Quantifying Extrusion Modification of LDPE with a Microcompounder
Bibliographic record
Abstract
Abstract Processibility of LDPE is known to be sensitive to processing history. Significant changes in processibility and product properties can occur through repeated extrusion without detectable changes in molecular weight and molecular weight distribution. Such changes of LDPE rheology are simulated with DSM micro-compounder and characterized with the small angle oscillatory tests and the SER uni-axial extensional flow with a K-BKZ analysis. Both the linear and the nonlinear rheology data suggest the major mechanism in the extrusion with the DSM micro-compounder is the reduction of the effects of long chain branching. The linear rheology analysis, along with GPC and NMR characterization confirms that the changes in the extrusion are not due to chemical crosslinking, though an increase in backbone molecular weight at extreme conditions is perceivable through the minor increase in molecular weight distribution, the increase in zero-shear viscosity and the decrease of melt index. The extensional rheology results, on the other hand, reveal the depression of the strain hardening with prolonged extrusion at 190 degree C or higher extrusion temperature. The stress growth data were evaluated with a K-BKZ constitutive with exponential damping function. The depression of strain hardening is well characterized with the strain hardening factor and the non-linear exponent beta as function of the extrusion conditions. The damping factor β is observed to be especially effective as the parameter to follow the depression of the strain hardening due to microcompounder extrusion. The microcompounder extrusion and the SER analysis with the K-BKZ analysis prove to be a new useful tool for simulating the shear modification of the LDPE.
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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".