<scp>ARGET ATRP</scp> of ethylene glycol dicyclopentenyl ether methacrylate with vegetable oil and terpene‐derived methacrylic monomers
Bibliographic record
Abstract
Abstract Homo and statistical copolymerization reactions of ethylene glycol dicyclopentenyl ether methacrylate (EGDEMA) and a vegetable‐oil based methacrylic ester C13MA (average alkyl chain length = 13) are studied via activator regenerated electron transfer polymerization (ARGET ATRP) using only trace amounts of copper catalyst. Poly(EGDEMA) and poly(C13MA) homopolymers and statistical poly(EGDEMA‐stat‐C13MA) copolymers are cleanly synthesized with monomodal molecular weight distribution and dispersities Đ = Mw/Mn = 1.39–1.76 and Mn ~ 12 kg/mol. Chain end fidelity is confirmed by chain extension from poly(C13MA) macroinitiator with EGDEMA to make poly(C13MA‐b‐EGDEMA) diblock copolymers, which exhibit two distinct glass transition temperatures (Tgs), one for the poly(C13MA) block (−39°C) and the other for the poly(EGDEMA) block (23.9°C), suggesting microphase separation. Due to the relatively low Tg of poly(EGDEMA‐stat‐C13MA), terpene‐derived isobornyl methacrylate (IBOMA) is copolymerized with EGDEMA forming poly(EGDEMA‐stat‐IBOMA) statistical copolymers with Tgs ranging from 22.9–113°C. Additionally, crosslinking of the poly(EGDEMA) homopolymer and poly(EGDEMA‐stat‐C13MA) and poly(EGDEMA‐stat‐IBOMA) copolymers is achieved by UV thiol‐ene clicking of the pendent double bonds of EGDEMA units with suitable dithiols at 365 nm. For poly(EGDEMA), conversion of the thiol‐ene click reaction reaches 70%; where as the conversion of the clicking reactions is higher in the copolymers with a conversion up to 92% for poly(EGDEMA‐stat‐C13MA) and 97% for poly(EGDEMA‐stat‐IBOMA).
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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) | 0.002 | 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".