Morphology and porosity of pure and magnetite nanoparticles decorated porous cellulose nanocrystal cryogel monoliths
Bibliographic record
Abstract
The investigation of porosity and porous materials have been of great interest to the medical field. Cellulose nanocrystals (CNC) are an attractive biocompatible natural material currently under development for use in tissue engineering. Herein, we probe the fabrication of carboxylated CNC-based cryogel scaffolds using the freeze-casting technique. We also employed a combination of characterization techniques to probe scaffold porosity, including scanning electron microscopy (SEM), small-angle X-ray scattering (SAXS), and dynamic vapor sorption (DVS). Our findings showed that macropore morphologies of the CNC-based cryogel scaffolds depend on the conditions under which water freezing takes place. The SAXS data fitted using the mass fractal model and power law suggest that the CNCs aggregated to form well-defined walls in the range of 96.7 nm – 27.3 nm for all samples, while the incorporation of nanoparticles disrupted this compactness in the range of 27.3 – 4.8 nm. The nanoparticles also showed a direct influence on water uptake of the cryogel scaffolds by reducing water sorption mesopores with a radius of 5 – 6 nm, as shown by the DVS technique.
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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".