Synthesis of bio‐based poly(methacrylates) using <scp>SG1</scp>‐containing amphiphilic macroinitiators by nitroxide mediated miniemulsion polymerization
Bibliographic record
Abstract
Abstract SG1‐based amphiphilic macroinitiators were synthesized from oligoethylene glycol methyl ether methacrylate and 10 mol% acrylonitrile or styrene (as the controlling comonomer) to conduct the nitroxide mediated polymerization of bio‐based methacrylic monomers (isobornyl methacrylate (IBOMA) and C13 alkyl methacrylate (C13MA)) in miniemulsion. The effect of the addition of surfactant (DOWFAX 8390), co‐stabilizer (n‐hexadecane) and different reaction temperatures (80, 90 and 100°C) on polymerization kinetics was studied. We found that the NMP of IBOMA/C13MA using amphiphilic macroalkoxyamines were most effective during miniemulsion polymerization (linear trend of Mn versus conversion and high latex stability) in presence of 2 wt% surfactant and 0.8 wt% co‐stabilizer (relative to monomer) at 90°C. The effect of surfactant, co‐stabilizer and temperature on particle size during the polymerization was studied and suggested a decrease in initial particle size with the addition of surfactant and co‐stabilizer. Finally, the thermal properties of IBOMA/C13MA polymers, prepared by amphiphilic macroinitiators, were examined thoroughly, indicating a Tg in the range of −44°C < Tg < 109°C.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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".