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Record W4391099650 · doi:10.1063/5.0182434

Optically transparent wideband metamaterial absorber based on equivalent aperture and characteristic mode analysis

2024· article· en· W4391099650 on OpenAlexaff
Qi Zheng, Jingjing Qi, Jinyu Ma, Peyman PourMohammadi, Qiwei Li

Bibliographic record

VenueJournal of Applied Physics · 2024
Typearticle
Languageen
FieldEngineering
TopicAdvanced Antenna and Metasurface Technologies
Canadian institutionsInstitut National de la Recherche Scientifique
FundersChina Academy of Space TechnologyNatural Science Foundation of Shanghai
KeywordsMaterials scienceWidebandOpticsOptoelectronicsMetamaterialMetamaterial absorberTransmittancePolarization (electrochemistry)Absorption (acoustics)Indium tin oxideLayer (electronics)Composite materialPhysics

Abstract

fetched live from OpenAlex

In this work, a low-profile optical transparent wideband metamaterial absorber based on radiation–absorption reciprocal theory is proposed. The top layer and bottom layer are composed of indium tin oxide–polyethylene terephthalate films, and the middle layer is a transparent substrate polymethyl methacrylate. The method of transparent wideband absorption using reciprocal theory is proposed to guide the design. Based on characteristic mode analysis and calculated equivalent aperture efficiency, the absorber consisting of composite resonators is analyzed and designed. The equivalent circuit model and surface current distributions are studied to verify the design. The numerical results show that high absorption of greater than 90% in the frequency range of 5.7–16.4 GHz is obtained. A wideband absorption rate of greater than 80% at a 60° incident angle under TM polarization and an absorption rate of greater than 65% at a 60° incident angle under TE polarization are obtained. The proposed design has the advantages of broadband absorption, polarization insensitivity, light transmittance of more than 70%, and compact structure, which can be applied to special scenes that require optical transparency, such as anechoic chamber glass and cockpit glass.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.354
Threshold uncertainty score0.499

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.016
GPT teacher head0.251
Teacher spread0.235 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2024
Admission routes1
Has abstractyes

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