All-Aqueous Liquid Crystal Nanocellulose Emulsions with Permeable Interfacial Assembly
Bibliographic record
Abstract
We report on the formation of water-in-water liquid crystal emulsions with permeable colloidal assemblies. Rodlike cellulose nanocrystals (CNC) spontaneously self-assemble into a helical arrangement with the coexistence of nonionic, hydrophilic polyethylene glycol (PEG) and dextran, whereas the two polymer solutions are thermodynamically incompatible. Stable water-in-water emulsions are easily prepared by mixing the respective CNC/polymer solutions, showing micrometric CNC/PEG dispersed droplets and a continuous CNC/dextran phase. With time, the resulting emulsion demixes into an upper, droplet-lean isotropic phase and a bottom, droplet-rich cholesteric phase. Owing to the osmotic pressure gradient between PEG and dextran phases, target transfer of cellulose nanoparticles occurs across the water/water interface to reassemble into a liquid crystal-in-liquid crystal emulsion with global cholesteric organization. The observed structural, optical, and temporal evolution confirm that the colloidal particles in the two immiscible phases experience short-range interactions and form long-range assemblies across the interface.
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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".