The Catalytic Mechanism of Diarylamine Radical-Trapping Antioxidants
Bibliographic record
Abstract
Diarylamine radical-trapping antioxidants are important industrial additives, finding widespread use in petroleum-derived products. They are uniquely effective at elevated temperatures due to their ability to trap multiple radicals per molecule of diarylamine. Herein we report the results of computational and experimental studies designed to elucidate the mechanism of this remarkable activity. We find that the key step in the proposed catalytic cycle-decomposition of the alkoxyamine derived from capture of a substrate-derived alkyl radical with a diarylamine-derived nitroxide-proceeds by different mechanisms depending on the structure of both the substrate and the diarylamine. N,N-Diarylalkoxyamines derived from saturated substrates and diphenylamines decompose by N-O homolysis followed by disproportionation. Alternatively, those derived from unsaturated substrates and diphenylamines, or saturated substrates and N-phenyl-β-naphthylamine, decompose by an unprecedented concerted retro-carbonyl-ene reaction. The alkoxyamines that decompose by the concerted process inhibit hexadecane autoxidations at 160 °C to the same extent as the corresponding diarylamine, whereas those alkoxyamines that decompose by the N-O homolysis/disproportionation pathway are much less effective. This suggests that the competing cage escape of the alkoxyl radicals following N-O homolysis leads to significantly less effective regeneration of diarylamines and implies that the catalytic efficiency of diarylamine antioxidants is substrate-dependent. The results presented here have significant implications in the future design of antioxidant additives: diarylamines designed to yield intermediate alkoxyamines that undergo the retro-carbonyl-ene reaction are likely to be much more effective than existing compounds and will display catalytic radical-trapping activities at lower temperatures due to lower barriers to regeneration.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".