Morphology and mechanical properties of natural rubber and styrene‐grafted natural rubber latex compounds
Bibliographic record
Abstract
Abstract The mechanical properties of natural rubber latex (NRL) modified with styrene‐grafted natural rubber (styrene‐GNR) latex were investigated. Styrene‐GNR was first synthesized via emulsion copolymerization using cumene hydroperoxide/tetraethylene pentamine as an initiator. The styrene‐GNR latex produced was mixed with NRL with various latex compounding contents and then prevulcanization was carried out. The mechanical properties and heat, weathering, and ozone resistance of the natural rubber (NR) and styrene‐GNR latex compounds were investigated as a function of the grafted NR content. The results indicated that the tensile and tear strength were decreased, whereas Young's modulus and hardness were increased at high content of styrene‐GNR. Addition of styrene‐GNR improved the resistance of the compounds to heat and weathering ageing. The ozone resistance of the compound containing styrene‐GNR is superior to that of the NR‐rich compound. The results indicated that NR/styrene‐GNR latex compounds maintained good antiageing properties required for outdoor applications. The tensile fracture surface examined by scanning electron microscopy confirmed a shift from ductility failure to brittle with an increase of the styrene‐GNR content in the compounds. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008
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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".