Morphology and Properties of Hydrogenated Nitrile Rubber/Poly Hydroxyl Zinc Monomethacrylate Composites by Curing with Peroxide
Bibliographic record
Abstract
The morphology evolution of hydroxyl zinc monomethacrylate (HZMMA) in hydrogenated nitrile rubber (HNBR) during its formation, and effect of synergistic behavior of HZMMA and carbon black (CB) in HNBR on its properties, were investigated. Fourier transform infrared spectroscopy (FTIR), differential scanning calorimetry (DSC), transmission electron microscopy (TEM) and X-ray diffraction (XRD) were used to probe the reaction of in-situ polymerized HZMMA. The results showed that an ionic polymer interpenetrating HNBR, due to homo-polymerization or graft polymerization of HZMMA solid monomer occurred, and poly-HZMMA particles, confirmed by FTIR and TEM, were formed during the HNBR vulcanization process. This kind of morphology for the HNBR composites played a very significant role in the HNBR reinforcement. At ambient temperature, the mechanical properties of HNBR composite filled with pure PHZMMA was much superior to those of the HNBR/PHZMMA/CB composites; however, when the temperature was increased to above 50°C, the decrease of the tensile strength for the latter was slower, and the tensile strength was always higher than that of the HNBR composites reinforced with pure PHZMMA at the same temperature. The elongation at break above 80°C was also always higher than that of the HNBR/PHZMMA sample. The HNBR/PHZMMA/CB composites showed excellent air oven aging resistance.
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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".