Metasurface Inverse Design.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2024
    Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Xiaoyue ZhuZJU-UIUC Institute, Interdisciplinary Center for Quantum Information, State Key Laboratory of Extreme Photonics and Instrumentation, Zhejiang University, Hangzhou 310027, China.
Chao QianZJU-UIUC Institute, Interdisciplinary Center for Quantum Information, State Key Laboratory of Extreme Photonics and Instrumentation, Zhejiang University, Hangzhou 310027, China.
Jie ZhangZJU-UIUC Institute, Interdisciplinary Center for Quantum Information, State Key Laboratory of Extreme Photonics and Instrumentation, Zhejiang University, Hangzhou 310027, China.
Yuetian JiaZJU-UIUC Institute, Interdisciplinary Center for Quantum Information, State Key Laboratory of Extreme Photonics and Instrumentation, Zhejiang University, Hangzhou 310027, China.
Yaxiong XuZJU-UIUC Institute, Interdisciplinary Center for Quantum Information, State Key Laboratory of Extreme Photonics and Instrumentation, Zhejiang University, Hangzhou 310027, China.
Mingmin ZhaoDepartment of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China.
Minjian ZhaoDepartment of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China.
Fengzhong QuOcean College Zhejiang University, Zhoushan 316021, China.
Hongsheng ChenZJU-UIUC Institute, Interdisciplinary Center for Quantum Information, State Key Laboratory of Extreme Photonics and Instrumentation, Zhejiang University, Hangzhou 310027, China.ORCID https://orcid.org/0000-0002-5735-9781

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recently, significant efforts have been devoted to guaranteeing high-quality communication services in fast-moving scenes, such as high-speed trains. The challenges lie in the Doppler effect that shifts the frequency of the transmitted signal. To this end, the recent emergence of spatiotemporal metasurfaces offers a promising solution, which can manipulate electromagnetic waves in time and space domain while being lightweight and cost-effective. Here we introduce deep learning-assisted spatiotemporal metasurfaces to automatically and adaptively neutralize Doppler effect in fast-moving situations. A tandem neural network is used to establish a rapid connection between on-site targets and time-varying series of spatiotemporal metasurfaces, endowing the capability of on-demand beamforming with Doppler effects offset. Moreover, oblique incidence problems are also studied in practice, which can be used for relieving multipath effect. In the microwave experiment, we fabricate the intelligent spatiotemporal metasurfaces and demonstrate the potential to fulfill Doppler-offset beamforming under oblique incidence.

Indexed as

Doppler effectsinverse design and deep learningspatiotemporal metasurfaceswireless communications

Identifiers

PMID39679235
PMCPMC11636439

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.