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
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 EtO - and kEtOM , respectively) has revealed that the reactivity increases in the order EtOLi<EtONa<EtOK<EtO(-)<EtOK/18C6. This indicates that the reaction is inhibited by Li(+), 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 σ(o) 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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 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".