Influence of Intermolecular Interactions on Acrylate–Methacrylate Copolymerization Reactivity Ratios: From Bulk to Aqueous Solution
Bibliographic record
Abstract
The influence of both monomer concentration (1 wt % to bulk) and solvent polarity (ethanol/water mixtures varying from pure ethanol to pure water) on copolymer composition is systematically investigated for the copolymerizations of methyl acrylate (MA) with di(ethylene glycol) methyl ether methacrylate (DEGMEMA), methacrylic acid (MAA), and methyl methacrylate (MMA), as well as for acrylic acid (AA) with DEGMEMA. Nonlinear parameter estimation techniques are employed to estimate system reactivity ratios from in situ nuclear magnetic resonance spectroscopy measurements of comonomer composition drift followed to high conversions as well as from copolymer compositions measured for low-conversion samples produced by pulsed-laser polymerization. The study demonstrates that the reactivity ratios needed to describe copolymerization in polymer particles can differ substantially from those required to accurately represent aqueous-phase reactions in emulsion copolymerization. However, acrylate–methacrylate compositions in aqueous solution are effectively described using a single set of reactivity ratios ( r acrylate = 0.18 ± 0.02 and r methacrylate = 4.40 ± 0.30), independent of monomer functionality. The extensive data set provides additional important insights into the complex monomer–monomer, solvent–monomer, and solvent–solvent intermolecular interactions that control the copolymer composition in polar media.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 teacher head, 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".