Pickering Emulsion Templated Layer-by-Layer Assembly for Making Microcapsules
Bibliographic record
Abstract
Pickering emulsions stabilized by poly(sodium styrenesulfonate) (PSS) surface-modified LUDOX CL particles were used as templates for the layer-by-layer (LbL) deposition of polyelectrolytes and charged nanoparticles to form composite shells. The microcapsules resulting from repeated LbL coating with poly(diallyldimethylammonium chloride) (PDADMAC) and PSS had porous walls due to the loose arrangement of the original nanoparticle aggregates at the oil-water interface, leading to significant microcapsule rupture and low encapsulation efficiency. Microcapsules formed by coating with PDADMAC and anionic LUDOX HS nanoparticles led to dense walls and stronger microcapsules, suitable for microencapsulation of hydrophobic materials with a wide range of polarities.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".