Innovative and high performance synthesis of microcapsules containing methyl anthranilate by microsuspension iodine transfer polymerization
Bibliographic record
Abstract
Abstract In this research, preparations of polymer microcapsule encapsulated methyl anthranilate (MA) as an essential oil model by both microsuspension conventional radical polymerization (ms CRP) and microsuspension iodine transfer polymerization (ms ITP) using methyl methacrylate (MMA) and ethylene glycol dimethacrylate (EGDMA) copolymer as the polymer shell were studied. In the case of ms CRP, a large amount of free polymer particles nucleated in aqueous medium were obtained. Using ms ITP, the free polymer particle formation was significantly depressed. Iodoform (CHI3) as a chain transfer agent with 0.8 wt% relative to the monomer, such a phenomenon was not observed. Various emulsifiers (oleic acid, Span 80 and PEG 30 dipolyhydroxystearate (DPHS)) with low hydrophile–lipophile balance value were used to retain MA in the monomer droplets or polymerizing particles. DPHS is the most effective emulsifier to retain MA in microcapsules giving 58% encapsulation at 20 wt% of DPHS relative to MA. In addition, from the controlled release study, only 55 wt% of the encapsulated MA was released by 90 days. Polymer microcapsule encapsulated MA using an MMA‐EGDMA copolymer shell with a high percentage of encapsulation and without free polymer particles was successfully prepared for the first time. Based on slow release of the encapsulated MA, the prepared microcapsules could be used in various applications. © 2017 Society of Chemical Industry
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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) | 0.000 | 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 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".