Boron nitride and fluoropolymer combinations: Interactions and their performance as processing aids
Bibliographic record
Abstract
Abstract In this work, we studied the adsorption capacity of boron nitride (BN) for fluoropolymer and polyethylene (PE) to gain a better understanding of the interactions and the performance of BN and fluoropolymer, and their combinations as processing aids in the extrusion of Ziegler‐Natta PEs. We found that BN has a relatively high adsorption capacity for both PE and fluoropolymer. As a result, simultaneous compounding of BN and fluoropolymer into the host polymer causes fluoropolymer to be trapped within the bulk of the polymer, and prevents the fluoropolymer particles from coating the die wall during flow. This limits the effectiveness of fluoropolymer and BN as processing aids. To avoid this interaction, we added fluoropolymer separately in a dry form just prior to extrusion. In this case, the synergistic effect of BN and fluoropolymer as a combination processing aid was evident. POLYM. ENG. SCI., 45:669–677, 2005. © 2005 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".