Evolution of Molecular Weight and Long Chain Branch Distributions in Olefin–Diene Copolymerization
Bibliographic record
Abstract
Abstract A model for olefin–diene copolymerization and long chain branch formation was developed. The model shows that the number‐average molecular weight and branching density increases linearly with time in a semi‐batch polymerization, while the polydispersity depends on the diene content in the polymer and on the polymerization time. For low diene fractions or low polymerization times, the polydispersity increases linearly with time. For higher diene contents, the polydispersity increases exponentially with polymerization time after a critical polymer concentration is reached. The calculated distributions of branched species indicate that diene content influences the amount of highly branched chains produced in the polymerization, markedly broadening the distribution of molecular weight and leading to gel formation. Weight distribution of branched species after 30 min of polymerization. magnified image Weight distribution of branched species after 30 min of polymerization.
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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) | 0.001 | 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".