Photochemical Carbon Dioxide Reduction on Mg-Doped Ga(In)N Nanowire Arrays under Visible Light Irradiation
Bibliographic record
Abstract
The photochemical reduction of carbon dioxide (CO 2 ) into energy-rich products can potentially address some of the critical challenges we face today, including energy resource shortages and greenhouse gas emissions. Our ab initio calculations show that CO 2 molecules can be spontaneously activated on the clean nonpolar surfaces of wurtzite metal nitrides, for example, Ga(In)N. We have further demonstrated the photoreduction of CO 2 into methanol (CH 3 OH) with sunlight as the only energy input. A conversion rate of CO 2 into CH 3 OH (∼0.5 mmol g cat –1 h –1 ) is achieved under visible light illumination (>400 nm). Moreover, we have discovered that the photocatalytic activity for CO 2 reduction can be drastically enhanced by incorporating a small amount of Mg dopant. The definitive role of Mg dopant in Ga(In)N, at both the atomic and device levels, has been identified. This study reveals the potential of III-nitride semiconductor nanostructures in solar-powered reduction of CO 2 into hydrocarbon fuels.
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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".