Bimetallic dendrimer-encapsulated nanoparticles as catalysts: a review of the research advances
Bibliographic record
Abstract
Bimetallic dendrimer-encapsulated nanoparticles (DENs) are important materials, because they have demonstrated improvement in performance compared to the monometallic DENs in many systems when they are used as catalysts. This tutorial review focuses on the recent research advances in bimetallic DENs with respect to their synthesis, characterization, and applications as catalysts. Bimetallic DENs can be made mainly via three routes: co-complexation, sequential loading, and partial displacement. The research in bimetallic DENs has been significantly promoted by the advancement of characterization instruments. The performances of bimetallic DENs as homogeneous and heterogeneous catalysts in organic synthesis have been compared with both monometallic DENs and their physical mixtures. It is concluded that the synergistic electronic effect in bimetallic nanoparticles enhances their catalytic activities.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".