Determination of Intramolecular Chain Transfer and Midchain Radical Propagation Rate Coefficients for Butyl Acrylate by Pulsed Laser Polymerization
Bibliographic record
Abstract
A novel method to extract individual free-radical polymerization rate coefficients for butyl acrylate intramolecular chain transfer (backbiting), k bb, and for monomer addition to the resulting midchain radical,, is presented. The approach for measuring k bb does not require knowledge of any other rate coefficient. Only the dispersion parameter of SEC broadening has to be determined by fitting measured MWDs or should be available from separate experiments. The method is based upon analysis of the shift in the position of the inflection point of polymer molecular weight distributions produced by a series of pulsed-laser polymerization (PLP) experiments with varying laser pulse repetition rate. The coefficient k bb is determined from the onset of the sharp decrease of the apparent propagation rate coefficient ( ) with decreasing repetition rate, an approach verified by simulation. With experiments performed between −10 and +30 °C, the estimated values are fitted well by an Arrhenius relation with pre-exponential factor A ( k bb ) = (4.84 ± 0.29) × 10 7 s -1 and activation energy E a ( k bb ) = (31.7 ± 2.5) kJ·mol -1 . At low pulse repetition rates, the experimental values are related to an averaged propagation rate coefficient,, that is dependent on the relative population of chain-end and midchain radicals. Evaluated by comparing simulated and experimental molecular weight distributions, provides an estimate for . The Arrhenius parameters are: A ( ) = (1.52 ± 0.14) × 10 6 L·mol -1 ·s -1 and E a ( ) = (28.9 ± 3.2) kJ·mol -1 .
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".