Cellulose fiber networks reinforced with glutaraldehyde–chitosan complexes
Bibliographic record
Abstract
ABSTRACT In this study, glutaraldehyde–chitosan complexes (GA–chitosan) were prepared and were used as functional additives to enhance the strength properties of cellulose fiber networks. The adsorption and distribution of GA–chitosan on the surface of cellulose fiber were characterized by scanning electron microscopy, X‐ray photoelectron spectroscopy and time‐of‐flight secondary ion mass spectrometry. The effects of glutaraldehyde dosage and GA–chitosan to fiber ratio on the strength properties, including wet‐strength, wet‐web strength, and dry strength, were investigated. GA–chitosan did not require high temperature curing and had good cross‐linking rates at room temperature. Samples treated with GA–chitosan exhibited significant improvements in their mechanical properties. Wet tensile index and wet‐web tensile index (both at 50% solids), and dry tensile index, were increased by about 1300, 190, and 115%, respectively. The GA–chitosan additive developed in this study provides a useful approach to prepare high‐performance value‐added specialty wood‐fiber based products. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015 , 132 , 42375.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".