Influence of washing with sodium lauryl sulphate (SLS) surfactant on different properties of ramie fibres
Bibliographic record
Abstract
Green composite materials are a means of reducing reliance on synthetic and especially single-use plastics (SUP) and raising public awareness of the need for urgent action to protect the planet. Natural (lignocellulosic) fibres are increasingly utilized as the reinforcement in polymer matrix composites, in search for increased renewability and sustainability. This work concerns the effect of washing ramie (Boehmeria nivea) fibres using sodium lauryl sulphate (SLS) surfactant. The SLS-treated ramie fibres were examined for their morphological, physical, thermal, structural, and mechanical properties by powder X-ray diffraction (XRD), Fourier transform infrared (FTIR) spectroscopy, thermogravimetric analysis (TGA), scanning electron microscopy (SEM), and tensile testing. SLS treated ramie fibres density and crystallinity index values were 1.23 g/cc and 84.5%, respectively, with a very high cellulose content of 81.3%, because hemicellulose and loose particles were dissolved. SEM images depicted the relevant changes, with no significant damage on treated fibre surfaces. With some assistance from the treatment, fibres initiated their degradation only above 250 °C, culminating at 327 °C, which appears suitable for the manufacturing of composites with the most common matrices.
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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".