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Record W4391953682 · doi:10.1080/09205071.2023.2301577

Ultra-wideband absorber based on graphene surface with polarization insensitivity under large angles

2024· article· en· W4391953682 on OpenAlexaff
Zhefei Wang, Ziru Hou, Junxiang Ge, Fayu Wan, Qingsheng Zeng, Mingxin Song, Jianqiang Hou, Larbi Talbi, Tayeb A. Denidni

Bibliographic record

VenueJournal of Electromagnetic Waves and Applications · 2024
Typearticle
Languageen
FieldEngineering
TopicAdvanced Antenna and Metasurface Technologies
Canadian institutionsInstitut National de la Recherche ScientifiqueUniversité du Québec à MontréalUniversité du Québec en Outaouais
Fundersnot available
KeywordsMolar absorptivityWidebandOpticsPolarization (electrochemistry)Materials scienceBrewster's angleImpedance matchingOblique caseAzimuthElectromagnetic radiationElectrical impedanceMetamaterial absorberMetamaterialPhysicsTunable metamaterials

Abstract

fetched live from OpenAlex

In this paper, a frequency-selective absorber with large-angular stability under oblique incidence is present. The absorptivity of the structure can be reached to maximum by impedance matching and parameter optimization method under a specific angle (40°), which ensures an excellent absorption response within 60° oblique incidence. This method solves the problem that the absorptivity of traditional absorbers deteriorates with the increase of incident angle. The absorber consists of a three-layer structure: two lossy layers and a metal ground layer, the equivalent circuit model is discussed and the operating frequency band is widened by generating electric resonances and magnetic resonances. Due to the high symmetry of the structure, the absorber has good polarization insensitivity. Numerical simulation shows that from 4.4 to 20 GHz, the absorptivity of the structure is above 90% within 40° oblique angle of incidence. Finally, the design plays an important role in military stealth and preventing electromagnetic interference.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.425
Threshold uncertainty score0.332

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 head0.005
GPT teacher head0.210
Teacher spread0.205 · 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 designBench or experimental
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

Citations2
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Electromagnetic Waves and ApplicationsSame topicAdvanced Antenna and Metasurface TechnologiesFrench-language works237,207