Revealing the Structure Evolution of Heterogeneous Pd Catalyst in Suzuki Reaction via the Identical Location Transmission Electron Microscopy
Bibliographic record
Abstract
The mechanism of palladium nanoparticles (Pd NPs)-catalyzed cross-coupling reactions has been the subject of intense debate since the recognition of catalytic active sites involving a wide array of dynamic changed Pd species. Here, through the combination of the hot filtration experiment together with the recently developed identical location transmission electron microscopy (IL-TEM) method, the delicate structure evolution of highly dispersed Pd NPs supported on oxygen-functionalized carbon nanotubes (Pd/oCNTs) as well as the kinetics properties of derived dissolved species in liquid phase were systemically investigated in the Suzuki-Miyaura reaction. The result indicates that the leached Pd components caused by the strong adsorption of reactants might have a significant contribution to the coupling products, and the degree for different substrates follows the order of iodobenzene > phenylboronic acid > bromobenzene. Meanwhile, the typical three sequential behaviors of supported Pd NPs, including dissolution, deposition, and growth, along with the increase of the conversion throughout the reaction were spatiotemporally observed by tracking the evolution of individually identifiable NPs. The performed work not only provides direct evidence for the interaction between Pd NPs surface with reactants on atomic scale but also gives a valuable reference for fundamentally understanding the mechanism of the heterogeneous Pd-catalyzed Suzuki coupling process as well as rational design of next-generation catalysts with high efficiency and reusability for synthetic applications.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".