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Record W2799844810 · doi:10.1049/joe.2018.0070

SE adjustment of planar mesh screen by fine‐tuning metal thickness

2018· article· en· W2799844810 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueThe Journal of Engineering · 2018
Typearticle
Languageen
FieldEngineering
TopicNanomaterials and Printing Technologies
Canadian institutionsSafran Electronics (Canada)
FundersEuropean Regional Development FundRégion BretagneMinistère de l'Education Nationale, de l'Enseignement Superieur et de la RechercheEuropean Commission
KeywordsMaterials sciencePlanarTransparency (behavior)MicrowaveElectromagnetic shieldingMetalMicroelectronicsOptoelectronicsSubstrate (aquarium)Electrical impedanceOpticsComposite materialComputer scienceElectrical engineeringTelecommunicationsMetallurgyEngineering

Abstract

fetched live from OpenAlex

The study presents the thickness effect of mesh metal films printed onto glass substrate on the shielding effectiveness (SE) of such transparent screens. Currently, standards in microelectronic technology use a metal film thickness of between ∼100 nm and few micrometres, depending on the available deposition and implementation techniques. This study demonstrates that the thickness of mesh metal films is a key parameter which needs to be adjusted precisely. A theoretical model based on SE, complex impedance and optical transparency has been developed for this purpose. At microwaves, a relevant selection of the metal thickness values from 0.1 to 2 µm changes the SE at low frequency (from 36 to 40 dB at 2 GHz, respectively) while maintaining it constantly at a higher frequency (close to 20 dB at 18 GHz). The optical transparency of such mesh screens is kept constant over the entire visible light spectrum (78%). Experimental data are in complete agreement with the theoretical values.

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.

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)0.001
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 score0.027
Threshold uncertainty score0.363

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.013
GPT teacher head0.212
Teacher spread0.199 · 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