Analysis of the Palladium-Catalyzed (Aromatic)C–H Bond Metalation–Deprotonation Mechanism Spanning the Entire Spectrum of Arenes
Bibliographic record
Abstract
A comprehensive understanding of the C-H bond cleavage step by the concerted metalation-deprotonation (CMD) pathway is important in further development of cross-coupling reactions using different catalysts. Distortion-interaction analysis of the C-H bond cleavage over a wide range of (hetero)aromatics has been performed in an attempt to quantify the various contributions to the CMD transition state (TS). The (hetero)aromatics evaluated were divided in different categories to allow an easier understanding of their reactivity and to quantify activation characteristics of different arene substituents. The CMD pathway to the C-H bond cleavage for different classes of arenes is also presented, including the formation of pre-CMD intermediates and the analysis of bonding interactions in TS structures. The effects of remote C2 substituents on the reactivity of thiophenes were evaluated computationally and were corroborated experimentally with competition studies. We show that nucleophilicity of thiophenes, evaluated by Hammett σ(p) parameters, correlates with each of the distortion-interaction parameters. In the final part of this manuscript, we set the initial equations that can assist in the development of predictive guidelines for the functionalization of C-H bonds catalyzed by transition metal catalysts.
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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".