Equilibrium Swelling, Interstitial Forces, and Water Structuring in Phytoglycogen Nanoparticle Films
Bibliographic record
Abstract
Phytoglycogen is a highly branched polymer of glucose that forms dendrimeric nanoparticles. This special structure leads to a strong interaction with water that produces exceptional properties such as high water retention, low viscosity, and high stability of aqueous dispersions. We have used ellipsometry at controlled relative humidity (RH) to measure the equilibrium swelling of ultrathin films of phytoglycogen, which directly probes the interstitial forces acting within the films. Comparison of the swelling behavior of films of highly branched phytoglycogen to that of other glucose-based polysaccharides shows that the chain architecture plays an important role in determining both the strong, short-range repulsion of the chains at low RH and the repulsive hydration forces at high RH. In particular, the length scale λ 0 that characterizes the exponentially decaying hydration forces provides a quantitative, RH-independent measure of film swelling that differs significantly for different glucose-based polysaccharides. By combining ellipsometry with infrared spectroscopy, we have determined the relationship between water structuring and inter-chain separation in the highly branched phytoglycogen nanoparticles, with maintenance of a high degree of water structure as the film swells significantly at high RH. These insights into the structure–hydration relationship for phytoglycogen are essential to the development of new products and technologies based on this sustainable nanomaterial.
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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".