Nanocellulose in Emulsions and Heterogeneous Water‐Based Polymer Systems: A Review
Bibliographic record
Abstract
Nanocelluloses (i.e., bacterial nanocellulose, cellulose nanocrystals, and cellulose nanofibrils) are cellulose-based materials with at least one dimension in the nanoscale. These materials have unique and useful properties and have been shown to assemble at oil-water interfaces and impart new functionality to emulsion and latex systems. Herein, the use of nanocellulose in both emulsions and heterogeneous water-based polymers is reviewed, including dispersion, suspension, and emulsion polymerization. Comprehensive tables describe past work employing nanocellulose as stabilizers or additives and the properties that can be tailored through the use of nanocellulose are highlighted. Even at low loadings, nanocellulose offers an unprecedented level of control as a property modifier for a range of emulsion and polymer applications, influencing, for example, emulsion type, stability, and stimuli-responsive behavior. Nanocellulose can tune polymer particle properties such as size, surface charge, and morphology, or be used to produce capsules and polymer nanocomposites with enhanced mechanical, thermal, and adhesive properties. The role of nanocellulose is discussed, and a perspective for future direction is presented.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".