Effect of long chain branching on nonisothermal crystallization behavior of polyethylenes synthesized with constrained geometry catalyst
Bibliographic record
Abstract
Abstract Nonisothermal crystallization behavior of linear and long chain branched (LCB) polyethylene (PE) samples having similar molecular weight but different long‐chain branching densities (LCBD) up to 0.44 C per 1000 carbons was investigated using differential scanning calorimetry (DSC) at various scanning rates. The LCB PE samples were prepared in our high‐temperature, high‐pressure continuous stirred‐tank reactor (CSTR) system using the constrained geometry catalyst. The existence of LCB was found to affect the PE crystallization behavior considerably. The enthalpy of crystallization and the ultimate degree of crystallinity decreased with the increase of LCBD. At the relatively low cooling rates, the small amount of LCB promoted nucleation but restrained chain movement and reduced the crystal growth rate. There was ∼ 17% of crystallinity generated from a secondary crystallization. The energy barrier became significant with the LCB structure, resulting in chain diffusion limitations and lower LCB PEs overall crystallization rates than their linear counterpart. POLYM. ENG. SCI., 2012. © 2011 Society of Plastics Engineers
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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 | 0.001 |
| 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".