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Record W3173999445 · doi:10.5539/jms.v11n2p100

Biodegradable Polyamide 6.6 for Textile Application

2021· article· en· W3173999445 on OpenAlexvenueno aff
Maria Carolina Garcia Peixoto Sacchi, Jo�ão Paulo Pereira Marcicano, Fernando Barros de Vasconcelos

Bibliographic record

VenueJournal of Management and Sustainability · 2021
Typearticle
Languageen
FieldMaterials Science
TopicTextile materials and evaluations
Canadian institutionsnot available
Fundersnot available
KeywordsBiodegradationPolyamideTextileDyeingYarnUltimate tensile strengthMaterials scienceComposite materialElongationTenacity (mineralogy)Pulp and paper industryFiberChemistryEngineeringOrganic chemistry

Abstract

fetched live from OpenAlex

The study evaluates comparatively some physical and chemical properties of polyamide 6.6 standard and biodegradable. It also evaluates the period of biodegradation of the biodegradable yarn sample and standard sample. The physical properties analyzed were tensile strength, elongation, and tenacity. The chemical properties were related to the behavior of the samples in dyeing and the evaluation of subsequent strength dyeing. The evaluated samples were taken from knitwear produced with polyamide textured filament yarn 80 dtex f 68x1, standard and biodegradable, being purged, bleached, and dyed. The results of the physical tests, although statistically different, have values ​​very near the average, which in practice represent acceptable values ​​within the statistical control process. Both standard and biodegradable samples had the same chemical behavior and there is no difference. Concerning to biodegradation time under laboratory conditions, the carbon dioxide produced by the samples was monitored and measured to determine the percentage of biodegradation according to ASTM D 5511. After 735 days the percentage of biodegradation of the biodegradable yarn was 81.7% and of the normal yarn was 5.2%. This is an expressive gain in ecological terms for synthetic fiber.

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 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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.476
Threshold uncertainty score0.223

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 head0.012
GPT teacher head0.279
Teacher spread0.267 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations3
Published2021
Admission routes1
Has abstractyes

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