Scopes of Acid Washing with Varying Concentrations of Phosphoric Acid vis-à-vis Bleach Wash
Bibliographic record
Abstract
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 machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".