Preparation of a natural rubber core/polymer shell in a nanomatrix by graft copolymerization
Bibliographic record
Abstract
Abstract The grafting of a vinyl monomer, methyl methacrylate (MMA) or styrene (ST), onto a natural rubber (NR) exhibited a core–shell structure, with NR as the core and poly(methyl methacrylate) or polystyrene as the shell. The grafting efficiency (GE) of the graft copolymer was determined by a solvent‐extraction technique. The synthesized graft copolymer was purified and then characterized by Fourier transform infrared spectroscopy analysis. The effects of the graft parameters, including time, initiator content, and concentration, and the type of monomer, MMA or ST, were investigated. A longer time was favorable for the graft copolymerization. GE first increased and then decreased with increasing concentration of initiator. GE decreased with increasing monomer content, and it was confirmed that the graft copolymerization was a surface‐controlled process. The grafting ST monomer had a higher GE compared to MMA under the same conditions. The characterization of the particles by transmission electron microscopy and scanning electron microscopy confirmed the formation of a core–shell structure. From the micrographs, we inferred that at 71% GE, the NR seed particle had a complete closed shell several nanometers in thickness. Therefore, the NR particle was dispersed in a polymer nanomatrix. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008
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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 | 0.001 |
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".