Alkali‐Metal Ion Catalysis and Inhibition in S<sub>N</sub>Ar Displacement: Relative Stabilization of Ground State and Transition State Determines Catalysis and Inhibition in S<sub>N</sub>Ar Reactivity
Bibliographic record
Abstract
Abstract We report here the first observation of alkali‐metal ion catalysis and inhibition in SNAr reactions. The plot of kobsd versus [alkali‐metal ethoxide] exhibits downward curvature for the reactions of 1‐(4‐nitrophenoxy)‐2,4‐dinitrobenzene with EtOLi, EtONa, and EtOK, but upward curvature for the corresponding reaction with EtOK in the presence of 18‐crown‐6‐ether (18C6). Dissection of kobsd into the second‐order rate constants for the reactions with the dissociated EtO− and the ion‐paired EtOM (i.e., k and kEtOM, respectively) has revealed that the reactivity increases in the order EtOLi − +, Na+, and K+ ions but is catalyzed by 18C6 K+ ion. The reactions of 1‐(Y‐substituted‐phenoxy)‐2,4‐dinitrobenzenes have been proposed to proceed through a stepwise mechanism, in which expulsion of the leaving group occurs after the rate‐determining step based on the kinetic result that σo constants exhibit a much better Hammett correlation than σ− constants. Alkali‐metal ion catalysis or inhibition has been discussed in terms of differential stabilization of ground‐state and transition‐state complexes through a qualitative energy profile. A π‐complexed transition‐state structure is proposed to account for the kinetic results.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".