Probing the Thermal Stability of (3‐Mercaptopropyl)‐trimethoxysilane‐Protected Au<sub>25</sub> Clusters by In Situ Transmission Electron Microscopy
Bibliographic record
Abstract
Abstract High‐surface‐area gold catalysts are promising catalysts for a number of selective oxidation and reduction reactions but typically suffer catalyst deactivation at higher temperatures. The major reason for catalyst deactivation is sintering, which can be triggered via two mechanisms: particle migration and coalescence, and Ostwald ripening. Herein, a direct method to synthesize Au25 clusters stabilized with 3‐mercaptopropyltrimethoxysilane (MPTS) ligands is discussed. The sintering of Au25(MPTS)18 clusters on mesoporous silica (SBA‐15) is monitored by using an environmental in situ transmission electron microscopy (TEM) technique. Results show that agglomeration of smaller particles is accelerated by increased mobility of particles during heat treatment, while growth of immobile particles occurs via diffusion of atomic species from smaller particles. The mobility of the Au clusters can be alleviated by fabricating overlayers of silica around the clusters. The resulting materials show tremendous sinter‐resistance at temperatures up to 650 °C as shown by in situ TEM and extended X‐ray absorption fine structure analysis.
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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".