Ultrathin Atomic Layer Deposited Al<sub>2</sub>O<sub>3</sub> Overcoat Stabilizes Al<sub>2</sub>O<sub>3</sub>-Pt/Ni-Foam Hydrogenation Catalysts
Bibliographic record
Abstract
Galvanic exchange seeds the growth of Pt nanostructures on the Ni foam monolith. Subsequent atomic layer deposition of ultrathin Al 2 O 3 followed by annealing under air affords supported Pt catalysts with ultralow loading (0.020 ppm). In addition to the expected enhancement of the stability of the Pt particles on the surface, the ∼2 nm Al 2 O 3 overcoat appears to also play a crucial role in the overall structural integrity of the NiO x nanoplates that grow on the Ni foam surface as a result of the preparative route. The resulting material is physically robust toward repeated handling and showcases retention of catalytic activity over 10 standard catalyst recycling trials, standing in marked contrast to the uncoated samples. Catalyst activity was tested via the hydrogenation of various functionalized styrenes at low temperatures and low hydrogen pressure in ethanol as a solvent, with a TOF as high as 9.5 × 10 6 h –1 for unfunctionalized styrene. Notably, the catalysts show excellent tolerance toward F, Cl, and Br substituents and no hydrogenation of the aromatic ring.
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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".