Unactivated Pd-catalyzed oxidative cross-coupling reactions of arenes with benzene: a theoretical and experimental study
Bibliographic record
Abstract
Oxidative C–H bond activated palladium-catalyzed aromatic cross-coupling reactions offer advantages of fewer required synthetic steps but disadvantages of loss of inherent regioselectivity and selectivity. In one proposed catalytic cycle, each arene adds to a palladium carboxylate catalyst according to a concerted metalation deprotonation mechanism, followed by reductive elimination to couple the arenes and the replenishment of the catalyst by an oxidant. Using this proposed mechanism, molecular structures and free energy profiles were calculated for coupling of benzene with a range of heteroarenes containing various substituents and with several Pd-carboxylate catalysts. Reaction kinetics were analysed using the energetic span model, predicting turnover frequencies (TOFs) of heterocoupling (HB and BH) and homocoupling (HH and BB) pathways and assessing degrees of turnover frequency control (XTOFs). More electron-withdrawing carboxylate ligands and more electron-donating heteroarene substituents decrease activation and reaction free energies of addition steps, with C-2 more favourable than C-3. When heteroarene and catalyst choice are particularly favourable, the first association can become exergonic, causing a significant change in catalytic kinetics. When not exergonic, free energy for addition of benzene is almost always higher, leading to large energetic spans and slower TOFs (BB < HB < BH < HH). Non-exergonic pathways are also faster with more electron-withdrawing ligands and more electron-donating heteroarene substituents because of lower energy addition steps and a smaller energetic span. For exergonic associations, the low-energy arene–catalyst intermediate creates a larger energetic span, slowing down the HH and HB pathways. More electron-withdrawing ligands and more electron-donating substituents increase the relative TOF for BH, and the reaction requires only small excesses of benzene to induce heterocoupling.
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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 | 0.000 | 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) | 0.003 | 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".