Shape Effect of Zinc Nanostructures on Electrochemical CO<sub>2</sub> Reduction
Bibliographic record
Abstract
To mitigate CO2 emissions and enable the conversion of CO2 to carbon-neutral fuels, the research on electrochemical reduction of CO2 (CO2RR) is gaining momentum. As an earth-abundant material, Zn is a promising electrocatalyst for highly active and selective reduction for the reduction of CO2 to CO. However, the shape effect of the Zn-based electrocatalysts on CO2RR has not been well understood. Herein, we synthesized hexagonal Zn nanoplates and systematically explored its shape-dependent catalytic activity for CO2RR, so as to achieve a better understanding of the relationship between the morphology and the catalytic activity of non-noble metal catalysts. Compared with the similarly-sized Zn nanoparticles, the H-Zn-NPs exhibit remarkably enhanced current density, together with an improved CO Faradaic efficiency of over 85% in a wide potential window. Theoretical results reveal that the unique hexagonal Zn nanostructure offers an increased number of catalytically active sites which are active for CO2RR to CO.
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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".