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Record W4405598274 · doi:10.1177/15280837241279963

Electromagnetic shielding efficiency of hybrid knitted fabrics treated with mxene

2024· article· en· W4405598274 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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Industrial Textiles · 2024
Typearticle
Languageen
FieldMaterials Science
TopicElectromagnetic wave absorption materials
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research Chairs
KeywordsMaterials scienceElectromagnetic shieldingComposite material

Abstract

fetched live from OpenAlex

This study details the fabrication of a hybrid fabric structure achieved through the utilization of copper-cotton core-spun yarns and a streamlined dip-coating method for the coating of MXene sheets. This fabrication approach results in a substantial enhancement in electromagnetic interference shielding efficiency (EMI SE) in the X-band frequency (8.2-12.4 GHz) while significantly reducing the required number of MXene coating steps. The textile samples fabricated with 0.08 mm diameter copper core filaments and a knitting density of 12 gauge (needle/inch) exhibit a peak EMI SE of 43.9 dB following three MXene coating cycles, utilizing a 1×1 Rib knit pattern. In comparison, employing a Full Milano knit pattern results in an improved EMI SE, reaching up to 45.2 dB. These findings elucidate the substantial impact of knit structure and the effective MXene coating process on improving the EMI SE for hybrid textiles.

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 categoriesInsufficient payload (model declined to judge)
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 score0.004
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.022
GPT teacher head0.243
Teacher spread0.222 · 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