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Record W2391089924

Preparation and Application of Novel Fabric Finishing Agent Containing Nano ATO

2002· article· en· W2391089924 on OpenAlexaff
Yue Wu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicTextile materials and evaluations
Canadian institutionsCAE (Canada)
Fundersnot available
KeywordsDispersantSlurryMaterials scienceDispersion (optics)NanometreComposite materialNano-Dispersion stabilityElectrical conductorChemical engineeringPolymer
DOInot available

Abstract

fetched live from OpenAlex

A novel fabric finishing agent containing ATO ultrafine conductive powder is prepared and used for anti static treatment on PET fabric. The technology of the dispersability and stability of ATO ultrafine conductive powder in water have been studied, and the influence of those parameters such as the types of dispersants and the adding amount?pH value and methods of dispersion on the preparation of ATO slurry has also been discussed. Monodispersed ATO slurry can be made by using BN dispersant. While using KH560, keeping pH=9, milling 40?h, the effect of dispersion is the best. The surface resistance of PET fabric treated by the novel finishing agent could be decreased from order of 10 12 ?Ω to 10 10 ?Ω, and the value changed little after being washed 50 times.

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 score0.003

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 head0.051
GPT teacher head0.307
Teacher spread0.256 · 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

Citations13
Published2002
Admission routes1
Has abstractyes

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