Elucidation of the role of ZnO in sulfur cure in novel EPDM-CTS blends
Bibliographic record
Abstract
A new concept is introduced in this study, suggesting the role played by the ZnO crystal in sulfur crosslinking polymers, particularly, rubber blends of EPDM-CTS. The study is conducted in a polymer blend of ethylene propylene diene terpolymer (EPDM) and cyclic tetrasulfide (CTS). CTS is a reactive low molecular weight polymer, which can act as a sulfur donor. It is proposed that the sulfur crosslinking occurs at the surface of the ZnO crystals. A reaction site is created on the surface of the ZnO crystal by the reaction with stearic acid, which creates a “template” or active site on the surface as a catalytic site for the CTS reaction to take place. Various experiments are performed to substantiate the newly proposed role the crystalline ZnO structure plays in influencing the initiation of the sulfur crosslinking. The investigation is conducted in rubber compounds in the absence of fillers and other additives and additionally in chemical model studies. The analyses conducted in rubber compounds are performed on fully or partially cured rubber to study the evolution of the chemical process involved in the CTS reaction and the curing of the rubber blends. Step-cured compound allows analyses of the transformation of the ZnO crystal size during the sulfur crosslinking process, and the ability to gauge the step transformation that the ZnO crystal is undergoing during the crosslinking process. Additional chemical model studies are used in the study of the influence of the ZnO crystal on sulfur crosslinking, to confirm the reaction path and by-products of reaction. Lastly, quantum mechanical (QM) and molecular mechanics (MM) calculations are applied in support of the suggested mechanism of reaction.
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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 | 0.000 |
| 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) | 0.001 | 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".