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Record W2075023341 · doi:10.1021/ie0700617

Continuous Dyeing of Cotton/Polyester and Polyester Fabrics with Reactive and Disperse Dyes Using Infrared Heat

2007· article· en· W2075023341 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

VenueIndustrial & Engineering Chemistry Research · 2007
Typearticle
Languageen
FieldEngineering
TopicDyeing and Modifying Textile Fibers
Canadian institutionsUniversité de Sherbrooke
FundersUniversité de Sherbrooke
KeywordsDyeingPolyesterMaterials scienceComposite materialPulp and paper industryDisperse dyeChemical engineering

Abstract

fetched live from OpenAlex

Continuous dyeing of cotton/polyester and 100% polyester fabrics was performed using mixtures of reactive and disperse dyes, or disperse dyes alone, respectively, and achieving dye fixation by heating, using an electric infrared oven situated in front of an electric hot air unit. Generally, the colors of the thermally produced dyeings were reasonably similar to those of the respective exhaust dyeings obtained using the same recipes. As expected, the thermally produced dyeings usually contained more unfixed dyes than the exhaust dyeings, largely a consequence of the quicker and less-efficient post-dyeing washing process. The results for pilot-scale dyeings are also compared with those obtained on an industrial scale in a finishing mill. Dyeing using infrared heating and hot air had no influence on the light stability of the colors or on the fabric handle. Most significantly, the negligible variation of color along the fabric length during continuous thermal dyeing illustrated that the process was well-controlled in all cases and could be valuable for the dyeing of small lots of fabric.

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 categoriesMeta-epidemiology (narrow)
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 score0.022
Threshold uncertainty score1.000

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 integrity0.0000.001
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 head0.055
GPT teacher head0.292
Teacher spread0.237 · 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