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Record W3009683652

Scopes of Acid Washing with Varying Concentrations of Phosphoric Acid vis-à-vis Bleach Wash

2020· article· en· W3009683652 on OpenAlexaff
Md. Jakir Hossain, Md. Saiful Hoque, Muhammad Abdur Rashid

Bibliographic record

VenueJournal of textile and apparel technology and management · 2020
Typearticle
Languageen
FieldMaterials Science
TopicTextile materials and evaluations
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsBleachDenimPhosphoric acidPulp and paper industryChemistryComposite materialMaterials scienceOrganic chemistryEngineering
DOInot available

Abstract

fetched live from OpenAlex

To acquire different fading effect and aesthetic outlook several techniques are applied in order that bleach wash is mostly used. As we know many limitations of bleach wash so our main motive is to find out an alternative method which can deliver same or better positive result than bleach wash. For this instance, we intend different concentrated acid wash and draw a comparison between acid and bleach wash on 100% cotton indigo dyed denim fabric. During our research, denim garments were developed using three parameters; bleach concentration 10 gm/L, temperature 40°C, time 20 minutes where acid concentration 0.5 to 2.5 ml/L, temperature 50°C, time 15 minutes. Due to change in acid concentration, the variation of its physical and mechanical properties like strength, weight loss, GSM, EPI & PPI and absorbency are observed. Furthermore, we focus on the color change properties such as wash, rubbing and perspiration fastness, CMC, K/S value and whiteness index. At the end of our study, we noticed that acid washed garments exhibit a promising disparity in almost all properties than bleach washed garments including same fading effects of bleach wash is accomplished by using 2% phosphoric acid in case of acid washing on denim 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.

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)0.000
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 score0.015
Threshold uncertainty score0.361

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.017
GPT teacher head0.247
Teacher spread0.230 · 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 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

Citations0
Published2020
Admission routes1
Has abstractyes

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