Influence of chitin purity on its dissolution behaviour in alkaline solvent
Bibliographic record
Abstract
The biopolymer chitin is a promising ingredient for bioplastics due to its strength and stability. Chitin fibres must be isolated from biomass by stripping away tightly bound minerals, proteins, and pigments. Depending on the desired chitin purity, this isolation process can be long and cost-prohibitive on industrial scale. Following isolation, chitin fibres must be dissolved or separated which is challenging due to chitins recalcitrance. Cryo-assisted dissolution in potassium hydroxide has been identified as a fast and non-toxic approach. However, to date, this method has not received widespread attention and has not been evaluated for chitins from different species. The present study demonstrated the dissolution of Northern pink shrimp (P. borealis) chitin using KOH solvent and the influence of residual impurities on dissolution behaviour was investigated for the first time. Three chitin samples with purities ranging from 84 to 97 % w/w were compared, and results confirmed that chitin with lower purity can be successfully dissolved in KOH solvent, provided that minerals were removed prior to dissolution. However, dissolution behaviour and physical properties were strikingly different between the samples. Microscopic analysis of chitin particles allowed the differentiation between exoskeleton features and the identification of insoluble particles, providing potential new avenues to improve dissolution processes.
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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 | 0.000 | 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".