Adsorption, kinetic, and thermodynamic studies of natural curcumin dye on cotton and polyamide fabric and the liberation of its active principle
Bibliographic record
Abstract
Abstract The increasing emphasis on environmental sustainability and the demand for eco‐friendly practices have led to a surge in interest in natural products, particularly natural dyes, across industries, including textiles. Curcumin, extracted from the turmeric plant, has gained widespread application not only for its vibrant colour characteristics but also for numerous therapeutic properties, serving as an antioxidant, anti‐inflammatory agent, and promoting wound‐healing effects. This study aims to understand the physical and chemical phenomena associated with the adsorption and desorption of turmeric extract and its active principles on cotton and polyamide fibres through mathematical models, with the goal of expanding textile applications. Dyeing experiments revealed adsorption equilibrium times of less than 25 min for both fibres, with the pseudo‐second‐order model providing the best fit for dyeing kinetics, suggesting control through the chemisorption process. The Freundlich model better suited cotton adsorption isotherms ( R 2 = 0.778), while the Langmuir model fit well for polyamide ( R 2 = 0.981). Thermodynamic parameters indicated non‐spontaneous interactions between curcumin and cotton, with an endothermic process, and an exothermic and spontaneous process for polyamide. Friction and water tests indicated greater colour resistance for polyamide, with grades exceeding 4. Desorption tests in 100% ethanol solution showed a total release of only 0.88% and 0.97% for polyamide and cotton, respectively, sustained for 12 h, fitting the Higuchi mathematical model, indicating a purely diffusive release process. These results demonstrate the potential of curcumin dye for achieving high dye exhaustion percentages in natural and synthetic fabrics and sustained release properties.
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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 | 0.001 |
| 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".