Temperature-Dependent Effects of Alkyl Substitution on Diarylamine Antioxidant Reactivity
Bibliographic record
Abstract
Alkylated diphenylamines are among the most efficacious radical-trapping antioxidants (RTAs) for applications at elevated temperatures since they are able to trap multiple radical equivalents due to catalytic cycles involving persistent diphenylnitroxide and diphenylaminyl radical intermediates. We have previously shown that some heterocyclic diarylamine RTAs possess markedly greater efficacy than typical alkylated diphenylamines, and herein, report on our efforts to identify optimal alkyl substitution of the scaffold, which we had found to be the ideal compromise between reactivity and stability. Interestingly, the structure–activity relationships differ dramatically with temperature: para -alkyl substitution slightly increased reactivity and stoichiometry at 37 and 100 °C due to more favorable (stereo)electronic effects and corresponding diarylaminyl/diarylnitroxide formation, while ortho -alkyl substitution slightly decreased both reactivity and stoichiometry. No such trends were evident at 160 °C; instead, the compounds were segregated into two groups based on the presence/absence of benzylic C–H bonds. Electron spin resonance spectroscopy indicates that increased efficacy was associated with lesser diarylnitroxide formation, and deuterium-labeling suggests that this is due to abstraction of the benzylic H atom, precluding nitroxide formation. Computations predict that this reaction path is competitive with established fates of the diarylaminyl radical, thereby minimizing the formation of off-cycle products and leading to significant gains in high-temperature RTA efficacy.
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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) | 0.002 | 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".