Recent Developments in the Formulation and Use of Polymers and Particles of Plant‐based Origin for Emulsion Stabilizations
Bibliographic record
Abstract
The main scope of this Review was the recent progress in the use of plant-based polymers and particles for the stabilization of Pickering and non-Pickering emulsion systems. Due to their availability and promising performance, it was discussed how the source, modification, and formulation of cellulose, starch, protein, and lignin-based polymers and particles would impact their emulsion stabilization. Special attention was given toward the material synthesis in two forms of polymeric surfactants and particles and the corresponding formulated emulsions. Also, the effects of particle size, degree of aggregation, wettability, degree of substitution, and electrical charge in stabilizing oil/water systems and micro- and macro-structures of oil droplets were discussed. The wide range of applications using such plant-based stabilizers in different technologies as well as their challenge and future perspectives were described.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".