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Record W2529916886 · doi:10.1111/jace.14583

Enhanced dielectric and microwave absorption properties of Cr/Al <sub>2</sub> O <sub>3</sub> coatings deposited by low‐power plasma spraying

2016· article· en· W2529916886 on OpenAlexaff
Liang Zhou, Meng Chen, Yanli Dong, Zhanwei Yuan

Bibliographic record

VenueJournal of the American Ceramic Society · 2016
Typearticle
Languageen
FieldMaterials Science
TopicElectromagnetic wave absorption materials
Canadian institutionsUniversity of Toronto
FundersChang'an UniversityXi’an Jiaotong UniversityNatural Science Foundation of Shaanxi ProvinceNational Natural Science Foundation of China
KeywordsMaterials scienceReflection lossMicrowaveCoatingDielectric lossPermittivityDielectricThin filmAbsorption (acoustics)Composite materialAnalytical Chemistry (journal)OptoelectronicsComposite numberNanotechnologyChemistry

Abstract

fetched live from OpenAlex

Abstract Low‐power plasma‐sprayed Cr/Al 2 O 3 coatings have been developed for their potential application as broad bandwidth, thin thickness, lightweight, and strong microwave‐absorbing materials. The dielectric and microwave absorption properties of the as‐sprayed coatings were studied in the X‐band (from 8.2 to 12.4 GH z). High complex permittivity of the coatings was obtained because of a large number of internal boundaries and the conductive networks. Meanwhile, a significant enhancement of microwave absorption properties of the coating was achieved due to the enhanced interfacial polarization and conductance loss. The reflection loss ( RL ) <−10 dB of the Al 2 O 3 –15Cr coating was obtained from 9.8 to 11.4 GH z by choosing an appropriate coating thickness, and an optimal minimum reflection loss ( RL min ) of −45.35 dB was achieved at 10.3 GH z with a thin thickness of 1.32 mm.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.006
GPT teacher head0.203
Teacher spread0.197 · 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 source (direct Gemma or distilled Codex), 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

Citations24
Published2016
Admission routes1
Has abstractyes

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Same venueJournal of the American Ceramic SocietySame topicElectromagnetic wave absorption materialsFrench-language works237,207