The next big thing for silicon nanostructures – CO<sub>2</sub> photocatalysis
Bibliographic record
Abstract
Silicene is a relatively new member of the growing family of two-dimensional single-element materials. Both top-down and bottom-up approaches provide access to silicene, the former via vapor deposition on a substrate and the latter via exfoliation of the layered CaSi2 precursor. Most top-down research has been concerned with understanding the various electronic, optical, magnetic, mechanical, electrical, thermal transport and gas-adsorption properties of silicene. By contrast, the focus on bottom-up silicene has primarily been on its synthesis, structure and chemical properties as they relate to its function and utility. Herein, emphasis is placed on the bottom-up strategy because of its scalability and the ease of subsequent silicene modification, with both qualities being important prerequisites for heterogeneous catalysis applications. In this context, synthetic freestanding silicene exists as single sheets or multilayer assemblies, depending on the CaSi2 exfoliation synthesis conditions. The structure of a sheet comprises three connected chair-configuration silicon 6-rings. This connectivity creates buckled sheets in which the hybridization around the unsaturated silicon atoms is sp2-sp3. By adjusting the CaSi2 exfoliation synthesis conditions, either layered silane (Si6H6) or siloxene (Si6H3(OH)3) nanosheets can be obtained. In our studies, we have explored the nucleation and growth of different transition metal nanoparticles on and within the layer spaces of these nanosheets, and explored their thermochemical and photochemical reactivity in CO2 hydrogenation reactions. An overview of these findings, related works and a new-and-optimized catalyst are provided in this article.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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 teacher head, 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".