Molecular Weight and Long Chain Branch Distributions of Branch‐Block Olefinic Thermoplastic Elastomers
Bibliographic record
Abstract
Abstract Olefinic thermoplastic elastomers can be prepared by incorporating semi‐crystalline macromonomers (e.g. isotactic or syndiotactic poly(propylene), high‐density polyethylene) onto amorphous backbones (e.g. atactic poly(propylene), ethylene/α‐olefin copolymers). The macromonomer incorporation reaction can be carried out in semi‐batch reactors by adding previously synthesized macromonomers to the reactor (ex situ approach), or by generating and incorporating the macromonomers in a single step (in situ approach). The differences in the microstructure of copolymers synthesized by in situ and ex situ techniques are explored herein through a mathematical model that can predict the concentration of linear and branched chains, their average molecular weights, polydispersity indices, and molecular weight distributions. In both cases linear chains predominate, but the ex situ approach produces a larger amount of branched chains with thermoplastic elastomer properties. Furthermore, for the in situ strategy, a significant amount of branched chains is only formed after the macromonomer concentration reaches a critical value. Schematic representation of the polymerization mechanism. image Schematic representation of the polymerization mechanism.
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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".