Rutile TiO <sub>2</sub> Confined Atomic Palladium Species Boosts C−C Coupling Efficiency in Sonogashira Coupling Reactions
Bibliographic record
Abstract
Abstract Developing high‐performance Pd‐based catalysts with ultra‐low Pd loading is essential but challenging for the multi‐step Sonogashira coupling reactions. Structure–function relationships for single atom catalysts (SACs) are highly dependent on the coordination environments of active sites on appropriate supports. Herein, a facile strategy consisting of crystal phase engineering and thermal atomization to access a Pd‐based SAC with 0.35 wt% Pd loading (Pd 1 /TiO 2‐ x ) is reported. The resulting material consists of spatially isolated Pd atoms decorated on rutile TiO 2 (a support that is frequently overlooked in catalyst design). The use of this Pd catalyst in the Sonogashira C−C coupling of iodobenzene and phenylacetylene to diphenylacetylene achieves distinguished catalytic efficacy, rendering a high yield of 98% and a turnover frequency (TOF) of 23 809 h −1 , which is comparable to similar state‐of‐the‐art catalysts. Mechanistic investigations disclose that this strategy promotes interfacial electron transfer between the metal and support, endowing a unique electronic structure and ensuring electronic metal–support coupling effects in Pd 1 /TiO 2‐ x . This significantly affects the adsorption/activation of reactants and the desorption of intermediates/products, thereby strongly boosting the coupling efficiency. These findings highlight the great importance of catalyst design for multi‐step coupling 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".