Different Effect of Two Commonly Used Stearate Acid Scavengers on Polypropylene Crystallization Promotion Performance of a Sorbitol-Type Nucleating Agent
Bibliographic record
Abstract
For Zieglar–Natta (Z–N) polypropylene (PP) to which a nucleating agent (NA) was added to regulate the properties, selecting an appropriate acid scavenger, a necessary additive for Z–N PP, is important for optimizing the effectiveness of the NA. However, the impact of various acid scavengers on the performance of NAs has not been systematically studied. In this work, the effect of two most widely used acid scavengers, calcium stearate (CaSt 2 ) and zinc stearate (ZnSt 2 ), on PP crystallization promotion performance of a commonly used NAs, NX8000 (a typical representative of sorbitol-type NAs family) was systematically investigated. It was found that CaSt 2 did not significantly alter the crystallization temperature ( T c ) of PP containing NX8000, while ZnSt 2 was detrimental to the nucleation benefit of NX8000, especially in the NA concentration range, where effective nucleation began but remained below the “critical saturation concentration”. The mechanism study showed that CaSt 2 added to PP almost remains chemically unchanged during heating and exhibits no significant impact on the NA. Differently, ZnSt 2 undergoes chemical reactions in a matrix at elevated temperature, producing stearic anhydride, which reacts with NX8000. As a result, a portion of the NA is consumed, leading to a reduction in its efficacy. Our work not only contributes to a comprehensive understanding of mechanisms when multiple additives are used simultaneously but also helps optimize additive formulations to maximize the performance of each component.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| 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".