Highly Efficient and Robust Platinum Nanocluster Catalyst Mediated by Polyamine Amidine‐Decorated Mesoporous Polymer Beads
Bibliographic record
Abstract
Abstract Platinum nanoclusters (PtNCs) are promising in catalysis due to their large specific surface area and unique physicochemical properties. Here, ultrasmall and uniform PtNCs are facilely synthesized with the mediation of amidine‐functionalized polyamines patched on mesoporous poly(divinylbenzene‐4‐vinylbenzyl chloride) beads. When each ligand patch has 14 amidines, ultrafine PtNCs (with the size as low as 1.1±0.1 nm) are formed as a result of several factors: deprotonated amidines (carbenes) strongly passivate on Pt atoms, amidines act as co‐stabilizers along with weak polyamine ligands, and PtNCs are confined to discrete ligand patches. When one ligand patch contains 9.3 amidines, the resulting PtNCs (1.7±0.3 nm) reach the highest turnover frequency of 536 h−1 for the catalytic reduction of 4‐nitrophenol in a batch reaction. This catalyst remains rather stable in a continuous flow test as a 4‐nitrophenol conversion of over 95 % is still achieved after running consecutively for 10 h.
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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".