Novel multiphase systems based on thermoplastic chitosan: Analysis of the structure-properties relationships
Bibliographic record
Abstract
© 2016 AIP Publishing LLC.In the last years, biopolymers have attracted great attention. It is for instance the case of chitosan, a linear polysaccharide. It is a deacetylated derivative of chitin, which is the second most abundant polysaccharide found in nature after cellulose. Chitosan has been found to be nontoxic, biodegradable, biofunctional, and biocompatible in addition to having antimicrobial and antifungal properties, and thus has a great potential for environmental (packaging,) or biomedical applications.For preparing chitosan-based materials, only solution casting or similar methods have been used in all the past studies. Solution casting have the disadvantage in low efficiency and difficulty in scaling-up towards industrial applications. Besides, a great amount of environmentally unfriendly chemical solvents are used and released to the environment in this method. The reason for not using a melt processing method like extrusion or kneading in the past studies is that chitosan, like many other polysaccharides such as starch, has very low thermal stability and degrade prior to melting. Therefore, even if the melt processing method is more convenient and highly preferred for industrial production, its adaptation for polysaccharide-based materials remains very difficult. However, our recently published studies has demonstrated the successful use of an innovative melt processing method (internal mixer, extrusion,) as an alternative route to solution casting, for preparing materials based on thermoplastic chitosan. These promising thermoplastic materials, obtained by melt processing, have been the main topic of recent international projects, with partners from different countries Multiphase systems based on various renewable plasticizers have been elaborated and studied. Besides, different blends, and nano-biocomposites based on nanoclays, have been elaborated and fully analyzed. The initial consortium of this vast project was based on an international consortium (Canada, Australia, France). This project is currently ongoing and open, with new international academic partners (Mexico, Brazil and Spain).
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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 | 0.000 | 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".