Gas-Phase Mechanisms of the Reactions of Reduced Organic Nitrogen Compounds with OH Radicals
Bibliographic record
Abstract
Research on the fate of reduced organic nitrogen compounds in the atmosphere has gained momentum since the identification of their crucial role in particle nucleation and the scale up of carbon capture and storage technology which employs amine-based solvents. Reduced organic nitrogen compounds have strikingly different lifetimes against OH radicals, from hours for amines to days for amides to years for isocyanates, highlighting unique functional group reactivity. In this work, we use ab initio methods to investigate the gas-phase mechanisms governing the reactions of amines, amides, isocyanates and carbamates with OH radicals. We determine that N-H abstraction is only a viable mechanistic pathway for amines and we identify a reactive pathway in amides, the formyl C-H abstraction, not currently considered in structure-activity relationship (SAR) models. We then use our acquired mechanistic knowledge and tabulated literature experimental rate coefficients to calculate SAR factors for reduced organic nitrogen compounds. These proposed SAR factors are an improvement over existing SAR models because they predict the experimental rate coefficients of amines, amides, isocyanates, isothiocyanates, carbamates and thiocarbamates with OH radicals within a factor of 2, but more importantly because they are based on a sound fundamental mechanistic understanding of their reactivity.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".