Adsorption of Xyloglucan onto Cellulose Surfaces of Different Morphologies: An Entropy-Driven Process
Bibliographic record
Abstract
The temperature-dependence of xyloglucan (XG) adsorption onto smooth cellulose model films regenerated from N-methylmorpholine N-oxide (NMMO) was investigated using surface plasmon resonance spectroscopy, and it was found that the adsorbed amount increased with increasing temperature. This implies that the adsorption of XG to NMMO-regenerated cellulose is endothermic and supports the hypothesis that the adsorption of XG onto cellulose is an entropy-driven process. We suggest that XG adsorption is mainly driven by the release of water molecules from the highly hydrated cellulose surfaces and from the XG molecules, rather than through hydrogen bonding and van der Waals forces as previously suggested. To test this hypothesis, the adsorption of XG onto cellulose was studied using cellulose films with different morphologies prepared from cellulose nanocrystals (CNC), semicrystalline NMMO-regenerated cellulose, and amorphous cellulose regenerated from lithium chloride/dimethylacetamide. The total amount of high molecular weight xyloglucan (XGHMW) adsorbed was studied by quartz crystal microbalance and reflectometry measurements, and it was found that the adsorption was greatest on the amorphous cellulose followed by the CNC and NMMO-regenerated cellulose films. There was a significant correlation between the cellulose dry film thickness and the adsorbed XG amount, indicating that XG penetrated into the films. There was also a correlation between the swelling of the films and the adsorbed amounts and conformation of XG, which further strengthened the conclusion that the water content and the subsequent release of the water upon adsorption are important components of the adsorption process.
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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".