Order and gelation of cellulose nanocrystal suspensions: an overview of some issues
Bibliographic record
Abstract
Cellulose nanocrystals (CNCs) are polydisperse rod-shaped particles of crystalline cellulose I, typically prepared by sulfuric acid hydrolysis of natural cellulose fibres to give aqueous colloidal suspensions stabilized by sulfate half-ester groups. Sufficiently dilute suspensions are isotropic fluids, but as the concentration of CNC in water is increased, a critical concentration is reached where a spontaneously ordered phase is observed. The (equilibrium) phase separation of the ordered chiral nematic phase is in competition with a tendency of the CNC suspension to form a gel. Qualitatively, factors that reduce the stability of the CNC suspension favour the onset of gelation. The chiral nematic structure is preserved, at least partially, when the suspension dries. Solid chiral nematic films of cellulose are of interest for their optical and templating properties, but the preparation of the films requires improvement. The processes that govern the formation of solid chiral nematic films from CNC suspensions include phase separation, gelation and also the effects of shear on CNC orientation during evaporation. Some insight into these processes is provided by polarized light microscopy, which indicates that the relaxation of shear-induced orientation to give a chiral nematic structure may occur via an intermediate twist-bend state.This article is part of a discussion meeting issue 'New horizons for cellulose nanotechnology'.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".