Scandium-III-nitrides: A New Material Platform for Semiconductor Photocatalysts with High Reducing Power
Bibliographic record
Abstract
Semiconductor nanowires have become emerging photocatalysts in artificial photosynthesis processes for solar fuel production. For reduction reactions, semiconductor photocatalysts with high reducing powers are highly desirable, especially for chemicals that are extremely difficult to reduce. This study introduces a new semiconductor photocatalyst, scandium (Sc)-III-nitrides, which have higher reducing powers than all conventional semiconductor photocatalysts. In specific, we focus on Sc x Ga 1– x N (ScGaN) nanowires. The detailed material synthesis and characterization of such nanowires are explored, and the photocatalytic reduction of carbon dioxide (CO 2 ), as an example of chemicals that are difficult to reduce, is also performed. The photocatalytic CO 2 reduction using GaN, a well-known high-performance semiconductor photocatalyst, is conducted as well as a reference. It is found that compared to using GaN nanowires, using ScGaN nanowires can significantly increase the production rate of formic acid (HCOOH). Moreover, ScGaN nanowires can further reduce HCOOH to methanol (CH 3 OH).
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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 | 0.000 | 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) | 0.000 | 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 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".