Ultrasonic-assisted sustainable extraction and dyeing of organic cotton fabric using natural dyes from Dillenia indica leaf
Bibliographic record
Abstract
As a means of preventing environmental damage caused by synthetic dyes, eco-friendly textile dyeing with natural dyes is gaining popularity worldwide. This study focused on the extraction of dyes from the leaf of Dillenia indica ( D. indica ) tree using an ultrasonic extraction technique and applied on the organic cotton fabrics. The ultrasonic method was used for both extractions of D. indica dyes and dyeing of organic cotton fabrics. Here, the amount of D. indica powder used were 5% and 6.67% for producing light and dark shade, respectively. The investigation of the color fastness to washing, rubbing, and light for the dyed organic cotton fabrics indicated an excellent rating. The spectrophotometric analysis revealed the L* (lightness or darkness), a* (redness or greenness), b* (yellowness or blueness), C* (chroma), h* (hue), R% (reflectance), and K/S (color strength) values, which accurately represented the shade of the dyed organic cotton fabric. To understand the interaction between D. indica dye and organic cotton fabrics, different characterization including, Fourier transform infrared spectroscopy (FTIR) and scanning electron microscopy (SEM) were performed. The characterization outcomes confirmed the successful deposition of D. indica dyes on the organic cotton fabrics. The other comparable testing results such as bursting strength, air permeability, and thermogravimetric analysis (TGA) of dyed and undyed organic cotton fabrics were in the acceptable range. One of the important findings of this research was no chemicals were utilized during the extraction and dyeing of organic cotton fabrics. This process can be referred to as completely chemical-free and advantageous for the environment because no chemicals were needed during extraction or dyeing. Therefore, the natural dye extracted from D. indica is extremely promising and could be a viable option for the sustainable dyeing of cotton fabrics in the textile dyeing industry.
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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) | 0.000 | 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) | 0.001 | 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".