THE EFFECT OF ACRYLONITRILE CONTENT ON THE THERMO-OXIDATIVE AGING OF NITRILE RUBBER
Bibliographic record
Abstract
ABSTRACT The level of thermo-oxidative degradation in a series of unstabilized and unfilled nitrile rubbers (NBR) varying in acrylonitrile (ACN) content (18–43.5 wt%) was investigated on heat-aged samples (40–120 °C) by Attenuated Total Reflectance–Fourier Transform Infrared (ATR-FTIR) spectroscopy. A similar degradation profile evolution was observed regardless of ACN content with the generation of hydroxyl-, carbonyl-, and ester-based products with a concomitant loss of the 1,4-trans, 1,4-cis, and 1,2-vinyl butadienes. The magnitude of IR active group absorption loss is greatest in the lowest ACN NBR concentration and steadily lessens toward higher ACN levels (1,4-cis > 1,2-vinyl > 1,4-trans >> butadiene methylenes). The 18% ACN NBR possesses two distinct kinetically different degradation regimes (80–120 and 40–80 °C). Activation energies by carbonyl growth and 1,4-trans loss increase from 71 to 87 kJ mol−1 and from 71 to 79 kJ mol−1 respectively, for decreasing ACN (43.5–18%) content. The rate of consumption of the 1,4-trans butadiene group is mainly affected by thermo-oxidative carbonyl-based and addition-cross-linking reactions, the latter being lower in activation energy for low to mid ACN NBRs. The high oxidation rate behavior of the lowest acrylonitrile rubber is attributed to its higher oxygen permeability rates. Cross-linking due to addition-type reactions is favored for higher 1,4 unsaturation levels.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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".