Water and hydroxide ion pathways in the σ-complexation of superelectrophilic 2-aryl-4,6-dinitrobenzotriazole 1-oxides in aqueous solution. A kinetic and thermodynamic study
Bibliographic record
Abstract
As part of our continuing studies of the highly electron-deficient nature of nitrobenzofuroxans, nitrobenzofurazans and related heterocycles, we report here a kinetic and thermodynamic study of σ-complexation for a series of 2-aryl-4,6 -dinitrobenzotriazole 1-oxides (3a–e) over a large pH range in aqueous solution. The reaction series represents a modulation in electrophilic properties of the benzotriazole moiety in formation of the corresponding hydroxy σ-adducts (4a–e). Analysis of the data has allowed dissection of observed rates into forward (kH2O1, kOH−2) and reverse (kH+−1, k−2) rate constants as well as the obtention of pKa values for H2O addition to the benzotriazole moiety. Our results reveal that 3a–e are superelectrophilic compounds with respect to 1,3,5-trinitrobenzene (TNB) as a standard electron-deficient aromatic, but less superelectrophilic compared to 4,6-dinitrobenzofuroxan (DNBF). Some data pertaining to buffer catalysis of the formation and decomposition of the adducts together with solvent deuterium isotope effects for these pathways are also reported. From these results, it is concluded that adduct formation occurs via general base catalyzed water attack: the general bases include notably H2O, HCO3−, CO32− as well as OH−. This contrasts with the situation for the σ-complexation of DNBF where HCO3− and CO32− were found to act as nucleophilic catalysts whereas OH− functioned as a general base catalyst. This contrasting behaviour provides further evidence that the dinitro-activated carbocyclic ring of the benzotriazoles 3a–e ranks somewhat lower in electrophilic/superelectrophilic properties compared to that in DNBF. Altogether, the results provide a basis for understanding the relationship between the superelectrophilic reactivities, as evidenced by the contrasting kinetic and thermodynamic properties of the systems at hand, and the varied abilities of these substrates to react in pericyclic Diels–Alder reactions.
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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) | 0.001 | 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".