Evaluation of Organically Modified Layered Double Hydroxides as Fillers for the Preparation of Polymer Nanocomposites in Miniemulsion Polymerization
Bibliographic record
Abstract
Abstract Latexes of poly(n‐butyl acrylate‐co‐methyl methacrylate) [P(BA‐co‐MMA)] filled with magnesium–aluminum layered double hydroxides (MgAl‐LDHs) are synthesized using miniemulsion polymerization. Three commercial LDHs organically modified with different types of anions are used as fillers (Perkalite F100S, Perkalite A100, and Perkalite AF50) and three different types of surfactants are tested to stabilize the miniemulsions including a cationic, an anionic, and a nonionic one. Stable LDH‐containing miniemulsions are prepared with a mixture of sodium dodecyl sulfate and Triton X‐405 and the polymerizable co‐stabilizer octadecyl acrylate. They are then polymerized to yield nanocomposite latexes. Depending on the type of LDH used, the presence of the inorganic material in the reaction medium affects the polymerization kinetics. X‐ray diffraction analysis of the resulting nanocomposite films suggests exfoliation of the inorganic material. The glass transition temperature of the nanocomposites is not affected by the LDHs and the decomposition temperature of the nanocomposites determined by thermogravimetric analysis is greater than that of the pure polymer.
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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".