Active Sites of Zn Catalysts for CO<sub>2</sub> Electroreduction to CO
Bibliographic record
Abstract
Electrochemical CO2 reduction reaction (CO2RR) is an attractive strategy to mitigate CO2 emissions and enable the conversion of CO2 to valuable fuels. To date, noble metals, such as Ag, Au and Pd, have been reported as the benchmarking electrocatalysts to selectively convert CO2 to CO, but their scarcity and the associated high cost inevitably limit their large-scale applications. Zn holds the promise as a potential alternative to noble metals due to its earth-abundance and intrinsic selectivity for CO production. However, systematic studies that clarify the active sites of Zn catalysts for CO2RR are presently lacking in the literature. In response, density functional theory (DFT) calculations were used in this study to identify the active sites for CO2RR to CO based on a Zn50 model. The binding energies of the key intermediates for CO2RR and the competitive hydrogen evolution reaction (HER) on Zn(100) facet, Zn(002) facet, edge and corner sites were calculated. The Gibbs free energy diagrams for CO2RR and HER were then constructed based on the computational hydrogen electrode model. The results of this work that can guide further experiments to achieve highly efficient CO2RR over Zn-based catalysts.
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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 | 0.001 | 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".