Evidence map›Paper›PMID 42845857›Full record

ArticleNanophotonics (Berlin, Germany)2026

Low-Frequency, Ultra-Thin and Ultra-Wideband Meta-Absorber via Resonance Enhancement Harnessing Magnetic Material.

Dan Liu, Xingshuo Cui, Yuxu Chen, Xiongyu Liang, Xiaochun Liu, Zhenxu Wang, Fei Gao, Tong Cai

Abstract read
In one paragraph

Article in Nanophotonics (Berlin, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

8 authors.

Dan LiuState Key Laboratory of Modern Optical Instrumentation the Electromagnetics Academy Zhejiang University Hangzhou China.
Xingshuo CuiAir Defense and Antimissile School Air Force Engineering University Xi'an China.ORCID https://orcid.org/0000-0001-8851-0774
Yuxu ChenAir Defense and Antimissile School Air Force Engineering University Xi'an China.ORCID https://orcid.org/0000-0001-6771-4495
Xiongyu LiangAir Defense and Antimissile School Air Force Engineering University Xi'an China.
Xiaochun LiuThe Research Institute for Special Structures of Aeronautical Composite ACICA The Aeronautical Science Key Lab for High Performance Electromagnetic Windows Ji'nan China.
Zhenxu WangAir Defense and Antimissile School Air Force Engineering University Xi'an China.
Fei GaoState Key Laboratory of Modern Optical Instrumentation the Electromagnetics Academy Zhejiang University Hangzhou China.ORCID https://orcid.org/0000-0001-9928-9390
Tong CaiState Key Laboratory of Modern Optical Instrumentation the Electromagnetics Academy Zhejiang University Hangzhou China.ORCID https://orcid.org/0000-0002-8562-3295

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Achieving efficient, ultra-thin, and broadband absorption in the low-frequency regime (e.g., P to S bands, 0.23-4 GHz) remains a significant challenge due to the inherent limitations of conventional materials and designs. To address this, we propose a composite metamaterial absorber that synergistically integrates a three-layer metasurface absorber (TLMA) with a top-loaded magnetic material (MM) layer. The standalone TLMA achieves perfect absorption (> 90%) but within a narrow 300 MHz band around 0.77 GHz. The introduction of the MM layer drastically enhances and broadens the resonant response through magnetic loss and optimized coupling, yielding an ultra-wide absorption bandwidth from 0.5 to 3.8 GHz, which effectively covers the P, L, and S bands. The final optimized structure exhibits a remarkable overall thickness of only 41.0 mm (0.068

Identifiers

PMID42845857
PMCPMC13642117

What OpenQuestion holds

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Registered trials

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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.