Characterization of Ethylene/α‐Olefin Copolymers Using High‐Temperature Thermal Gradient Interaction Chromatography
Bibliographic record
Abstract
Several crystallization‐based techniques are used to measure the chemical‐composition distribution of polyolefins, but they are limited to semicrystalline polyolefins. Recently, high‐temperature thermal gradient interaction chromatography (HT‐TGIC) has been developed to quantify the chemical‐composition distribution of semicrystalline and amorphous polyolefins, thus broadening the range of techniques available for the analysis of polyolefin chemical‐composition distribution. In HT‐TGIC, the fractionation mechanism relies on the interaction of polyolefin chains with a graphite surface upon temperature change in an isocratic solvent. In the present investigation, a series of ethylene/1‐octene copolymers having approximately the same molecular weight average and different comonomer fractions (up to 25% of 1‐octene) is synthesized using a metallocene catalyst to investigate the fractionation mechanism of HT‐TGIC. Three copolymer samples and their blends are also studied to determine which operation parameters influence the HT‐TGIC peak shape and position. The cooling rate has no significant effect on the desorption temperature and the broadness of the HT‐TGIC chromatograms. On the other hand, the heating rate and the elution flow rate substantially influence the peak temperature and breadth. image
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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".