Synthesis and mechanical properties of diimide‐hydrogenated natural rubber vulcanizates
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Hydrogenated natural rubber (HNR), providing an ethylene–propylene alternating copolymer, was prepared by the chemical modification of natural rubber latex (NRL) using diimide generated from hydrazine (N 2 H 4 ) and hydrogen peroxide (H 2 O 2 ), with copper sulfate (CuSO 4 ) as catalyst. 1 H‐NMR analysis indicated that 48% hydrogenation was performed with a mole ratio of N 2 H 4 /double bonds = 4 and H 2 O 2 /N 2 H 4 = 1.5 at 50°C for 7 h. The obtained HNR was subjected to a sulfur cure by using a conventional milling process. The cure characteristics, mechanical properties before and after heat aging, and abrasion and ozone resistances of HNR vulcanizate were examined and compared with those of natural rubber (NR), ethylene propylene diene terpolymer (EPDM) and 50 : 50 NR/EPDM vulcanizates. The results indicated that the cure rate of 48% HNR showed no significant change when compare to both NR and 50 : 50 NR/EPDM blends, and offered a better processing advantage over EPDM. The mechanical properties and abrasion resistance of a 48% HNR vulcanizate were comparable to those of a NR vulcanizate. Additionally, its heat and ozone resistances were better than those of NR vulcanizate, due to a reduction in the amount of double bonds in the backbone chain. Thus, hydrogenation of NR can lead to a type of rubber that has improved heat and ozone resistances while still maintaining its good mechanical properties. Consequently, it improves the properties of NR for a wide range of applications. © 2009 Wiley Periodicals, Inc. J Appl Polym Sci, 2009
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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 it