Solvent‐free acetylation of lignocellulosic fibers at room temperature: Effect on fiber structure and surface properties
Bibliographic record
Abstract
ABSTRACT Acetylation is one of the most interesting chemical treatments to improve the affinity of lignocellulosic fibers with polymeric matrices for the elaboration of several types of composites. In this paper, the acetylation of flax and wood pulp (bleached softwood Kraft pulp and thermomechanical pulp) fibers was carried out at room temperature in a solvent‐free system with acetic anhydride in the presence of sulfuric acid as catalyst. The effect of acetylation on the fine structure of fibers was investigated by spectroscopic methods, while the extent of acetylation was quantified by weight percent gain. The effect of reaction time on fiber morphology was studied at macro‐ and microscale using scanning electron microscopy, optical microscopy, and fiber quality analysis. The evolution of the hydrophobic/hydrophilic character of fibers was determined by contact angle measurements. The wettability of fibers by liquid epoxy resin was also evaluated to confirm the improvement of the affinity of acetylated fibers with the epoxy matrix. It was found that the hydrophilic character of fibers decrease with increasing reaction time, whereas the trend was less pronounced beyond specific reaction times. Acetylated fibers can therefore be potential candidates for replacing nonbiodegradable reinforcing materials in composite applications. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015, 132, 42247.
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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".