Thermal Analysis and Characterization of Some Cellulosic Fabrics Dyed by a New Natural Dye and Mordanted with Different Mordants
Bibliographic record
Abstract
A new natural dye was extracted from Bisham plant then applied to cotton and linen fabrics. The thermal stability of these fabrics in their blank state then dyed by this natural dye (Commiphora-gileadensis), and then mordanted by different mordants that are; Alum (Potassium and Aluminum Sulfate) AL2K2 (SO4).24H2O - Chrome (Potassium di-Chromate K2Cr2O7 ) and Ferrous sulfate (FeSO4.7H2O) which were applied separately. Thermal analysis is a convenient, useful and reproducible method for characterizing complex organic materials. Thermo-gravimetric analysis (TGA), its differential (DTG) and differential scanning calorimetry (DSC) were used to evaluate the effect of mordanting cotton and linen fabric on their thermal behaviour. These techniques can distinguish between different fiber generic types and between different mordants applied to their dyed fabrics. It was possible to detect the presence of the mordant component when present in small proportions. Although cotton and linen fabrics produce the same DTG peaks, they can be differentiated as their main endothermic peaks occur at significantly different temperature (about 348,339oC respectively).Also, linen fabric produces an asymmetrical deep peak compared with the sharper, more symmetrical peak of cotton.
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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".