Heterogeneous reduction of carbon dioxide by hydride-terminated silicon nanocrystals
Bibliographic record
Abstract
Silicon constitutes 28% of the earth's mass. Its high abundance, lack of toxicity and low cost coupled with its electrical and optical properties, make silicon unique among the semiconductors for converting sunlight into electricity. In the quest for semiconductors that can make chemicals and fuels from sunlight and carbon dioxide, unfortunately the best performers are invariably made from rare and expensive elements. Here we report the observation that hydride-terminated silicon nanocrystals with average diameter 3.5 nm, denoted ncSi:H, can function as a single component heterogeneous reducing agent for converting gaseous carbon dioxide selectively to carbon monoxide, at a rate of hundreds of μmol h(-1) g(-1). The large surface area, broadband visible to near infrared light harvesting and reducing power of SiH surface sites of ncSi:H, together play key roles in this conversion. Making use of the reducing power of nanostructured hydrides towards gaseous carbon dioxide is a conceptually distinct and commercially interesting strategy for making fuels directly from sunlight.
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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".