Copolymers of 3,5‐dimethylphenyl acrylate and methyl methacrylate: synthesis, characterization and determination of monomer reactivity ratios
Bibliographic record
Abstract
Abstract Copolymers of 3,5‐dimethylphenyl acrylate (DMPA) and methyl methacrylate (MMA) having various compositions were synthesized using free radical solution polymerization in butane‐2‐one at 70 ± 1 °C with benzoyl peroxide as initiator. The structure of the copolymer was confirmed by FTIR, 1H NMR and 13C NMR spectroscopic techniques. The polydispersity indices of the copolymers determined using gel permeation chromatography suggest that the chain termination by disproportion was predominant when the mole fraction of MMA in the feed is high and radical recombination was predominant when the mole fraction of DMPA was high in the feed. The glass transition temperature of the copolymer increases with increase in MMA content. The thermal stability of the copolymers increases with increase in DMPA content. The copolymer compositions were determined using 1H NMR analysis. The monomer reactivity ratios were determined by application of conventional linearization methods such as the Fineman–Ross (r1 = 0.3942; r2 = 2.3250), the Kelen–Tüdös (r1 = 0.3848; r2 = 2.2584), an extended Kelen–Tüdös (r1 = 0.3608; r2 = 2.3384) and a non‐linear error‐in‐variables model method using a computer program, RREVM (r1 = 0.3879; r2 = 2.2642). These values suggest that MMA is more reactive than DMPA and the copolymer will be richer in MMA units. Copyright © 2003 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 | 0.001 | 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".