Influence of Fine Structure on the Variations of Thermal and Mechanical Properties in Flax Fibers Modified with Different Alkaline Treatment Conditions
Bibliographic record
Abstract
The alkaline treatment condition plays a crucial role in governing the ultimate properties of flax fibers. In this study, flax fibers were modified with mild alkalization and severe mercerization conditions to give fundamental insight into how the molecular-scale changes in cell wall fine structure and cellulose supramolecular structure can affect the macroscopic properties of fibers. SEM, FTIR, XRD, TGA, and DSC techniques were employed to characterize the variations in morphology, composition, crystalline structure, and thermal properties of fibers. Also, tensile tests evaluated their reinforcing performance in polypropylene-based composites. The results indicated that alkalization in 5% (w/v) NaOH solution preserved the tensile properties of fibers, shifted their thermal decomposition temperature from 198 to 254°C, and effectively decreased their moisture absorption content by 18%. The improvements primarily originate from the partial removal of noncellulosic constituents and promoted crystallinity of native cellulose Iβ structure. However, mercerization in 20% (w/v) solution significantly reduced the rigidity of fibers in the longitudinal direction. Furthermore, it decreased the moisture absorption only by 6% and shifted the thermal degradation to 275°C. The excessive elimination of noncellulosic constituents and the polymorphic transformation, which led to a weaker hydrogen bonding network in the cellulose II region, accounts for these changes.
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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".