Tuning the Physical Properties of Carboxylated Cellulose Nanocrystal (cCNC) Microspheres by Hybridizing with Silk Fibroin (SF)
Bibliographic record
Abstract
A new class of hydrophobic/lipophilic cellulose microspheres are made from carboxylated cellulose nanocrystals (cCNC) by adding silk fibroin (SF) protein in the course of spray-drying from aqueous suspension. We found mere 2% SF addition could leverage the surface energy with an increase of contact angle from 27.5° to 60.4°. Besides the complete altered surface energy from cellulose beads, the hybrid SF-cCNC microspheres also show improved mechanical properties and prolonged diffusion kinetics for transporting water-soluble ions / molecules (e.g., methylene blue). Depth profiling of the SF-cCNC microspheres reveals that SF is more concentrated at the surface in comparison with the core, and this surface localization is the reason for the tuned properties. Moreover, post methanol treatment of the SF-cCNC hybrid microspheres induces a β-sheet phase transition to the Silk II structure, which can further enhance the mechanical properties and slow down the small molecule transport of the microspheres. Therefore, a new method has been established that could tune the physical properties of functional cellulose microspheres through the control of SF structural transformation, which could significantly benefit for controlled drug release and microplastic beads replacement applications.
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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) | 0.000 | 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 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".